Exergetic, Energetic and Environmental Dimensions [1 ed.] 9780128137345

Table of contents :
Front-Matter_2018_Exergetic--Energetic-and-Environmental-Dimensions.pdf (p.1)
Exergetic, Energetic and Environmental Dimensions
Copyright_2018_Exergetic--Energetic-and-Environmental-Dimensions.pdf (p.2)
Copyright
List-of-Contributors_2018_Exergetic--Energetic-and-Environmental-Dimensions.pdf (p.3-10)
List of Contributors
Preface_2018_Exergetic--Energetic-and-Environmental-Dimensions.pdf (p.11-12)
Preface
Chapter-1-1---Potential-Energy-Solutions-_2018_Exergetic--Energetic-and-Envi.pdf (p.13-47)
1.1 - POTENTIAL ENERGY SOLUTIONS FOR BETTER SUSTAINABILITY
1. INTRODUCTION
2. CRITICAL CHALLENGES
3. POTENTIAL SOLUTIONS
4. HYDROGEN ENERGY
5. RENEWABLE ENERGY
6. CLEAN ENERGY RESEARCH LABORATORY AS A WORLD-LEADING CENTER
7. THERMOCHEMICAL AND HYBRID HYDROGEN PRODUCTION CYCLES
8. PHOTONIC HYDROGEN PRODUCTION
9. AMMONIA
10. SYSTEM INTEGRATION AND MULTIGENERATION
11. COMPARATIVE ASSESSMENTS
11.1 RENEWABLES
11.2 HYDROGEN
11.3 AMMONIA
12. CONCLUSIONS
ABBREVIATIONS
REFERENCES
Chapter-1-2---Net-Zero-Energy-Residential-B_2018_Exergetic--Energetic-and-En.pdf (p.48-62)
1.2 - NET ZERO ENERGY RESIDENTIAL BUILDING ARCHITECTURE IN THE FUTURE
1. INTRODUCTION
2. SOLAR DECATHLON
3. METHODS
4. ENERGY BALANCE SUBCONTEST
4.1 ARCHITECTURAL CHARACTERISTICS
4.2 PASSIVE STRATEGIES
4.3 ACTIVE STRATEGIES
4.4 ENERGY PRODUCTION
4.5 OTHER STRATEGIES
5. CONCLUSIONS
REFERENCES
Chapter-1-3---Achieving-Green-Building-Standards-v_2018_Exergetic--Energetic.pdf (p.63-77)
1.3 - ACHIEVING GREEN BUILDING STANDARDS VIA ENERGY EFFICIENCY RETROFIT: A CASE STUDY OF AN INDUSTRIAL FACILITY
1. INTRODUCTION
2. GREEN BUILDINGS
2.1 GREEN BUILDING REQUIREMENTS
2.1.1 Water Efficiency
2.1.2 Energy Efficiency
2.1.3 Indoor Environmental Quality
2.1.4 Materials and Resources
2.1.5 Green Energy Audit of Buildings
3. CASE STUDY
3.1 CLIMATE CONDITIONS
3.2 THERMOGRAPHIC INSPECTION
3.3 LIGHTING AUDIT
3.4 PROPOSING RETROFIT ACTIONS
3.5 COST-BENEFIT ANALYSIS
4. CONCLUSIONS
ABBREVIATIONS
REFERENCES
Chapter-1-4---A-New-Approach-for-a-Control-Syste_2018_Exergetic--Energetic-a.pdf (p.78-92)
1.4 - A NEW APPROACH FOR A CONTROL SYSTEM OF AN INNOVATIVE BUILDING-INTEGRATED PHOTOBIOREACTOR
1. INTRODUCTION
2. BUILDING-INTEGRATED PHOTOBIOREACTORS
2.1 THERMAL COMFORT
2.2 VISUAL COMFORT
2.3 RENEWABLE ENERGY PRODUCTION
2.4 CARBON SEQUESTRATION POTENTIAL
3. LIMITING FACTORS FOR ALGAE CULTIVATION
3.1 LIGHT PROFILE
3.2 AMOUNT OF GASES
3.3 MIXING
3.4 TEMPERATURE
3.5 PH
3.6 SALINITY
4. CONTROL SYSTEM DESIGN
5. RESULTS
6. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-1-5---Multicriteria-Selection-Factors-for-E_2018_Exergetic--Energeti.pdf (p.93-108)
1.5 - MULTICRITERIA SELECTION FACTORS FOR EVALUATION OF INTELLIGENT BUILDINGS—A NOVEL APPROACH FOR ENERGY MANAGEMENT
1. INTRODUCTION
2. LITERATURE REVIEW
2.1 ENERGY CONSUMPTION
2.2 INTELLIGENT BUILDINGS
3. METHODOLOGY
3.1 PHASE I: IDENTIFY THE DECISION CRITERIA
3.2 PHASE II: ASSESSING THE ACCURACY OF THE FINDINGS OF THE PREVIOUS STEP THROUGH QUESTIONING THE EXPERTS
3.3 PHASE III: CREATE THE MODEL
4. RESULTS AND DISCUSSION
5. CONCLUSIONS
REFERENCES
Chapter-1-6---The-Place-of-Coal-Production-_2018_Exergetic--Energetic-and-En.pdf (p.109-119)
1.6 - THE PLACE OF COAL PRODUCTION AND CONSUMPTION IN TURKEY'S ECONOMY
1. INTRODUCTION
2. COAL TYPES AND PROPERTIES
3. COAL RESERVES AND PRODUCTION IN THE WORLD AND TURKEY
4. OCCUPATIONAL ACCIDENTS IN COAL MINING
5. COAL PROFIT-LOSS ANALYSIS
6. RESULTS AND DISCUSSION
7. CONCLUSIONS
REFERENCES
Chapter-1-7---Long-term-Energy-Demand-and-Sup_2018_Exergetic--Energetic-and-.pdf (p.120-137)
1.7 - LONG-TERM ENERGY DEMAND AND SUPPLY PROJECTIONS AND EVALUATIONS FOR TURKEY
1. INTRODUCTION
2. ENERGY CONSUMPTION IN TURKEY
2.1 THE STRUCTURE OF THE ENERGY SECTOR IN TURKEY
2.2 THE STRUCTURE OF THE ELECTRICITY SECTOR IN TURKEY
3. METHODOLOGY
4. RESULTS AND DISCUSSION
4.1 ENERGY DEMAND SCENARIOS
4.1.1 Business-as-Usual Scenario
4.1.2 Mitigation Scenario
4.2 ELECTRICITY GENERATION SCENARIOS
4.2.1 Hydro Scenario
4.2.2 Nuclear Scenario
4.2.3 Geo and Wind Scenario
4.2.4 Total Scenario
5. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-1-8---Comparison-of-ANN--Regression-Analysis-_2018_Exergetic--Energe.pdf (p.138-153)
1.8 - COMPARISON OF ANN, REGRESSION ANALYSIS, AND ANFIS MODELS IN ESTIMATION OF GLOBAL SOLAR RADIATION FOR DIFFEREN ...
1. INTRODUCTION
2. MATERIALS AND METHODS
2.1 ARTIFICIAL NEURAL NETWORK
2.2 REGRESSION ANALYSIS
2.3 ADAPTIVE NETWORK-BASED FUZZY INFERENCE SYSTEM
3. RESULTS AND DISCUSSION
4. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-1-9---Production-Planning-Using-Day_2018_Exergetic--Energetic-and-En.pdf (p.154-171)
1.9 - PRODUCTION PLANNING USING DAY-AHEAD PRICES IN A CEMENT PLANT
1. INTRODUCTION
2. SYSTEM DESCRIPTION
2.1 CEMENT INDUSTRY
2.2 THE CEMENT SECTOR
2.3 DAY-AHEAD MARKET
2.4 LINEAR PROGRAMMING AND MIXED INTEGER PROGRAMMING
2.5 THE PROPOSED METHODOLOGY
2.6 THE MIXED INTEGER PROGRAMMING MODEL
3. RESULTS AND DISCUSSION
4. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-1-10---The-Importance-of-Ships-in-the_2018_Exergetic--Energetic-and-.pdf (p.172-183)
1.10 - THE IMPORTANCE OF SHIPS IN THE NEXT-GENERATION ELECTRIC POWER SYSTEMS
1. INTRODUCTION
2. SYSTEMS DESCRIPTION
3. CASE STUDY
4. RESULTS AND DISCUSSION
5. CONCLUSION
NOMENCLATURE
REFERENCES
Chapter-1-11---Ventilation-Strategies-for-the-Preve_2018_Exergetic--Energeti.pdf (p.184-197)
1.11 - VENTILATION STRATEGIES FOR THE PREVENTIVE CONSERVATION OF MANUSCRIPTS IN THE NECIP PAŞA LIBRARY, İZMIR, TURKEY
1. INTRODUCTION
2. NECIP PAŞA LIBRARY
3. DESCRIPTION OF METHOD
3.1 MEASUREMENTS
3.2 BUILDING ENERGY PERFORMANCE MODELING AND CALIBRATION
3.3 ASSESSMENT OF CHEMICAL DEGRADATION RISK
4. RESULTS AND DISCUSSION
4.1 RESULTS OF MEASUREMENTS
4.2 RESULTS OF MODEL CALIBRATION
4.3 CONFIGURATION OF SIMULATION CASES
4.3.1 Case 1: Mechanical Ventilation
4.3.2 Case 2: Natural Ventilation
4.4 DISCUSSION
5. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-1-12---Effect-of-Double-Skin-Fa-ade-on-T_2018_Exergetic--Energetic-a.pdf (p.198-214)
1.12 - EFFECT OF DOUBLE-SKIN FAÇADE ON THERMAL ENERGY LOSSES IN BUILDINGS: A CASE STUDY IN TABRIZ
1. INTRODUCTION
2. DESCRIPTION OF SYSTEMS
2.1 MATHEMATICAL MODELING
2.2 VALIDATION
2.3 COMPUTER SIMULATION
3. RESULTS AND DISCUSSION
4. SUMMARY AND CONCLUSION
NOMENCLATURE
REFERENCES
Chapter-2-1---Energy-and-Exergy-Analyses-of-a-G_2018_Exergetic--Energetic-an.pdf (p.215-233)
2.1 - ENERGY AND EXERGY ANALYSES OF A GEOTHERMAL-BASED INTEGRATED SYSTEM FOR TRIGENERATION
1. INTRODUCTION
2. SYSTEM DESCRIPTION
3. THERMODYNAMIC ANALYSIS
4. RESULTS AND DISCUSSION
4.1 EFFECT OF DISTRICT COOLING ON SYSTEM EFFICIENCIES
4.2 EFFECT OF DISTRICT HEATING ON SYSTEM EFFICIENCIES
4.3 EFFECT OF TURBINE ISENTROPIC EFFICIENCIES ON OVERALL SYSTEM PERFORMANCE
4.4 EFFECT OF GEOTHERMAL FLUID TEMPERATURE ON SYSTEM EFFICIENCIES
4.5 EFFECT OF AMBIENT TEMPERATURE ON SYSTEM EFFICIENCIES
5. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-2---Comparative-Assessment-of-Three-I_2018_Exergetic--Energetic-an.pdf (p.234-253)
2.2 - COMPARATIVE ASSESSMENT OF THREE INTEGRATED TRIGENERATION SYSTEMS FOR DAIRY FARMS
1. INTRODUCTION
2. SYSTEM DESCRIPTION
2.1 BACKGROUND DETAILS
2.2 SYSTEM ENERGY DETAILS
2.3 SPECIFIC SYSTEM DETAILS
3. THERMODYNAMIC ANALYSIS
4. RESULTS AND DISCUSSION
5. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-3---Performance-Assessment-of-a-Biomass_2018_Exergetic--Energetic-.pdf (p.254-278)
2.3 - PERFORMANCE ASSESSMENT OF A BIOMASS-FIRED REGENERATIVE ORC SYSTEM THROUGH ENERGY AND EXERGY ANALYSES
1. INTRODUCTION
1.1 ENERGY RESOURCES OF THE ORGANIC RANKINE CYCLE
1.1.1 Geothermal Applications
1.1.2 Solar Applications
1.1.3 Waste Heat Applications
1.1.4 Biomass Applications
2. SYSTEM DESCRIPTION
3. MATHEMATICAL MODEL
3.1 ENERGY ANALYSIS
3.2 EXERGY ANALYSIS
3.3 PERFORMANCE ASSESSMENT PARAMETERS
4. RESULTS AND DISCUSSION
4.1 VALIDATION
4.2 PARAMETRIC STUDIES
4.2.1 Variation of Turbine Inlet Temperature
4.2.2 Variations in Excess Air Ratio
4.2.3 Variations in Mass Flow Rate of Dry Biomass
4.2.4 Variations in Biomass Fuels
5. CONCLUSIONS
REFERENCES
Chapter-2-4---Thermal-Design-and-Modeling-of-She_2018_Exergetic--Energetic-a.pdf (p.279-305)
2.4 - THERMAL DESIGN AND MODELING OF SHELL AND TUBE HEAT EXCHANGERS COMBINING PTSC AND ORC SYSTEMS
1. INTRODUCTION
2. SYSTEM DESCRIPTION
3. MATHEMATICAL MODELING
3.1 MATHEMATICAL MODELING OF PARABOLIC TROUGH SOLAR COLLECTOR
3.2 MATHEMATICAL MODELING OF SHELL AND TUBE HEAT EXCHANGERS
3.3 EXERGETIC ASSESSMENT OF THE HEAT EXCHANGER
4. RESULTS AND DISCUSSIONS
4.1 RESULTS FOR THE SEGMENTAL BAFFLE CONFIGURATION
4.1.1 Effect of Outer Diameter of the Tube on the Performance of the System
4.1.2 Effect of Baffle Spacing on the Performance of the System
4.2 RESULTS FOR HELICAL BAFFLE CONFIGURATIONS
4.2.1 Effects of Tube Diameter on the Performance of the System
4.2.2 Effect of Tube Length on the Performance of the System
4.2.3 Effect of the Shell-Side Mass Flow Rate on the Performance of the System
4.2.4 Effect of Solar Radiation on the Performance of the System
4.2.5 Results for the Exergetic Performance Assessment
5. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-5---CFD-Analysis-of-a-Solar-Geoth_2018_Exergetic--Energetic-and-En.pdf (p.306-321)
2.5 - CFD ANALYSIS OF A SOLAR-GEOTHERMAL SHELL AND TUBE HEAT EXCHANGER
1. INTRODUCTION
2. MODELING
2.1 MODEL DOMAIN AND INPUT PARAMETERS
2.2 MODEL ASSUMPTIONS AND GOVERNING EQUATIONS
2.3 EXERGETIC AND HEAT EXCHANGER EFFECTIVENESS CALCULATIONS
2.4 INLET AND BOUNDARY CONDITIONS
2.5 MESH GENERATION AND SOLUTION PROCEDURE
3. RESULTS AND DISCUSSIONS
3.1 THE EFFECT OF THE SHELL-SIDE MASS FLOW RATE ON THE STHX'S VELOCITY AND TEMPERATURE DISTRIBUTIONS
3.2 THE RATE OF HEAT TRANSFER, EXERGETIC EFFICIENCY, AND HEAT EXCHANGER EFFECTIVENESS FOR DIFFERENT SHELL-SIDE MASS FLOW RATES
4. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-6---Numerical-Investigation-of-Fixe_2018_Exergetic--Energetic-and-.pdf (p.322-338)
2.6 - NUMERICAL INVESTIGATION OF FIXED-BED DOWNDRAFT WOODY BIOMASS GASIFICATION
1. INTRODUCTION
1.1 THE STOICHIOMETRIC EQUILIBRIUM MODEL
1.2 NONSTOICHIOMETRIC EQUILIBRIUM MODEL
2. WOOD PELLET EXPERIMENTS
3. NUMERICAL PROCEDURE
4. RESULTS AND DISCUSSION
5. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-7---Passive-Thermal-Management-of-a-P_2018_Exergetic--Energetic-an.pdf (p.339-350)
2.7 - PASSIVE THERMAL MANAGEMENT OF A PHOTOVOLTAIC PANEL: INFLUENCE OF FIN ARRANGEMENTS
1. INTRODUCTION
2. MATERIALS AND METHODS
3. RESULTS AND DISCUSSION
3.1 VALIDATION
3.2 PARAMETRIC RESULTS
4. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-8---Thermal-Performance-of-a-Sola_2018_Exergetic--Energetic-and-En.pdf (p.351-360)
2.8 - THERMAL PERFORMANCE OF A SOLAR ROOM HEATER WITH EVACUATED TUBES
1. INTRODUCTION
2. DESIGN AND INSTALLATION OF THE SOLAR HEATING SYSTEM
3. EXPERIMENTS AND RESULTS
4. TEST ROOM HEAT LOSS CALCULATION AND SYSTEM'S PERFORMANCE FOR HEATING SEASON
5. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-9---Thermodynamic-Assessment-of-an-Inte_2018_Exergetic--Energetic-.pdf (p.361-379)
2.9 - THERMODYNAMIC ASSESSMENT OF AN INTEGRATED SOLAR COLLECTOR SYSTEM FOR MULTIGENERATION PURPOSES
1. INTRODUCTION
2. SYSTEMS DESCRIPTION
3. THERMODYNAMIC ASSESSMENT
3.1 MASS BALANCE ANALYSIS
3.2 ENERGY BALANCE ANALYSIS
3.2.1 Concentrating Collector
3.2.2 Rankine Cycle
3.2.3 Double-Effect Absorption Cooling Subsystem
3.2.4 Proton-Exchange Membrane Electrolyzer
3.3 EXERGY BALANCE ANALYSIS
3.4 ENERGY AND EXERGY EFFICIENCIES OF THE INTEGRATED SYSTEM
4. RESULTS AND DISCUSSION
5. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-10---Energy--Exergy-and-Exergoecono_2018_Exergetic--Energetic-and-.pdf (p.380-399)
2.10 - ENERGY, EXERGY AND EXERGOECONOMIC ANALYSIS OF A SOLAR PHOTOVOLTAIC MODULE
1. INTRODUCTION
2. SYSTEM DESCRIPTION
3. ANALYSES
3.1 ENERGY ANALYSIS
3.2 EXERGY ANALYSIS
3.3 EXERGOECONOMIC ANALYSIS
4. RESULTS AND DISCUSSION
4.1 ENERGY AND EXERGY ANALYSIS
4.2 EXERGOECONOMIC ANALYSIS
5. CONCLUSION
NOMENCLATURE
REFERENCES
Chapter-2-11---Exergetic-and-Energetic-Performanc_2018_Exergetic--Energetic-.pdf (p.400-417)
2.11 - EXERGETIC AND ENERGETIC PERFORMANCE EVALUATION OF A FLAT PLATE SOLAR COLLECTOR IN DYNAMIC BEHAVIOR
1. INTRODUCTION
2. MODELING
2.1 MODELING OF SOLAR COLLECTOR
2.1.1 Energy Analysis
2.1.1.1 Heat Balance for the Transparent Cover
2.1.1.2 Heat Balance for the Air Gap
2.1.1.3 Heat Balance for the Absorber
2.1.1.4 Heat Balance for the Transfer Fluid
2.1.2 Exergy Analysis
2.2 MODELING OF SOLAR RADIATION
3. NUMERICAL CALCULATIONS
4. RESULTS AND DISCUSSION
5. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-12---Performance-Assessment-of-Variou_2018_Exergetic--Energetic-an.pdf (p.418-430)
2.12 - PERFORMANCE ASSESSMENT OF VARIOUS GREENHOUSE HEATING SYSTEMS; A CASE STUDY IN ANTALYA
1. INTRODUCTION
2. SYSTEM DESCRIPTION
3. ANALYSIS
4. RESULTS AND DISCUSSION
5. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-13---Energy--Exergy--and-Exergoenvironmental-_2018_Exergetic--Ener.pdf (p.431-451)
2.13 - ENERGY, EXERGY, AND EXERGOENVIRONMENTAL ASSESSMENTS OF SOLAR-ASSISTED ABSORPTION COOLING SYSTEMS AND CONVENT ...
1. INTRODUCTION
2. DESCRIPTION OF THE SYSTEM
3. ENERGETIC AND EXERGETIC ANALYSES
3.1 HELIOSTAT SOLAR FIELD SYSTEM
3.1.1 Rankin Cycle
3.1.1.1 Conventional System
3.1.2 Absorption Systems
4. RESULTS AND DISCUSSIONS
4.1 EFFECTS OF EVAPORATOR TEMPERATURE THE ENERGETIC AND EXERGETIC COEFFICIENTS OF PERFORMANCE
4.2 EFFECTS OF EVAPORATOR TEMPERATURE ON EXERGOENVIRONMENTAL IMPACT FACTORS
4.3 EFFECTS OF EVAPORATOR TEMPERATURE ON EXERGOENVIRONMENTAL IMPACT COEFFICIENTS
4.4 EFFECTS OF EVAPORATOR TEMPERATURE ON THE EXERGOENVIRONMENTAL IMPACT INDEXES
4.5 EFFECTS OF EVAPORATOR TEMPERATURE ON IMPROVING EXERGOENVIRONMENTAL IMPACT
4.6 EFFECTS OF EVAPORATOR TEMPERATURE ON EXERGETIC STABILITIES
4.7 EFFECTS OF EVAPORATOR TEMPERATURE ON THE EXERGETIC SUSTAINABILITY INDEXES
4.8 EFFECTS OF AMBIENT TEMPERATURE ON ENERGETIC AND EXERGETIC COEFFICIENTS OF PERFORMANCE
4.9 EFFECTS OF VARIATION IN AMBIENT TEMPERATURE ON EXERGY DESTRUCTION RATES
5. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-14---Comparative-Study-of-Two-Solar-Cascad_2018_Exergetic--Energet.pdf (p.452-469)
2.14 - COMPARATIVE STUDY OF TWO SOLAR CASCADE ABSORPTION-COMPRESSION REFRIGERATION SYSTEMS BASED ON ENERGY AND EXER ...
1. INTRODUCTION
2. SYSTEM DESCRIPTION
3. MODEL SIMULATION
3.1 THE FLAT-PLATE COLLECTOR SIMULATION
3.2 THE THERMAL STORAGE TANK SIMULATION
3.3 THE EJECTOR SIMULATION
3.4 EXERGY ANALYSIS
4. THERMODYNAMIC PERFORMANCE
5. RESULTS AND DISCUSSION
6. PARAMETRIC STUDY
6.1 NANOPARTICLES VOLUME FRACTION INFLUENCE
6.2 COLLECTOR TILT ANGLE INFLUENCE
6.3 COLLECTOR AREA INFLUENCE
6.4 LOW PRESSURE INFLUENCE
7. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-15---Comparative-Study-of-Active-and-Pa_2018_Exergetic--Energetic-.pdf (p.470-500)
2.15 - COMPARATIVE STUDY OF ACTIVE AND PASSIVE COOLING TECHNIQUES FOR CONCENTRATED PHOTOVOLTAIC SYSTEMS
1. INTRODUCTION
2. PHYSICAL MODEL
3. MATHEMATICAL MODEL
3.1 PHOTOVOLTAIC MODULE LAYERS
3.2 MICROCHANNEL HEAT SINK DOMAIN
3.3 PHASE CHANGE MATERIAL HEAT SINK DOMAIN
3.4 BOUNDARY CONDITIONS
3.5 SOLUTION METHODS AND CONVERGENCE CRITERIA
3.6 NUMERICAL RESULTS VALIDATION
3.6.1 Uncooled Concentrated Photovoltaic System Validation
3.6.2 Microchannel Heat Sink Validation
3.6.3 Phase Change Material Heat Sink Validation
4. RESULTS AND DISCUSSION
4.1 ACTIVE COOLING TECHNIQUE USING MICROCHANNEL HEAT SINK
4.1.1 Effect of Manifold Pitch
4.1.2 Average Solar Cell Temperature Comparison
4.1.3 Local Solar Cell Temperature Comparison
4.1.4 Net Gained Electrical Power Comparison
4.2 PASSIVE COOLING TECHNIQUE USING PHASE CHANGE MATERIAL
4.2.1 Thermal Performance of the Concentrated Photovoltaic–Phase Change Material System Without Fins
4.2.2 Thermal Performance Comparison for Concentrated Photovoltaic–Phase Change Material Systems With a Different Number of Fins
4.3 COMPARISON BETWEEN THE PROPOSED ACTIVE AND PASSIVE COOLING TECHNIQUES
5. CONCLUSION
NOMENCLATURE
REFERENCES
2.15 . APPENDIX A
AUXILIARY EQUATIONS USED IN THE CURRENT MODEL
Chapter-2-16---Optimization-of-Slope-Angles-o_2018_Exergetic--Energetic-and-.pdf (p.501-515)
2.16 - OPTIMIZATION OF SLOPE ANGLES OF PHOTOVOLTAIC ARRAYS FOR DIFFERENT SEASONS
1. INTRODUCTION
2. MATHEMATICAL MODEL
2.1 PV ARRAY
2.2 THE LATITUDE AND LONGITUDE OF ANY POINT ON EARTH
2.3 CALCULATION OF SOLAR ANGLES
3. RESULTS AND DISCUSSION
3.1 GEOGRAPHICAL LOCATION AND INSOLATION LEVEL
3.2 APPLICATIONS OF OPTIMAL SLOPE ANGLES FOR DIFFERENT SEASONS
4. CONCLUSION
NOMENCLATURE
REFERENCES
Chapter-2-17---Design--Energy-and-Exergy-An_2018_Exergetic--Energetic-and-En.pdf (p.516-525)
2.17 - DESIGN, ENERGY AND EXERGY ANALYSES OF LINEAR FRESNEL REFLECTOR
1. INTRODUCTION
2. SYSTEM DESCRIPTION
2.1 DESIGN PARAMETERS
2.2 ENERGY AND EXERGY ANALYSES
3. RESULTS AND DISCUSSION
4. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-18---Integration-of-Reflectors-to-Imp_2018_Exergetic--Energetic-an.pdf (p.526-542)
2.18 - INTEGRATION OF REFLECTORS TO IMPROVE ENERGY PRODUCTION OF HYBRID PVT COLLECTORS
1. INTRODUCTION
2. SYSTEM DESCRIPTION
3. EXPERIMENTAL APPARATUS AND PROCEDURE
4. RESULTS AND DISCUSSION
5. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-19---Thermodynamic-and-Thermoeconom_2018_Exergetic--Energetic-and-.pdf (p.543-559)
2.19 - THERMODYNAMIC AND THERMOECONOMIC COMPARISONS OF TWO TRIGENERATION SYSTEMS
1. INTRODUCTION
2. SYSTEM DESCRIPTION
3. ENERGY ANALYSIS
4. EXERGY ANALYSIS
5. THERMOECONOMIC ANALYSIS
5.1 THERMOECONOMIC EVALUATION
5.1.1 Average Cost of Fuel
5.1.2 Average Cost of Product
5.1.3 Cost Rate of Exergy Destruction
5.1.4 Cost Rate of Exergy Loss
5.1.5 Relative Cost Difference
5.1.6 Thermoeconomic Factor
6. RESULTS AND DISCUSSION
7. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-20---Comparative-Evaluation-of-Possibl_2018_Exergetic--Energetic-a.pdf (p.560-573)
2.20 - COMPARATIVE EVALUATION OF POSSIBLE DESALINATION OPTIONS WITH VARIOUS NUCLEAR POWER PLANTS
1. INTRODUCTION
2. DESALINATION METHODS
3. COST ASSESSMENT
4. SYSTEM DESCRIPTION
5. RESULTS AND DISCUSSION
6. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-21---Comparative-Evaluation-of-Possibl_2018_Exergetic--Energetic-a.pdf (p.574-587)
2.21 - COMPARATIVE EVALUATION OF POSSIBLE DESALINATION OPTIONS FOR AKKUYU NUCLEAR POWER PLANT
1. INTRODUCTION
2. SYSTEM DESCRIPTION
2.1 DESALINATION METHODS
2.1.1 Multiple Effect Distillation
2.1.2 Multistage Flash
2.1.3 Reverse Osmosis
2.2 DEEP SOFTWARE
2.3 AKKUYU NUCLEAR POWER PLANT
3. ASSUMPTIONS AND METHOD OF THE STUDY
4. ANALYSIS OF THE STUDY
5. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-22---Determination-of-Flow-Character_2018_Exergetic--Energetic-and.pdf (p.588-602)
2.22 - DETERMINATION OF FLOW CHARACTERISTICS OF MULTIPLE SLOT JET IMPINGEMENT COOLING
1. INTRODUCTION
1.1 A SINGLE CONFINED SLOT JET
1.2 ARRAY OF SLOT JETS
2. MATERIALS AND METHOD
2.1 DEFINITION OF THE PROBLEM
2.2 GOVERNING EQUATION AND SOLUTION METHOD
2.3 BOUNDARY CONDITIONS AND MESH INDEPENDENCY
3. RESULTS AND DISCUSSIONS
3.1 VALIDATION OF METHODOLOGY
3.2 PARAMETRIC RESULTS
4. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-23---A-Numerical-Study-on-Phase-C_2018_Exergetic--Energetic-and-En.pdf (p.603-615)
2.23 - A NUMERICAL STUDY ON PHASE CHANGE INSIDE A SPHERICAL CAPSULE
1. INTRODUCTION
2. MATERIALS AND METHODS
2.1 CHARACTERIZATION OF THE PHASE-CHANGE MATERIAL
2.2 DEFINITION OF THE PROBLEM
2.3 SOLUTION METHOD
2.4 VALIDATION OF THE MODEL
3. RESULTS AND DISCUSSION
3.1 EFFECT OF FREE STREAM TEMPERATURE
3.2 EFFECT OF HEAT TRANSFER COEFFICIENT
4. CONCLUSIONS
NOMENCLATURE
ACKNOWLEDGMENTS
REFERENCES
Chapter-2-24---Energy-and-Exergy-Analyses-o_2018_Exergetic--Energetic-and-En.pdf (p.616-628)
2.24 - ENERGY AND EXERGY ANALYSES OF NITROGEN LIQUEFACTION PROCESS
1. INTRODUCTION
2. SYSTEM DESCRIPTION
3. ENERGY AND EXERGY ANALYSES
4. RESULTS AND DISCUSSION
5. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-25---Thermodynamic-Performance-Anal_2018_Exergetic--Energetic-and-.pdf (p.629-643)
2.25 - THERMODYNAMIC PERFORMANCE ANALYSIS OF A RAW MILL SYSTEM IN A CEMENT PLANT
1. INTRODUCTION
2. SYSTEM DESCRIPTION
3. THERMODYNAMIC ASSESSMENT
3.1 MASS BALANCE
3.2 ENERGY BALANCE
3.3 EXERGY BALANCE
3.4 THERMODYNAMIC ANALYSIS OF SYSTEM COMPONENTS
3.4.1 Raw Mill
3.4.2 Filter Ventilation
3.4.3 Filter
3.4.4 Cooling Tower
3.4.5 Abgas Ventilation
3.4.6 Farine Silo
3.4.7 Airlift Compressor
3.4.8 Cyclone
3.5 ENERGY EFFICIENCY
3.6 EXERGY EFFICIENCY
4. RESULTS AND DISCUSSION
5. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-26---Experimental-and-Numerical-Invest_2018_Exergetic--Energetic-a.pdf (p.644-663)
2.26 - EXPERIMENTAL AND NUMERICAL INVESTIGATIONS OF CONDENSATION HEAT TRANSFER IN MULTIPORT TUBES
1. INTRODUCTION
2. EXPERIMENTAL FACILITY
2.1 EXPERIMENTAL PROGRAM
2.2 TEST FACILITY
2.3 DATA ACQUISITION AND REDUCTION
3. RESULTS AND DISCUSSION
3.1 SUBCOOLED LIQUID FLOW PRESSURE DROP
3.2 SUBCOOLED LIQUID HEAT TRANSFER
3.3 TWO-PHASE FLOW PRESSURE DROP
3.4 CONDENSATION HEAT TRANSFER
4. NUMERICAL ANALYSIS
4.1 NUMERICAL MODELING
4.2 SOFTWARE USE
4.3 SOFTWARE RESULTS
5. ARTIFICIAL NEURAL NETWORK ANALYSIS
6. CONCLUSION
NOMENCLATURE
REFERENCES
Chapter-2-27---Heat-and-Fluid-Flow-Analyses-_2018_Exergetic--Energetic-and-E.pdf (p.664-680)
2.27 - HEAT AND FLUID FLOW ANALYSES OF AN IMPINGING JET ON A CUBIC BODY
1. INTRODUCTION
2. MODELING PROCEDURE
3. RESULTS AND DISCUSSION
4. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-2-28---Gas-Diffusion-Layers-for-PEM-F_2018_Exergetic--Energetic-and-.pdf (p.681-713)
2.28 - GAS DIFFUSION LAYERS FOR PEM FUEL CELLS: EX- AND IN-SITU CHARACTERIZATION
1. INTRODUCTION
2. CHARACTERISTICS OF GAS DIFFUSION LAYER
2.1 POROSITY AND PORE SIZE DISTRIBUTION
2.2 ELECTRICAL CONDUCTIVITY
2.3 THERMAL CONDUCTIVITY
2.4 GAS PERMEABILITY
2.5 WETTABILITY
3. EX-SITU CHARACTERIZATION OF GAS DIFFUSION LAYER
3.1 POROSITY AND PORE SIZE DISTRIBUTION
3.1.1 Mercury Intrusion Porosimetry
3.1.2 Method of Standard Porosimetry
3.1.3 Capillary Flow Porometry
3.2 ELECTRICAL CONDUCTIVITY
3.2.1 Through-Plane Electrical Conductivity
3.2.2 In-Plane Electrical Conductivity
3.3 THERMAL CONDUCTIVITY
3.3.1 Through-Plane Thermal Conductivity
3.3.2 In-Plane Thermal Conductivity
3.3.2.1 Conventional In-Plane Thermal Conductivity Measurement
3.3.2.2 Parallel Thermal Conductance Technique
3.4 GAS PERMEABILITY
3.4.1 Through-Plane Gas Permeability
3.4.2 In-Plane Gas Permeability
3.5 WETTABILITY
3.5.1 Sessile Drop Technique
3.5.2 Wilhelmy Plate Technique
3.6 CLOSURE
4. IN-SITU CHARACTERIZATION OF GAS DIFFUSION LAYERS (ELECTROCHEMICAL PERFORMANCE ASSESSMENT)
4.1 EFFECT OF TYPE AND LOADING OF CARBON BLACK POWDER
4.2 EFFECT OF HYDROPHOBIC AND HYDROPHILIC TREATMENT
4.3 EFFECT OF MICROSTRUCTURE MODIFICATION
4.4 CLOSURE
5. SUMMARY
ACKNOWLEDGMENTS
REFERENCES
Chapter-3-1---Expert-Opinions-on-Natural-Gas-Ve_2018_Exergetic--Energetic-an.pdf (p.714-733)
3.1 - EXPERT OPINIONS ON NATURAL GAS VEHICLES RESEARCH NEEDS FOR ENERGY POLICY DEVELOPMENT
1. INTRODUCTION
2. METHODOLOGY
3. EVALUATION RESULTS
3.1 GENERAL QUESTIONS
3.2 TECHNICAL QUESTIONS
3.2.1 Areas of Research Opportunity
3.2.2 NGV Mileage
3.2.3 NGV Fueling Code Enforcement
3.2.4 NG Storage Technologies
3.2.5 Use of Renewable Gas in NGVs
4. DISCUSSION
5. CONCLUSIONS AND IMPLICATIONS
ACKNOWLEDGMENTS
REFERENCES
Chapter-3-2---An-Experimental-Study-on-Adsorption-C_2018_Exergetic--Energeti.pdf (p.734-744)
3.2 - AN EXPERIMENTAL STUDY ON ADSORPTION CHARACTERISTICS OF R134A AND R404A ONTO GRANULAR AND PELLET-TYPE ACTIVATE ...
1. INTRODUCTION
2. EXPERIMENTAL APPARATUS AND PROCEDURE
3. MATHEMATICAL APPROACH
4. RESULTS AND DISCUSSION
5. CONCLUSIONS
NOMENCLATURE
ACKNOWLEDGMENTS
REFERENCES
Chapter-3-3---MHD-Natural-Convection-and-Entropy-G_2018_Exergetic--Energetic.pdf (p.745-760)
3.3 - MHD NATURAL CONVECTION AND ENTROPY GENERATION IN A NANOFLUID-FILLED CAVITY WITH A CONDUCTIVE PARTITION
1. INTRODUCTION
2. MODELING
2.1 NANOFLUID EFFECTIVE THERMOPHYSICAL PROPERTIES
2.2 BOUNDARY CONDITIONS AND SOLUTION METHOD
3. RESULTS AND DISCUSSION
4. CONCLUSIONS
NOMENCLATURE
ACKNOWLEDGMENTS
REFERENCES
Chapter-3-4---Fabrication-and-Investigation-of-Si_2018_Exergetic--Energetic-.pdf (p.761-773)
3.4 - FABRICATION AND INVESTIGATION OF SILVER WATER NANOFLUIDS FOR LONG-TERM HEAT TRANSFER APPLICATION
1. INTRODUCTION
2. EXPERIMENTAL APPARATUS AND PROCEDURE
2.1 NANOFLUID FABRICATION
2.2 CHARACTERIZATION
2.3 EXPERIMENTAL SETUP
3. RESULTS AND DISCUSSION
3.1 ULTRAVIOLET-VISIBLE SPECTROSCOPY
3.2 THERMAL CONDUCTIVITY MEASUREMENT
3.3 ZETA POTENTIAL MEASUREMENT
3.4 SCANNING ELECTRON MICROSCOPY
3.5 HEAT PIPE PERFORMANCE
4. CONCLUSIONS
LIST OF SYMBOLS
ACKNOWLEDGMENTS
REFERENCES
Chapter-3-5---Microstructure-and-Oxidation-Behav_2018_Exergetic--Energetic-a.pdf (p.774-795)
3.5 - MICROSTRUCTURE AND OXIDATION BEHAVIOR OF ATMOSPHERIC PLASMA-SPRAYED THERMAL BARRIER COATINGS
1. INTRODUCTION
2. THERMAL BARRIER COATINGS
2.1 MATERIALS
2.1.1 Yttria-Stabilized Zirconia
2.1.2 Lanthanum Zirconate
2.1.3 Alumina (Al2O3)
2.1.4 Cerium Oxide
2.1.5 Mullite
2.2 STRUCTURE OF THERMAL BARRIER COATINGS
2.2.1 Ceramic Top Coat
2.2.2 Bond Coat
2.2.3 Substrate Superalloys
3. MANUFACTURING PROCESSES OF THERMAL BARRIER COATING
3.1 ELECTRON BEAM PHYSICAL VAPOR DEPOSITION
3.2 ATMOSPHERIC PLASMA SPRAY
3.3 HIGH-VELOCITY OXYGEN FUEL
4. FAILURE MECHANISMS AND PRECAUTIONS OF THERMAL BARRIER COATINGS
5. EXPERIMENTAL STUDIES: OXIDATION
6. CONCLUDING REMARKS
REFERENCES
Chapter-3-6---Research-on-the-Pyrolysis-Charact_2018_Exergetic--Energetic-an.pdf (p.796-809)
3.6 - RESEARCH ON THE PYROLYSIS CHARACTERISTICS OF TOMATO WASTE WITH FE–AL2O3 CATALYST
1. INTRODUCTION
2. EXPERIMENTAL FACILITY
2.1 BIOMASS FEEDSTOCK
2.2 PREPARATION AND CHARACTERIZATION OF CATALYTIC MATERIAL
2.3 PYROLYSIS EXPERIMENTS
2.4 CHARACTERIZATION OF BIO-OIL
3. RESULTS AND DISCUSSION
3.1 CATALYST CHARACTERIZATION
3.2 CATALYTIC PYROLYSIS EXPERIMENTS AND BIO-OIL CHARACTERIZATION
4. CONCLUSIONS
ACKNOWLEDGMENT
REFERENCES
Chapter-3-7---Regression-Models-for-Predicting-Some_2018_Exergetic--Energeti.pdf (p.810-831)
3.7 - REGRESSION MODELS FOR PREDICTING SOME IMPORTANT FUEL PROPERTIES OF CORN AND HAZELNUT OIL BIODIESEL–DIESEL FUE ...
1. INTRODUCTION
2. EXPERIMENTAL APPARATUS AND PROCEDURE
2.1 BIODIESEL PRODUCTION
2.2 MEASUREMENTS
3. RESULTS AND DISCUSSION
3.1 VISCOSITY VARIATIONS
3.1.1 Effect of Biodiesel Fraction
3.1.2 Effect of Temperature
3.2 FLASH POINT VARIATION
3.3 HIGHER HEATING VALUE VARIATION
4. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-3-8---Biodiesel-Synthesis-by-Using_2018_Exergetic--Energetic-and-Env.pdf (p.832-840)
3.8 - BIODIESEL SYNTHESIS BY USING THE SMART CATALYTIC MEMBRANE
1. INTRODUCTION
2. EXPERIMENTAL
2.1 MATERIALS
2.2 CATALYTIC MEMBRANE SYNTHESIS AND CHARACTERIZATION
2.3 CATALYTIC PERFORMANCE OF CATALYTIC BLEND MEMBRANES
3. RESULTS AND DISCUSSIONS
3.1 CATALYTIC MEMBRANE CHARACTERIZATION
3.1.1 Fourier Transform Infrared Spectroscopy
3.1.2 Thermogravimetric Analysis
3.2 SYNTHESIS OF BIODIESEL
3.2.1 Effect of Reaction Time
3.2.2 Effect of Methanol–Oleic Acid Molar Ratio
3.2.3 Effect of Catalyst Concentration
3.2.4 Effect of Reaction Temperature
4. CONCLUSIONS
NOMENCLATURE
ACKNOWLEDGMENTS
REFERENCES
Chapter-3-9---Waste-to-Energy-With-a-Combine-Mem_2018_Exergetic--Energetic-a.pdf (p.841-851)
3.9 - WASTE TO ENERGY WITH A COMBINE MEMBRANE TECHNOLOGY: BIOBUTANOL PRODUCTION AND PURIFICATION
1. INTRODUCTION
2. EXPERIMENTAL
2.1 MATERIALS
2.2 MEMBRANE PREPARATION
2.3 MEMBRANE CHARACTERIZATION
2.4 PERVAPORATION EXPERIMENTS
3. RESULTS AND DISCUSSION
3.1 MEMBRANE CHARACTERIZATION RESULTS
3.2 HYDROPHOBIC PERVAPORATION RESULTS
3.3 HYDROPHILIC PERVAPORATION RESULTS
3.4 COMPARISON WITH LITERATURE DATA
4. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-3-10---Research-on-Reaction-Parameters_2018_Exergetic--Energetic-and.pdf (p.852-873)
3.10 - RESEARCH ON REACTION PARAMETERS ABOUT HAZELNUT OIL METHYL ESTER PRODUCTION
1. INTRODUCTION
2. EXPERIMENTAL APPARATUS AND PROCEDURE
2.1 MATERIALS
2.2 REACTION PARAMETERS AND BIODIESEL PRODUCTION PROCEDURE
2.3 DENSITY MEASUREMENT PROCEDURE
2.4 DYNAMIC VISCOSITY MEASUREMENT PROCEDURE
2.5 UNCERTAINTY ANALYSIS
3. RESULTS AND DISCUSSIONS
3.1 IMPACT OF CATALYZER CONCENTRATION
3.2 IMPACT OF REACTION TEMPERATURE
3.3 IMPACT OF REACTION TIME
3.4 IMPACT OF ALCOHOL–OIL MOLAR RATIO
3.5 FATTY ACID METHYL ESTER COMPOSITION AND SOME FUEL PROPERTIES OF FINAL BIODIESEL
4. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-3-11---Evaluation-of-Bio-Oils-Produce_2018_Exergetic--Energetic-and-.pdf (p.874-888)
3.11 - EVALUATION OF BIO-OILS PRODUCED FROM POMEGRANATE PULP CATALYTIC PYROLYSIS
1. INTRODUCTION
2. EXPERIMENT
2.1 MATERIALS
2.2 PYROLYSIS
2.3 STRUCTURAL ANALYSES
3. RESULTS AND DISCUSSION
3.1 EFFECT OF CATALYSIS ON PRODUCT YIELDS
3.2 BIO-OIL CHARACTERIZATION
4. CONCLUSIONS
REFERENCES
Chapter-4-1---Comparative-Life-Cycle-Environmenta_2018_Exergetic--Energetic-.pdf (p.889-910)
4.1 - COMPARATIVE LIFE CYCLE ENVIRONMENTAL IMPACT ASSESSMENT OF NATURAL GAS AND CONVENTIONAL VEHICLES
1. INTRODUCTION
2. BACKGROUND
3. LIFE CYCLE ASSESSMENT: APPROACH AND METHODOLOGY
4. SYSTEM DESCRIPTION AND ANALYSIS
4.1 PASSENGER CARS
4.2 HEAVY-DUTY VEHICLES
4.2.1 Class 8 Trucks
4.2.2 Transit Buses
5. RESULTS AND DISCUSSION
5.1 PASSENGER CARS
5.2 HEAVY-DUTY VEHICLES
5.2.1 Class 8 Trucks
5.2.2 Transit Buses
6. CONCLUSIONS
NOMENCLATURE
ACKNOWLEDGMENTS
REFERENCES
Chapter-4-2---Life-Cycle-Assessment-of-A_2018_Exergetic--Energetic-and-Envir.pdf (p.911-935)
4.2 - LIFE CYCLE ASSESSMENT OF AMMONIA PRODUCTION METHODS
1. INTRODUCTION
2. LIFE CYCLE ASSESSMENT
2.1 GOAL AND SCOPE DEFINITION
2.2 LIFE CYCLE INVENTORY ANALYSIS
2.3 LIFE CYCLE IMPACT ASSESSMENT
2.4 INTERPRETATION OF RESULTS AND IMPROVEMENT
2.5 ASSESSMENT METHODS
2.5.1 CML 2001 Method
2.5.1.1 Depletion of Abiotic Resources
2.5.1.2 Human Toxicity
2.5.1.3 Fresh Water Aquatic Eco-toxicity
2.5.1.4 Acidification Potential
2.5.1.5 Global Warming
2.5.1.6 Eutrophication
2.5.2 Eco-indicator 99 Method
2.5.2.1 Human Health
2.5.2.2 Ecosystem Quality
2.5.2.3 Resources
3. PRODUCTION METHODS
3.1 AMMONIA PRODUCTION
3.2 HYDROGEN PRODUCTION
3.3 NITROGEN PRODUCTION
4. LIFE CYCLE ASSESSMENT: METHODOLOGY
4.1 ASSUMPTIONS AND KEY INPUTS
4.2 ROUTES OF AMMONIA PRODUCTION SELECTED FOR THE STUDY
4.3 CASE STUDIES
5. RESULTS AND DISCUSSION
6. CONCLUSIONS
REFERENCES
Chapter-4-3---Mass-Transfer-Effects-in-SCR-Re_2018_Exergetic--Energetic-and-.pdf (p.936-954)
4.3 - MASS TRANSFER EFFECTS IN SCR REACTOR FOR NOX ABATEMENT IN DIESEL ENGINES
1. INTRODUCTION
2. EXPERIMENTAL
2.1 MONOLITH REACTOR EXPERIMENTS
3. MATHEMATICAL MODEL
3.1 EXTERNAL (INTERPHASE) MASS TRANSFER
3.2 INTERNAL MASS TRANSFER
3.3 DETERMINATION OF APPARENT AND INTRINSIC REACTION RATE CONSTANTS
3.4 MASS TRANSFER CORRELATIONS FOR MONOLITH REACTORS
4. RESULTS AND DISCUSSION
4.1 STANDARD SELECTIVE CATALYTIC REDUCTION EXPERIMENTS
4.2 EVALUATION OF MASS TRANSPORT AND SURFACE REACTION RESISTANCES
4.3 EXTERNAL MASS TRANSFER COEFFICIENTS FROM THE LITERATURE
5. CONCLUSIONS
NOMENCLATURE
ACKNOWLEDGMENTS
REFERENCES
Chapter-4-4---An-Experimental-Study-on-the-Effects-of-_2018_Exergetic--Energ.pdf (p.955-970)
4.4 - AN EXPERIMENTAL STUDY ON THE EFFECTS OF INLET WATER INJECTION OF DIESEL ENGINE HEAT RELEASE RATE, FUEL CONSUM ...
1. INTRODUCTION
2. DESCRIPTION OF EXPERIMENTAL SYSTEM
2.1 EXPERIMENTAL APPARATUS
2.2 EXPERIMENTAL PROCEDURE
3. EVALUATION OF EXPERIMENTAL MEASUREMENTS
3.1 ENGINE PERFORMANCE CHARACTERISTICS AND HRR CALCULATIONS
3.2 ERROR ANALYSIS AND UNCERTAINTIES
4. RESULTS AND DISCUSSIONS
4.1 THE EFFECTS OF WATER ADDITION ON HRR, TEMPERATURE, PRESSURE, AND BRAKE-SPECIFIC FUEL CONSUMPTION
4.2 THE EFFECTS OF WATER ADDITION ON NOX EMISSIONS AND OPACITY
5. CONCLUSIONS
NOMENCLATURE
ACKNOWLEDGMENTS
REFERENCES
Chapter-4-5---Carbon-Captu_2018_Exergetic--Energetic-and-Environmental-Dimen.pdf (p.971-990)
4.5 - CARBON CAPTURE
1. INTRODUCTION
2. CARBON CAPTURE TECHNOLOGIES
2.1 PRECOMBUSTION CO2 CAPTURE
2.2 OXY-COMBUSTION CO2 CAPTURE
2.3 POSTCOMBUSTION CO2 CAPTURE
3. COMPARISONS AMONG CARBON CAPTURE TECHNOLOGIES
3.1 COMPARISON OF TECHNOLOGIES IN TERMS OF MATURITY
3.2 COMPARISON OF ADVANTAGES OF THE TECHNOLOGIES
3.3 COMPARISON OF DISADVANTAGES OF THE TECHNOLOGIES
3.4 COMPARISON OF TECHNOLOGIES IN TERMS OF ECONOMY
4. CARBON CAPTURE FOR INDUSTRIAL APPLICATIONS
4.1 CEMENT AND CLINKER PRODUCTION
4.2 IRON AND STEEL INDUSTRY
4.3 WATER DESALINATION PROCESSES
4.4 OIL REFINERY
4.5 GAS-TO-LIQUID PROCESS
4.6 ETHYLENE OXIDE PRODUCTION
5. SUMMARY AND CONCLUSIONS
NOMENCLATURE
ACKNOWLEDGMENTS
REFERENCES
Chapter-4-6---Vacuum-Stripping-Membrane-De_2018_Exergetic--Energetic-and-Env.pdf (p.991-1001)
4.6 - VACUUM STRIPPING MEMBRANE DESALINATION FOR MARMARA SEAWATER
1. INTRODUCTION
2. EXPERIMENTAL APPARATUS AND PROCEDURE
2.1 MEMBRANE PREPARATION PROCEDURE
2.2 MEMBRANE CHARACTERIZATION PROCEDURE
2.3 SWELLING PROCEDURE
2.4 PERVAPORATION APPARATUS
3. RESULTS AND DISCUSSION
3.1 MEMBRANE CHARACTERIZATION RESULTS
3.2 SWELLING RESULTS
3.3 EFFECT OF TEMPERATURE ON SEPARATION PERFORMANCE
3.4 EFFECT OF SALT CONCENTRATION ON SEPARATION PERFORMANCE
4. CONCLUSIONS
ABBREVIATIONS
ACKNOWLEDGMENTS
REFERENCES
Chapter-4-7---Removal-of-Ions-Pb2--and-Cd2--Fr_2018_Exergetic--Energetic-and.pdf (p.1002-1016)
4.7 - REMOVAL OF IONS PB2+ AND CD2+ FROM AQUEOUS SOLUTION BY CONTAINMENT GEOMATERIALS
1. INTRODUCTION
2. EXPERIMENTAL APPARATUS AND PROCEDURE AND CHARACTERIZATION
2.1 ADSORPTION EXPERIMENT AND MODELING
2.2 TEMPERATURE EFFECT AND THERMODYNAMIC PROCESS
3. RESULTS AND DISCUSSION
3.1 ADSORPTION KINETICS OF PB2+ ON GM1, GM2, AND GM3
3.2 ADSORPTION KINETICS OF CD2+ ON GM1
3.3 ADSORPTION ISOTHERM OF PB2+ AND CD2+ ON GM1
3.4 EQUILIBRIUM ADSORPTION MODELING
3.5 TEMPERATURE EFFECT AND THERMODYNAMIC STUDY
3.6 PH EFFECT ON ADSORPTION ISOTHERMS
4. CONCLUSIONS
NOMENCLATURE
REFERENCES
Chapter-4-8---Investigation-of-Irreversibility-W_2018_Exergetic--Energetic-a.pdf (p.1017-1031)
4.8 - INVESTIGATION OF IRREVERSIBILITY WITH CO2 EMISSION MEASUREMENT IN INDUSTRIAL ENAMEL FURNACE
1. INTRODUCTION
2. INDUSTRIAL FURNACES
3. THERMODYNAMIC MODELING
4. RESULTS AND DISCUSSION
4.1 ENERGY ANALYSIS
4.2 EXERGY ANALYSIS
4.3 IMPLEMENTATION PROJECTS
4.4 ENERGY ANALYSIS AFTER EFFICIENCY IMPLEMENTATION PROJECTS
4.5 EXERGY ANALYSES AFTER EFFICIENCY IMPLEMENTATION PROJECTS
4.6 MEASUREMENT OF CO2 EMISSIONS
5. CONCLUSIONS
NOMENCLATURE
REFERENCES
FURTHER READING
Chapter-4-9---Environmental-Flow-Assessm_2018_Exergetic--Energetic-and-Envir.pdf (p.1032-1045)
4.9 - ENVIRONMENTAL FLOW ASSESSMENT METHODS: A CASE STUDY
1. INTRODUCTION
2. REVIEW OF ENVIRONMENTAL FLOW ASSESSMENT METHODS
2.1 CLASSIFICATION OF ENVIRONMENTAL FLOW METHODS
2.1.1 Hydrological Methods
2.1.2 Hydraulic Rating Methods
2.1.3 Habitat Simulation Methods
2.1.4 Holistic Methods
2.2 ENVIRONMENTAL FLOW CONCEPT IN THE WORLD
3. ASSESSMENT OF KANDIL HYDROELECTRIC POWER PLANT BASED ON SELECTED METHODS
3.1 TENNANT METHOD
3.2 FLOW DURATION CURVE METHOD
3.3 ABOUT THE HYDROPOWER PLANT
4. RESULTS AND DISCUSSION
5. CONCLUSIONS
REFERENCES
Index_2018_Exergetic--Energetic-and-Environmental-Dimensions.pdf (p.1046-1082)
Index
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
Q
R
S
T
U
V
W
X
Y
Z

Citation preview

Exergetic, Energetic and Environmental Dimensions

Edited by Ibrahim Dincer C. Ozgur Colpan Onder Kizilkan

Academic Press is an imprint of Elsevier 125 London Wall, London EC2Y 5AS, United Kingdom 525 B Street, Suite 1800, San Diego, CA 92101-4495, United States 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom Copyright © 2018 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library ISBN: 978-0-12-813734-5 For information on all Academic Press publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Katie Hammon Acquisition Editor: Lisa Reading Editorial Project Manager: Lindsay Lawrence Production Project Manager: Mohanapriyan Rajendran Designer: Victoria Pearson Typeset by TNQ Books and Journals

List of Contributors Canan Acar Bahcesehir University, Istanbul, Turkey Bora Acarkan Yildiz Technical University, Istanbul, Turkey Mahmoud Ahmed EgypteJapan University of Science and Technology (E-JUST), Alexandria, Egypt Gu¨lden G. Akkurt Izmir Institute of Technology, Izmir, Turkey Ibrahim E. Alaefour University of Waterloo, Waterloo, ON, Canada Hamed Alimoradiyan Eastern Mediterranean University, Famagusta, Turkey Gu¨venc¸ U. Alpaydın Dokuz Eylul University, _Izmir, Turkey Ersin Alptekin Dokuz Eylul University, _Izmir, Turkey Mehmet Altinkaynak Suleyman Demirel University, Isparta, Turkey Ay¸se F. Altun Uluda g University, Bursa, Turkey Zeynep D. Arsan Izmir Institute of Technology, Izmir, Turkey Elnaz Asadian Tehran University, Tehran, Iran Ali Avci Yildiz Technical University, Istanbul, Turkey Atakan Avcı Uluda g University, Bursa, Turkey Ebubekir S. Aydin Gebze Technical University, Kocaeli, Turkey Mustafa Aydin Dokuz Eylul University, _Izmir, Turkey Katayoun T. Azari Tehran University, Tehran, Iran Mohaled T. Baissi Centre de De´veloppement des Energies Renouvelables, CDER, Ghardaı¨a, Algeria

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xiv

LIST OF CONTRIBUTORS

Mutlucan Bayat Karabuk University Baliklar Kayasi Mevkii, Karabuk, Turkey Seyfettin Bayraktar Yildiz Technical University, Istanbul, Turkey Hanane Ben cheikh el hocine Centre de De´veloppement des Energies Renouvelables, CDER, Ghardaı¨a, Algeria Atilla Bilgin Karadeniz Technical University, Trabzon, Turkey Abdullah Bolek Yildiz Technical University, Istanbul, Turkey Tohid N.G. Borhani Imperial College London, London, United Kingdom Fateme A. Boyaghchi Alzahra University, Tehran, Iran Selmi E. Bozba g Koc¸ University, Istanbul, Turkey Ammar B. Brahim University of Gabes, Gabes, Tunisia Jocelyne Brendle´ Universite´ de Haute Alsace, Mulhouse Cedex, France Ozum Calli Izmir University of Economics, Izmir, Turkey Vahit Corumlu Suleyman Demirel University, Isparta, Turkey Turgay Co¸skun Izmir Institute of Technology, Izmir, Turkey Onur Demir Ford Otosan R&D Center, Istanbul, Turkey Emrah Deniz Karabuk University, Karabuk, Turkey Ibrahim Dincer UOIT, Oshawa, ON, Canada; YTU, Istanbul, Turkey Selim Dincer Bogazici University, Istanbul, Turkey Aydın H. Do¨nmez _ Yıldız Technical University, Istanbul, Turkey Orhan Durgun Avrasya University, Trabzon, Turkey

LIST OF CONTRIBUTORS

Aysegul A. Eker Yildiz Technical University, Istanbul, Turkey Bulent Eker Namik Kemal University, Tekirdag, Turkey Muftah H. El-Naas Qatar University, Doha, Qatar Mohamed Emam EgypteJapan University of Science and Technology (E-JUST), Alexandria, Egypt Turgay Emir Akc¸ansa, Istanbul, Turkey Anil Erdogan Dokuz Eylul University, _Izmir, Turkey Can Erkey Koc¸ University, Istanbul, Turkey Kemal Ermis Sakarya University, Sakarya, Turkey Mehmet A. Ezan Dokuz Eylul University, _Izmir, Turkey Ali Fellah University of Gabes, Gabes, Tunisia Ersan Go¨nu¨l Uluda g University, Bursa, Turkey Okay Go¨nu¨lol Dokuz Eylul University, _Izmir, Turkey Mehmet Gu¨ray Gu¨ler Yildiz Technical University, Istanbul, Turkey O¨zcan Gu¨lhan Izmir Institute of Technology, Izmir, Turkey Mert Gu¨lu¨m Karadeniz Technical University, Trabzon, Turkey Huseyin Gunerhan Ege University, Izmir, Turkey Aynur Hacioglu Kocaeli University, Kocaeli, Turkey Hafsia Haloui Centre de De´veloppement des Energies Renouvelables, CDER, Ghardaı¨a, Algeria

xv

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LIST OF CONTRIBUTORS

Boualem Hamdi Universite´ des Sciences et Technologies Houari Boumediene USTHB, Bab Ezzouar, Alger, Alge´rie Feridun Hamdullahpur University of Waterloo, Waterloo, ON, Canada Mouna Hamed University of Gabes, Gabes, Tunisia Souhila A. Hamoudi Centre de Rechercher scientifique et technique en Analyse Physico Chimique (CRAPC), Bou Ismail, Tipaza, Alge´rie; Universite´ des Sciences et Technologies Houari Boumediene USTHB, Bab Ezzouar, Alger, Alge´rie Parisa Heidarnejad University of Tehran, Tehran, Iran Nilufer D. Hilmioglu Kocaeli University, Kocaeli, Turkey Go¨khan Hisar Ford Otosan R&D Center, Istanbul, Turkey Mehdi Hosseini UOIT, Oshawa, ON, Canada Ahmet Kabul Suleyman Demirel University, Isparta, Turkey Cem Kalkan _ Dokuz Eylul University, Izmir, Turkey Arif Karabu ga Suleyman Demirel University, Isparta, Turkey Hazal G. Karada g Koc¸ University, Istanbul, Turkey Yakup Karakoyun _ Yıldız Technical University, Istanbul, Turkey Nuri Kayansayan Near East University, Mersin, Turkey A. Khelifa Centre de De´veloppement des Energies Renouvelables, CDER, Ghardaı¨a, Algeria Muhsin Kılıc¸ Uluda g University, Bursa, Turkey Gu¨lden Ko¨ktu¨rk _ Dokuz Eylul University, Izmir, Turkey Serhan Ku¨c¸u¨ka _ Dokuz Eylul University, Izmir, Turkey

LIST OF CONTRIBUTORS

Yusuf Kurtgoz Karabuk University, Karabuk, Turkey Xianguo Li University of Waterloo, Waterloo, ON, Canada Motahare Mahmoodnezhad Alzahra University, Tehran, Iran Ali Malek Centre de De´veloppement des Energies Renouvelables, CDER, Ghardaı¨a, Algeria Rogaye Motalebzade Islamic Azad Univesity, Meshgin Shahr, Iran Gu¨ven Nergiz Dokuz Eylul University, _Izmir, Turkey Filiz U. Nigiz Kocaeli University, Kocaeli, Turkey Alireza Noorpoor University of Tehran, Tehran, Iran Rouhollah Norouzi Islamic Azad Univesity, Meshgin Shahr, Iran David Ouellette Dokuz Eylul University, _Izmir, Turkey; University of Toronto, Toronto, ON, Canada Mehmet Ozalp Karabuk University Baliklar Kayasi Mevkii, Karabuk, Turkey Nurgu¨l O¨zbay Bilecik S¸eyh Edebali University, Bilecik, Turkey Ahmet Ozbilen UOIT, Oshawa, ON, Canada Esra O¨zdemir Uluda g University, Bursa, Turkey Adnan Ozden University of Waterloo, Waterloo, ON, Canada Barkın Ozener Ford Otosan R&D Center, Istanbul, Turkey Muhammet O¨zer Dokuz Eylul University, _Izmir, Turkey C. Ozgur Colpan Dokuz Eylul University, _Izmir, Turkey Ahmet Ozsoy Suleyman Demirel University, Isparta, Turkey

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LIST OF CONTRIBUTORS

Hakan F. O¨ztop Firat University, Elazı g, Turkey Murat Ozturk Suleyman Demirel University, Isparta, Turkey Eylem Pehlivan Bilecik S¸eyh Edebali University, Bilecik, Turkey M. Furkan Polat Bogazici University, Istanbul, Turkey Ali Radwan EgypteJapan University of Science and Technology (E-JUST), Alexandria, Egypt Tahir A.H. Ratlamwala Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Karachi, Pakistan Marc A. Rosen UOIT, Oshawa, ON, Canada Hasan Sadikoglu _ Gebze Technical University, Kocaeli, Turkey; Yildiz Technical University, Istanbul, Turkey Zehra S¸ahin Karadeniz Technical University, Trabzon, Turkey Cem D. S¸ahin Izmir Institute of Technology, Izmir, Turkey Deniz S¸anli Ford Otosan R&D Center, Istanbul, Turkey Elif K. Sari Okan University, Istanbul, Turkey Re¸sat Selba¸s Suleyman Demirel University, Isparta, Turkey Fatih Selimefendigil Celal Bayar University, Manisa, Turkey Ahmet Senpinar Firat University, Elazig, Turkey Eren Sevinchan UOIT, Oshawa, ON, Canada Samaneh Shahgaldi University of Waterloo, Waterloo, ON, Canada Osamah Siddiqui UOIT, Oshawa, ON, Canada Vishavdeep Singh UOIT, Oshawa, ON, Canada

LIST OF CONTRIBUTORS

u¨t Mehmet Z. So¨g Piri Reis University, Istanbul, Turkey Ismail Tabet Centre de De´veloppement des Energies Renouvelables, CDER, Ghardaı¨a, Algeria Ayc¸a Tokuc¸ Dokuz Eylul University, _Izmir, Turkey Murat Top Dokuz Eylul University, _Izmir, Turkey Khaled Touafek Centre de De´veloppement des Energies Renouvelables, CDER, Ghardaı¨a, Algeria Mustafa Tuti Karadeniz Technical University, Trabzon, Turkey Isılay Ulusoy Okan University, Istanbul, Turkey Anıl U¨nal Dokuz Eylul University, _Izmir, Turkey Derya Unlu Kocaeli University, Kocaeli, Turkey Ali Vakili Ardebili Tehran University, Tehran, Iran Sedat Vatandas Enervis, Bursa, Turkey Melik Z. Yakut Suleyman Demirel University, Isparta, Turkey Ali K. Yakut Suleyman Demirel University, Isparta, Turkey Elif Yaman Bilecik S¸eyh Edebali University, Bilecik, Turkey Rahmiye Z. Yarbay S¸ahin Bilecik S¸eyh Edebali University, Bilecik, Turkey Adife S¸. Yargıc¸ Bilecik S¸eyh Edebali University, Bilecik, Turkey Fazıl Erinc¸ Yavuz Dokuz Eylul University, _Izmir, Turkey Kenan Yi git Yildiz Technical University, Istanbul, Turkey Fatih Yilmaz Vocational Schools of Technical Sciences Aksaray University, Aksaray, Turkey

xix

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LIST OF CONTRIBUTORS

Ozgun Yucel Gebze Technical University, Kocaeli, Turkey Yunus E. Yuksel Afyon Kocatepe University, Afyon, Turkey Ceren Yuksel _ Dokuz Eylul University, Izmir, Turkey Zehra Yumurtacı _ Yıldız Technical University, Istanbul, Turkey Zhien Zhang Chongqing University of Technology, Chongqing, China; Chongqing University, Chongqing, China

Preface We are in an era of humanity facing critical global challenges, ranging from energy and water to environmental impacts. This requires the development of sustainable solutions to overcome energy-related global problems, such as rapid increases in global energy usage, increased depletion of fossil fuels, and worsened environmental problems, such as air and water pollution, which are considered as issues related to global warming. These solutions are expected to be socially desirable, economically feasible, energetically and exergetically efficient, and environmentally friendly. It is a well-known fact that using conventional energy technologies with fossil fuels will not be sufficient for this purpose. In addition to improving the performance and reducing the cost and environmental impact of conventional technologies, utilization of renewable energy resources and usage of alternative energy technologies must be encouraged and implemented. Many countries have already made strategic plans to complete their transition to these resources and technologies. Researchers from all over the world work hard to overcome the technical barriers associated with these new technologies and to bring them into the commercialization stage for wide usage. For this purpose, it is clear that researchers from different disciplines must be brought together to consider different aspects of the research topics. In this regard, new material synthesis and development, experimental testing and characterization, and theoretical analyses and modeling are critical stages needed to carry out successful research. Among the different theoretical analyses, exergy analysis has gained significant attention, especially for improving the performance of integrated energy systems as this analysis can help in identifying the locations of inefficiencies in a system and calculating the magnitude of the irreversibilities. Recently, the usage of exergy analysis has been extended to include the cost and environmental dimensions through methods such as exergoeconomics and exergoenvironmental analyses. This book consists of four key sections on energy and sustainability, energy systems and analyses, alternative fuels and materials, and environmental impact and assessment, which are based on numerous invited papers and invited conference papers that were selected from the Eighth International Exergy, Energy, and Environment Symposium (IEEES-8), which was held in Antalya, Turkey, May 1e4, 2016, and the Second International Conference on Energy Systems (ICES-2016), which was held in Istanbul, Turkey, December 21e23, 2016. These papers are put together under the title of “Exergetic, Energetic, and Environmental Dimensions.” This topic is of prime significance since there is a strong need for practical solutions through better design, analysis, and assessment in order to achieve better efficiency, environment, and sustainability. This book covers a number of topics, ranging from thermodynamic analysis and optimization of energy systems to environmental impact assessment to offer readers broad content on analysis, modeling, development, experimental investigation, improvement, management, etc. of many micro to macro systems and applications, ranging from basic to advanced categories. Detailed information on thermal energy conversion and storage technologies such as parabolic trough solar collectors and organic Rankine cycles, phase change materials, and electrochemical energy conversion technologies such as fuel cells and photovoltaic cells can also be found in this book.

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PREFACE

The editors of this unique edited book would like to warmly thank the editorial team of Elsevier, all contributing authors, reviewers, and organizing committee members of IEEES-8 and ICES-2016 for their efforts that have made this book a success. Furthermore, the editors hope that this book will be useful for readers in increasing their awareness and knowledge on the exergetic, energetic, and environmental dimensions. Dr. Ibrahim Dincer Dr. C. Ozgur Colpan Dr. Onder Kizilkan

CHAPTER

POTENTIAL ENERGY SOLUTIONS FOR BETTER SUSTAINABILITY

1.1 Ibrahim Dincer1, 2, Canan Acar3

1

2

UOIT, Oshawa, ON, Canada ; YTU, Istanbul, Turkey ; Bahcesehir University, Istanbul, Turkey3

1. INTRODUCTION With increasing population and rising standards of living, global energy demand is rising significantly [1]. Currently, most demand is met by fossil fuel supplies, which are geographically restricted. As these sources have limited supplies, they are not expected to keep up with the increasing demand for a long time. At the same time, rising fossil energy consumption results in high levels of air pollution in rapidly growing megacities and contributes to global warming, with potentially large economic and environmental costs [2,3]. Making the most of energy sources is extremely important as energy has been an important part of our daily lives, especially since the Industrial Revolution. And due to increasing issues related to fossil fuel utilization, it is essential to develop reliable, affordable, and clean energy systems. There are various alternative energy resources, for example, geothermal, hydropower, solar, and wind, that are referred to as renewables since their reserves are restored more rapidly compared to their consumption rate [4]. Finding different resources is one way to address the increasing global energy demand. However, these resources should be handled more efficiently in order to get more outputs from the same amount of energy consumption. In the long term, scientific and technical developments might allow substitution of traditional fuels with new fuels and clean energy systems. For this to happen, the new resource or alternative energy system must perform at least as efficiently as the traditional ones. It is also expected for alternative and clean energy systems to have fewer negative environmental effects, for example, greenhouse gas (GHG) emissions and health-and-safety risks [5]. Past energy transitions show a trend toward cheaper, cleaner, more abundant, and more reliable new fuels, as well as the replacement of old energy-conversion technologies with new ones. For more than 200 years, societies have switched from wood, dung, and charcoal to diversified modern systems consisting of fossil fuels like coal, oil, and natural gas and low-carbon technologies like hydroelectricity, nuclear, and renewables [6]. This is a long-term trend toward less pollution and fewer carbon emissions. However, replacing one energy source with another type might require developing a new technology and changing the energy structure entirely or partially. This might also involve changing the Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00001-9 Copyright © 2018 Elsevier Inc. All rights reserved.

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CHAPTER 1.1 POTENTIAL ENERGY SOLUTIONS FOR BETTER SUSTAINABILITY

production, processing, and allocation of energy sources. Main energy sources (e.g., coal, natural gas, and uranium) are extracted, treated, and transported over complex structures that require significant infrastructure investments. Energy facilities usually function for 30e50 years, so they cannot alter energy sources or processing technologies instantly. Replacing the currently functioning traditional fuel-based plants with alternative energy sources is generally very costly [7]. This study first discusses the traditional and alternative energy sources currently available or under study. First, conventional energy sources such as coal, oil, natural gas, and nuclear are evaluated in terms of related challenges accompanied by some potential solutions. Next, alternatives such as renewables, hydrogen, ammonia, system integration, and multigeneration are discussed. The feasibility of traditional and alternative energy systems depends mainly on exploiting novel technologies that exploit them more resourcefully while minimizing their detrimental environmental impacts, particularly their contribution to air, land, and water pollution.

2. CRITICAL CHALLENGES The limited nature and environmental issues of traditional fossil fuels can be addressed by alternative and clean energy systems. These energy systems have a wide range from renewable energies to multigeneration. However, there are some critical challenges regarding alternative and clean energy production, which can be summarized as: 1. Energy return on investment (EROI): is the ratio of the net energy available to be used as an end product compared to the energy input to the production process, i.e., the “profit” from energy production. Most alternatives have low EROIs compared to oil. 2. Scalability and timing: For the promise of an alternative to be achieved, it must be supplied in the time frame needed, in the volume needed, at a reasonable cost. Most alternatives fail to meet either scalability or timing or both. 3. Substitutability: It is very challenging to design and deliver an alternative energy system that could be a direct substitute to our current fossil fuelebased one. Most alternative energy systems require infrastructure changes. For example, electric vehicles require (1) retooling of factories to produce the vehicles, (2) development of a large-scale battery industry, (3) development of recharging facilities, (4) smart grid solutions and deployment, (5) design and production of instruments for the maintenance and repair of vehicles, and (6) spare parts industry. Another example is ethanol. Ethanol cannot be transported in existing pipeline infrastructures and it requires more energy-intensive truck and train transport. 4. Commercialization: Most promising alternative energy systems are in small R&D scales and not commercialized yet. The average time between laboratory benchtop demonstration and full-scale commercialization is 20 years. Mitigation efforts require long lead times. 5. Input requirements: The inputs to alternative energy development are generally material resources, not money. Some of the alternative energy systems have supply constraints on inputs. For instance, a key input to thin-film solar is indium, and its known world reserves would last 13 years at current consumption rates. 6. Intermittency: Global energy demand is constant, thus, the alternative energy systems must be able to meet this demand continuously. The intermittent nature of renewable energies requires efficient and clean energy storage systems.

2. CRITICAL CHALLENGES

5

7. Land and water: The alternative energy system should have minimum negative impact on the environment, preferably with low land and water requirements. Detailed discussion on critical challenges regarding the extraction, conversion, and utilization of various energy sources is provided next. Coal: A range of technologies are available to utilize coal in a cleaner way, such as filtration (to control particulate emissions) and scrubbing (to lower harmful sulfur and nitrogen emissions). There are also various ways to remove mercury. Furthermore, coal can be converted to syngas in order to be burned with lower emissions. Most of these technologies are well established, and some are in already used in existing facilities. Various CO2 capture and storage systems are under significant research and development, however, these systems have been demonstrated to be expensive. Oil and Natural Gas: Mining processes of these energy sources have possible negative influences on the environment including (but not limited to) water, land, and air pollution. Offshore mining can cause spills and leaks that pollute the water. Transferring oil and gas from mines to consumers also causes some risks. For instance, global oil shipment is done by using pipelines and tankers, which have spillage risks. Oil and gas emit lower levels of CO2, SO2, NOx, and mercury compared to coal, however, they still significantly contribute to these emissions. Nuclear Energy: Major obstacles to the expansion of nuclear power worldwide include concerns about safety and high capital costs compared to other energy sources. Nuclear accidents at the Three Mile Island plant in Harrisburg, Pennsylvania, in 1979 and the Chernobyl reactor in Ukraine in 1986 convinced many people that nuclear power is not safe. Chernobyl caused more than 30 deaths in the days immediately following the accident (from acute radiation exposure), and widespread exposure to radioactivity from the accident over a large part of the northern hemisphere may ultimately lead to tens of thousands of deaths from cancer over a period of decades. Although both accidents were largely the result of human errors, and modern facilities have much more substantial safety procedures, these events demonstrated that nuclear accidents are possible. Along with these environmental impacts, nuclear power also causes safety concerns since highly enriched uranium can be used to make nuclear weapons. Biomass: Biomass is generally considered as a cleaner and “greener” energy source. However, combustion in some traditional systems is not effective; it produces great amounts of contaminants, e.g., SO2, NOx, and CO, which are particularly damaging in inefficiently ventilated buildings. Interior air contamination is a severe hazard and leads to numerous respirational disorders, especially in countries relying greatly on biomass combustion for heating, cooking, etc. When biomass is used in primitive systems inefficiently, most of their energy content is wasted. Ethanol and biodiesel are feasible renewables that can cut our need for fossil fuels and lower emissions. But, growing these crops (particularly corn for ethanol) needs significant amounts of fossil fuel input for fertilizer production, farming operations, and transportation. Therefore, biomass does not always provide substantial net energy savings over fossil fuels. Growing crops also requires significant amounts of clean water intake as well as substantial amounts of nutrients from soil. Furthermore, relying too much on biomass could divert crops from food to energy production. Hydropower: Hydropower is perhaps the most developed and widely used renewable energy source. Over many years, hydropower is considered as environmentally benign since it reduces

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CHAPTER 1.1 POTENTIAL ENERGY SOLUTIONS FOR BETTER SUSTAINABILITY

fossil fuel usage in many places. However, as alternative and cleaner energy sources are being developed, some of the disadvantages of hydropower systems are highlighted. Some of these are: (1) killing plants and displacing animals, including endangered species, when reservoirs are flooded; (2) altering river flow rates, the quantity and character of sediments moving through the channel, and materials that make up streambeds and riverbanks; (3) modifying water parameters such as temperature and levels of nutrients and dissolved O2; (4) degrading downstream channels, floodplains, and deltas by reducing the transport of nutrients and sediments below dams; and (5) blocking migration of fish and other aquatic species upstream and downstream. While hydropower does not generate GHG emissions as water spins electric turbines, reservoirs emit CO2 and/or methane from rotting submerged vegetation and carbon inflows from the catchment area. In general, smaller hydropower facilities in tropical regions have higher emissions compared to larger facilities in colder regions. Along with these challenges, global hydropower reserves could be extended at most by a factor of two or three since the remaining resources are in restricted locations. For example, in the United States, it is projected that almost 60% or more of the hydropower reserves are already in use, and the majority of the lasting reserves could potentially harm the surrounding ecosystems significantly. Ocean Energy: The biggest and most experimental type is electricity production by using the ocean’s thermal energy where the warm water near the ocean surface goes through several steps to use the stored heat to power a turbine, then the steam or vapor output is cooled with cold deep water. Ocean thermal energy is not very affordable and is technologically challenging in larger scales because of the physical challenges related to operations in the ocean environment. It can provide most efficient solutions in areas with significant temperature differences between surface and deeper waters, mostly in the tropical regions. However, if (and when) commercialized, ocean thermal energy could turn into a vast new energy source. Geothermal Energy: It is considered to be a renewable energy source since the heat from the earth’s interior is considered to be essentially unlimited. Where there are sufficient resources, it is possible to generate power in a clean, reliable, and affordable manner with geothermal energy. However, it is challenging to use this method in high-electricity-demanding areas since it does not deliver adequately high subsurface temperatures. Therefore, currently, geothermal is mostly a small part of the energy infrastructure. With advanced technologies, it might become feasible in regions with great geothermal resources to harness the surplus supply to generate various portable energy carriers, e.g., H2 production. Wind Energy: Turbines produce electricity without emitting pollutants during operation. However, wind turbines raise some environmental concerns especially when selecting suitable wind farm spots. Wind turbines might harm the natural habitat in ridgelines and coastal areas. Turbine blades could also kill large numbers of birds and bats. For instance, wind turbines in Altamont Pass (California) had substantial impact on these animals. Then scientific and technological advancements addressed these issues. Now, environmental matters are generally identified and addressed with cautious placement according to comprehensive environmental assessments. Substituting a somewhat substantial portion of traditional carbon-based fuel use with wind energy involves extensive turbine placement; thus addressing the issues mentioned here is crucial when designing extensive wind-based energy infrastructure.

3. POTENTIAL SOLUTIONS

7

Solar Energy: Concentrating use of solar energy is most suitable in areas with strong irradiation and clear skies. Photovoltaic (PV) and water heating systems can be utilized in different weather types and locations. PV is employed extensively in small electronic consumer items like handheld calculators. On the other hand, these devices have a maximum PV efficiency of about 15%. Therefore, enormous supplies of PVs are needed in order to support the electricity production to keep up with the increasing global energy demand. For instance, more than 25 km2 of typical PV panels are required to produce the equivalent quantity of electricity that is generated by a traditional large coal-based power plant.

3. POTENTIAL SOLUTIONS Increasing concerns related to the environmental impacts of energy production and use as well as the limited nature of traditional fuels have made it increasingly obvious that “more of the same” is not a satisfactory solution to address the critical challenges related to our increasing energy consumption. A lot of the global traditional fuel reserves are being entirely used, and source exhaustion is increasing the cost of the remaining supplies. Several specialists argue that global oil industry will max out in the near future, while others oppose this notion and claim that technological advancements will keep making fresh reserves available. We can increase our energy supply with alternative resources and technologies with reduced negative environmental impacts. However, these options usually are not entirely commercialized and are more expensive than the conventional methods. Clean energy systems can solve these energy challenges in a clean, reliable, and affordable way. Clean energy offers potential solutions for sustainability to tackle critical challenges mentioned thus far. Clean energy systems enhance (1) system efficiencies, (2) resource utilization, (3) affordability, (4) environmental protection, (5) energy security, and (6) system design and performance analysis. Clean energy systems provide potential solutions through a Source-System-Service approach that requires specific tasks to be accomplished to build an entirely and truly clean infrastructure, as shown in Fig. 1. First, it is essential to pick a clean source of energy. There are certainly some principles to bear in mind, for example, abundance, local obtainability, affordability, dependability, safety, environmental impacts, etc. The majority of the promising alternatives seem to be renewables. Next, it

Source ● ●

System ●

clean

●

abundant

●

●

cheap

●

available

●

etc.

●

●

efficiency increase system integration multigeneration waste/loss recovery etc.

FIGURE 1 Source-System-Service route to sustainability [4].

Service ●

dependable

●

efficient

●

practical

●

clean

●

etc.

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CHAPTER 1.1 POTENTIAL ENERGY SOLUTIONS FOR BETTER SUSTAINABILITY

is essential to examine system losses and efficiencies on top of selecting a clean energy source. Generally, a system can be investigated via the following essential steps: • • • •

Process upgrading for minimum depletion and maximum amount of useful outputs. Efficiency rise by finding and adjusting sources of losses. System integration for extra reliable operation with improved and enhanced outputs. Multigeneration to increase the number of useful products by using the same energy input.

Service means the application stage, and similarly, it is necessary to reduce losses, irreversibilities, wastes, etc. in this stage to make the most out of the desired goods and services. When there is scarcity of resources, we need to get more from a limited amount of input. In recent decades, most countries have significantly improved system efficiencies. There are countless fields in which we can keep on and speed up these trends via even more efficient consumption of all energy and material resources. R&D investments toward more effective energy systems improvements frequently pay for themselves and even result in savings. It is often cheaper, faster, and cleaner to reap gains from end-use efficiency (sometimes referred to as “megawatts,” to connote energy that does not have to be produced) than to expand energy supply through exploration and drilling. Similarly, by investing in recycling programs, better product design, and longer product lifetimes, we can reduce our need for newly produced energy. In the literature, there is a significant amount of work on scientific research, technological development, and employment of clean energy systems. Fig. 2 shows potential clean energy systems and their advantages compared to conventional fossil fuel power generation systems. Green chemistry provides sustainability from the point of reserves and environmental impact. Green chemistry identifies and minimizes any potential threats to health and environment at the fundamental point, which is related to intrinsic properties of any molecule. For that reason, green chemistry (or sustainable chemistry), has a goal to address challenges for a more sustainable world from the perspectives of population increase, food and clean water supply, rapid exhaustion of energy and material reserves, global warming, and water contamination (from toxic wastes and dispersion). Green chemistry is nowadays an essential driving force of the sustainable future development [8]. Critical energy challenges could potentially be addressed by green chemistry. Because of the rapid depletion of fossil fuel reserves and the GHG emissions associated with fossil fuelebased energy systems, it has turned out to be essential to find novel, alternative, abundant, affordable, reliable, and sustainable energy sources and carriers. From this perspective, H2 is a promising energy carrier. H2 is considered as a sustainable energy carrier for numerous reasons. First, it is possible to produce H2 from renewable energy and material resources such as solar, wind, water, and geothermal. Furthermore, if produced from renewables and used in a clean system such as a fuel cell, H2 energy can be utilized without GHG emissions. Solar irradiation is a promising input to produce H2 via H2O splitting and has been attracting a great deal of interest in the literature. Thermodynamics states that the required Gibbs free energy has to be supplied to the H2O molecule in order to dissociate it to produce H2. This can be done by the following: (1) exploiting photons directly to run the dissociation reaction, (2) converting photons to thermal energy and transferring to H2O to release H2, (3) PV-based electrolysis, or (4) hybrid methods. Numerous methods to produce H2 from H2O via solar energy have been summarized by Dincer and Zamfirescu [8]. Development of an efficient, reliable, and affordable technology to support direct photon-to-H2 production is challenging since the process is highly irreversible.

4. HYDROGEN ENERGY

Conventional Energy System

Sustainable Energy System (SES) 1

Heavily fossil fuels

Losses

Process

Renewables

Useful Output

Process

Losses

Useful Output

Emissions

Less emissions

Sustainable Energy System (SES) 2

Sustainable Energy System (SES) 3

Renewables

Renewables Output 1

Output 1 Less Losses

Output 2 Process

9

Multigeneration Useful Outputs

Output 2

Less Losses Process

Multigeneration Useful Outputs

Output 3 Output 4

Less emissions

Less Sustainable

Output 3 Recovered losses

Output 4

Recovered emissions Less emissions

More Sustainable

FIGURE 2 Possible sustainable energy system options [4].

The need for cleaner, more reliable, more affordable, and efficient systems is significantly increasing for production, delivery, and usage of energy. Clean energy systems provide a big promise to address this need and the energy demand related concerns. Clean energy systems meet current needs without compromising future generations’ energy supplies. Societal and financial welfare without damaging the environment could be attained by switching to clean energy systems. But there are specific points that should be identified and analyzed carefully before switching to clean energy systems. Thus, in Table 1, a SWOT (strengths, weaknesses, opportunities, and threats) analysis of clean energy systems is provided.

4. HYDROGEN ENERGY Recently, the importance of H2 has been recognized and its use is gaining more importance. The extensive utilization of fossil fuels has accelerated their depletion and also these fuels contribute harmful oxides of carbon, nitrogen, sulfur, etc. that are responsible for global warming [9].

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CHAPTER 1.1 POTENTIAL ENERGY SOLUTIONS FOR BETTER SUSTAINABILITY

Table 1 SWOT (Strengths, Weaknesses, Opportunities, and Threats) Analysis of Clean Energy Systems S

W

O

T

promises · Financial source · Local utilization · Immense sources market · Adaptable · Expansion opportunities · Better design exercises technologies · Smarter · Innovative solutions · Dependability · Government encouragements · Variable end use

enough · Not collaboration of

liberation · Energy and safety of · Introduction new jobs improvement · Market efficiency · Overall · Supply effectiveness · Carbon reduction quality · Air/water/soil enhancement · Climate change for · Need sustainability · Vitality

financial · Global crisis and · Scalability timing · Commercialization · Substitutability · Complexity · Regulatory requirements · Government regulations and

opportunities

· · · · · · · · ·

politicians and entrepreneurships Community awareness Opposition to change Missing knowledge and training High early investment, installation, O&M costs Affordability Low energy density Long payback time Infrastructural changes Lack of institutional and government consensus and policies

policies

price of · Low conventional energy sources and systems

Modified from Dincer I, Acar C. A review on clean energy solutions for better sustainability. International Journal of Energy Research 2015;39(5):585e606.

There are various performance gaps between the current state and targets of H2 economy. These targets are set to attain a commercial H2 economy. There are numerous promising studies in the literature addressing the challenges in the main areas of the H2 economy: production, storage, and utilization. To demonstrate these challenges, Table 2 summarizes some of the goals and compares these goals to estimations of the present state of the art [10]. It should be noted that the existing challenges are even greater than the ones listed heredevery element must meet numerous goals at once. Many technologies do well in a particular field but perform poorly in another. In addition, the goals in each stage (production, storage, utilization) must be addressed concurrently for H2 economy to be feasible. Table 2 is not a complete inventory but a demonstration of some of the key challenges. There are some goals that are not listed here, such as H2 flow rate requirements, the number of fill and empty cycles to be accomplished, etc. Table 2 also shows that the current options are not able to support the storage targets. For instance, the 450 km travel distance requirement without refueling is a major challenge. H2 is a light gas and the challenge is to store an adequate volume of it in a limited space. The consumer requirements state that the storage tank must be filled in 3e5 min and tolerate hundreds of refuelings over a lifetime of 15 years. The simple H2-powered device is the fuel cell invented in 1839 by Sir William Grove. In the 1950s, the US National Aeronautics and Space Administration made a device from this concept to supply energy for space travel. Table 2 shows that there are still substantial challenges to building a feasible H2-powered device. Fuel cells need major improvements in catalysis and membrane development. Affordable and reliable fuel cells should have membranes with high permeability, selective gas separation; high conductivity; and, durability at elevated temperatures and in corrosive environments.

4. HYDROGEN ENERGY

11

Table 2 Benchmarks, Minimum Improvement Factors, and Promising Technologies for a Viable H2 Economy

Production

Benchmarka

Minimum Factor of Improvementb

0.40 USD/L H2

4e10

Key Challenges

· Cost CO capture and · storage · Efficiency · Leaks · Embrittlement · Cost filling and · Fuel release duration · Impurities · Durability · Materials cost 2

Storage

Utilization

a b

km on full · >450 tank · 3e5 min filling 150,000 km · >5 years warranty · cost: · Engine 2000e5000 USD

2e3

10e100

Promising Technologies

· Membranes · Catalysts · Renewables Nanomaterials and novel materials

· Membranes · Catalysts

McDowall [11], Durbin and Malardier-Jugroot [94]. Winter and Nitsch [95]; Herdem et al. [96]; Pudukudy et al. [13].

These challenges require intensive research in synthesis, characterization, and modeling of novel materials such as nanostructures, films, membranes, and cheap and highly conductive components. Strategically, the long-term goal is to produce H2 in an efficient, affordable, reliable, and clean way [11]. For instance, an efficient process uses the input energy and materials resourcefully. Affordability requires H2 not to be more expensive than existing fuels. Also, clean H2 should emit no or little CO2 and toxins in its entire life cycle (must be less than the current options). The primary means of H2 production is extraction from natural gas through a process known as steam reforming. However, steam reforming is operating near theoretical limits and is still several times more expensive than gasoline [12]. In addition, the clean production requirement significantly increases the cost of this process. At present, it is not possible to produce H2 effectively, at an affordable price, and in an environmentally benign way. For instance, the production costs must be lowered by at least a factor of four [13]. A possible short-term solution is coal gasification. This method is reasonably developed and cost competitive when the facilities operate at full capacity [14]. However, there are still some problems to solve. This process produces H2 with pollutants, and the product has to be refined before feeding to fuel cells. Effective purification requires catalysts to withstand the impurities in the coal [15]. Also, catalysts must tolerate high temperatures and be corrosive resistant. This method could emit substantial amounts of GHGs. Thus, it is essential to capture and store pollutant gases [16]. Electrolysis is another way to produce H2 by H2O splitting. This process can operate with a variety of electricity sources such as renewables and nuclear. But the maximum electrolysis efficiency is 75%. At present, electricity production is the primary factor affecting the cost of H2 production, which is about 4e10 times more expensive compared to fossil fuels. In order to address this issue, more efficient catalysts should be used in electrolysis. As clean energy sources become more affordable, the

12

CHAPTER 1.1 POTENTIAL ENERGY SOLUTIONS FOR BETTER SUSTAINABILITY

cost of electrolysis is expected to drop. Thus, continuing research on renewable energies is beneficial to achieve targets of the H2 economy. In addition, scientists are investigating potential processes for hydrogen energy systems. For example, photolysis and photoelectrochemical (PEC) systems do not need costly catalysts. Although these novel systems may not support a cost-competitive H2 economy in the near future, they could possibly help reach the long-term goals. These novel methods have the potential to make a long-term contribution as the scientific and technological developments are considered. It should be noted that the anticipated H2 economy can take advantage of investments on continuing research in a variety of fields. Energy efficiency, renewables, bridge technologies and H2 use in nontransportation sectors are some of the research areas to improve the current know-how on enhancing energy security and reducing GHG emissions. Short-term H2 production is expected to be based on fossil fuel use. The most promising option is natural gas steam reforming when switching to a H2 economy. Since this process still has GHG emissions, efforts are being made to improve the energy efficiency of this process along with carbon capture technologies. Critical challenges related to H2 production are presented in Table 3.

5. RENEWABLE ENERGY Renewables are obtained from natural sources and constantly replaced. Renewables can be directly or indirectly solar (e.g., biomass, hydro, solar, wind, etc.) or nonsolar based (e.g., geothermal, ocean, tidal, etc.). Renewables with potential outputs are listed in Fig. 3. Addressing the issues for the future of energy supplies and the environmental impact of fossil fuels requires energy production by using mostly or entirely renewables [17]. Switching from fossil fuels to renewables would require a drastic change in the social and political state, and it would also modify our daily lives [18].

Table 3 Brief Summary of Critical Challenges in H2 Production Bio-derived Liquids Reforming

Coal and Biomass Gasification

Electrolysis

Thermochemical

PEC

Microorganisms

Capital costs

Capital costs

Capital costs

Capital costs

O2 tolerance

O&M costs

Efficiency

Efficiency

Efficiency

Efficient and durable photocatalysts Innovative integrated devices

Manufacturing design

Feedstock availability, quality, cost Carbon capture and storage

Renewable energy integration Manufacturing design

Effective and durable materials

Feedstock availability, quality, cost

Optimum microorganism functionality

5. RENEWABLE ENERGY

13

Renewable Energy

Solar

Geothermal

Heating/ Cooling

Biomass

Fuel (H2)

Ocean

Fresh Water (Desalination)

Wind

Hydro

Power

FIGURE 3 Types of renewable energy sources along with their associated outputs [4].

The most prominent disadvantage of renewables is their intermittent nature. Renewables should be stored to provide energy with no restrictions. Batteries or accumulators can meet low-energy demands since they have low capacities. But they have significant energy losses, negative environmental impacts, high maintenance costs, short life spans, and a restricted number of chargeedischarge cycles. For larger power demands, internal combustion engines (ICEs) offer supply for extended periods. However, together with renewables, they still use fossil fuels that release GHGs. Renewables could lower fossil fuel use in ICEs by less than 20% [19]. H2 can be used as a renewable energy storage medium. It has extended storage period, large energy capacity, and it could address the irregular and sporadic nature of renewables. H2 from renewables can replace fossil fuels in numerous systems. In fuel cells, it generates electricity and heat with minimal environmental damage [20]. In this section, some of the renewable energy harnessing technologies are briefly explained and their current energy conversion efficiencies are compared (Table 4). It should be noted that energy conversion efficiencies listed in Table 4 are reported by Hobbs and Meier [21] where energy conversion efficiency is defined as: Conversion efficiency ¼

Energy output Energy input

(1)

Direct nonconcentrating solar thermal: Solar radiation is used to heat a medium such as water or air. Water can either be used as domestic hot water or for radiant floor heating. The benefit of this system is that it reduces reliance on fossil fuels or grid electricity for heating purposes. Saltwater pond for solar thermal: Heat that is stored at the bottom of a saltwater pond can be used as an energy supply in an Organic Rankine cycle (ORC) or Sterling engine. In these systems, heat

14

CHAPTER 1.1 POTENTIAL ENERGY SOLUTIONS FOR BETTER SUSTAINABILITY

Table 4 Current Energy Conversion of the Selected Renewable Energy Technologies Renewable Energy

Technology

Solar

Direct nonconcentrating thermal Saltwater pond CSP PV TPV PVT Artificial photosynthesis PEC Turbines Dammed reservoir Run of the river Micro and pico hydro Tidal Wave Thermal

Wind Hydropower

Ocean

Geothermal

Conversion Efficiency (%)a 45e75 10 25e31 3e45 >50 PLoad

PRES>PLoad 100

Power [kW]

80

60

ESS Charging 40

ESS Discharging

20 ESS Charging 0

1

2

3

4

5

ESS Minimum Level 6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Time [hours]

FIGURE 5 Electrical demand, renewable energy system (RES), and energy storage system (ESS) capacities of ship.

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CHAPTER 1.10 THE IMPORTANCE OF SHIPS

Case-1

Power [kW]

(A)

Case-2 for environmental priority of CO

2

150

100

50

0

(B)

Case-2 for economic priority

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

50

Power [kW]

40 30 20 10 0

Time [hours]

FIGURE 6 Use of (A) auxiliary engines and (B) shore-side power on shipboard for different cases.

instead of AEs, according to the both economic and environmental priorities owing to the price of electricity and unit of CO2 emission release on the port side, which is smaller than on the shipside. The electrical energy costs and CO2 emission releases are given in Fig. 7 for the different cases. The results of the algorithm show that Case 2 is more economical and environmental than Case 1. The total cost of electrical energy can be decreased by 77% and CO2 emission can be reduced by 75% by using both AES and the SEM algorithm on the ship. The SSP infrastructure is the most suitable method for integrating the smart grid on ships. The SSP application is available in some ports, but not frequently enough owing to some barriers. There is not enough grid capacity, grid emission factors can be more than the ship’s AEs, and initial investment costs may be high for ship owners and port authorities in many maritime nations. These barriers can be overcome by integrating smart grids in the future. If maritime nations use more RES and ESS systems in their ports or regions, the capacity of the electricity grid will be used more effectively with the ability for advanced sensing technologies. Thus, the level of the grid emission factors will decrease, and the initial investment costs will be indirectly recovered owing to the lower maintenance and operating costs. Therefore, next-generation electric power system applications and projects should be

5. CONCLUSION

Case-1

(A)

Case-2 for economic priority

175

Case-2 for environmental priority of CO 2

Cost [USD]

15 10 5 0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

(B)

CO2 [Ton]

0.08 0.06 0.04 0.02 0

Time [hours]

FIGURE 7 Electrical energy costs (A) and CO2 emission releases (B) for different cases.

taken into account by maritime sector representatives to provide energy efficiency. Financial support should be developed by governments to encourage smart grid applications. The use of AES and their sustainability on shipboard should be more examined. Such approaches could allow researchers to make two-way electrical energy and information flows available from “ship to grid” or “grid to ship” by using energy management systems.

5. CONCLUSION In this study, the role of ships using the smart grid concept is presented. The SEM algorithm is proposed for ships with integrated AES while in ports by using a smart grid infrastructure. The use of the most economic or most environmental energy source on the ships while in port was analyzed using the proposed algorithm. To explain the importance of the algorithm, a case study was performed in MATLAB. The results showed that the SEM algorithm provides economic and environmental benefits for the ships and ports. Fuel consumption, exhaust gas emissions, noise emissions, vibration, and maintenance costs from ships and ports can be reduced by using both AES and SEM systems. The use of both AES and the SEM algorithm on shipboard will help to meet the regulations of IMO.

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CHAPTER 1.10 THE IMPORTANCE OF SHIPS

This study aimed to attract the attention of maritime sector representatives to improve energy efficiency and find innovative solutions for ships.

NOMENCLATURE AES AEs APV AWT Cenergy,fuel Cenergy,SSP CO2 cos d EAEs;CO2 EFAEs;CO2 EFgrid;CO2 EPfuel,kWh EPfuel,ton EPgrid ESS ESSP;CO2 FC IMO ISolar MG NOx nWT PAEs PESS PESS,i PPV PRES PSSP PV PWT RES SEM SFC SOx SSP Vwind WT mPV mWT r

Alternative energy sources Auxiliary engines PV panel area, m2 Rotor swept area, m2 Fuel cost, USD Electrical energy cost from SSP, USD Carbon dioxide Solar angle, degree CO2 emission release from AEs, tons CO2 emission factor from AEs, g/kWh CO2 emission factor from national electricity grid, g/kWh Unit energy price from AEs, USD/kWh Fuel price, USD/ton Unit electricity cost from national electricity grid, USD/kWh Energy storage system Emission release from SSP, tons Fuel consumption, tons International Maritime Organization Solar irradiation, W/m2 Micro grid Nitrogen oxide Number of WT AEs capacities, kW ESS capacity, kW Initial ESS capacity, kW PV capacity, kW RES capacity, kW SSP capacity, kW Photo-voltaic WT capacity, kW Renewable energy system Ship energy management Specific fuel consumption, g/kWh Sulfur oxide Shore-side power Wind speed, m/s Wind turbine PV efficiency, % Rotor efficiency, % Air density, kg/m3

REFERENCES

177

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[18] Dahmane M, Bosche J, El-Hajjaji A, Dafarivar M. Renewable energy management algorithm for stand-alone system. In: Paper presented at the annual meeting for the Society of IEEE International Conference on Renewable Energy Research and Applications (ICRERA), Madrid, October 2013; 2013. p. 621e6. http:// dx.doi.org/10.1109/ICRERA.2013.6749830. [19] Elma O, Selamogullari US. A new home energy management algorithm with voltage control in a smart home environment. Energy 2015;91:720e31. http://dx.doi.org/10.1016/j.energy.2015.08.094. [20] Koohi-Kamalia S, Rahima NA, Mokhlis H. Smart power management algorithm in microgrid consisting of photovoltaic, diesel, and battery storage plants considering variations in sunlight, temperature, and load. Energy Conversion and Management 2014;84:562e82. http://dx.doi.org/10.1016/j.enconman.2014.04.072. [21] Al-Asmar J, Kouta R, Chaccour K, El-Assad J, Laghrouche S, Eid E, Wack M. Power generation and cogeneration management algorithm with renewable energy integration. Energy Procedia 2015;74: 1394e401. http://dx.doi.org/10.1016/j.egypro.2015.07.785. [22] Do-Young P, Jin-Seok O. Smart power management system for leisure-ship. Journal of Navigation and Port Research 2011;35:749e53. http://dx.doi.org/10.5394/KINPR.2011.35.9.749. [23] Xu-Jing T, Wang T, Zhi C, Ye-Mao H. The design of power management system for solar ship. In: Paper presented at the annual meeting for the Society of IEEE International Conference on Transportation Information and Safety (ICTIS), Wuhan, June 2015; 2015. p. 548e53. http://dx.doi.org/10.1109/ ICTIS.2015.7232182. [24] Top 50 world container ports. Website: http://www.worldshipping.org/about-the-industry/global-trade/top50-world-container-ports. [25] Bunker Index. Marine fuel prices in 2016. Website: http://www.bunkerindex.com/. [26] ENTEC. European Commission Directorate General Environment, service contract on ship emissions: assignment, abatement and market-based instruments, task 1-preliminary assignment of ship emissions to European countries, final report. London, UK: ENTEC UK Limited; 2005. [27] Eurostat. European statistical system. Electricity prices by countries in 2016. Website: http://appsso.eurostat. ec.europa.eu/nui/submitViewTableAction.do. [28] Hall WJ. Assessment of CO2 and priority pollutant reduction by installation of shoreside power. Resources, Conservation and Recycling 2010;54:462e7. http://dx.doi.org/10.1016/j.resconrec.2009.10.002. [29] Patel MR. Shipboard propulsion, power electronics, and ocean energy. Taylor & Francis Group: CRC Press; 2012, ISBN 978-1-4398-8850-6. 6000 Broken Sound Parkway NW (Hardback).

CHAPTER

VENTILATION STRATEGIES FOR THE PREVENTIVE CONSERVATION OF MANUSCRIPTS IN THE NECIP _ PA¸SA LIBRARY, IZMIR, TURKEY

1.11

Turgay Co¸skun, Cem D. S¸ahin, O¨zcan Gu¨lhan, Zeynep D. Arsan, Gu¨lden G. Akkurt Izmir Institute of Technology, Izmir, Turkey

1. INTRODUCTION Historic buildings are a significant part of the world’s cultural heritage. Historic library buildings contain manuscripts, the preservation of which is vital for human culture. If a sufficient indoor microclimate is supplied in libraries, they may survive for centuries [1]. Insufficient indoor microclimate conditions in a historic building may cause mechanical, biological, and chemical degradation of cultural property. Therefore, approaches to conservation have been improved to avoid risks of degradation to cultural properties in historic buildings. Two types of approaches to conservation can be implemented: direct and indirect physical interventions. The former means physical reactions on the property, such as stabilization, consolidation, and disinfestations. Indirect intervention, on the other hand, is defined as preventive conservation, and mainly deals with environmental monitoring and control of storage areas, good housekeeping, pest management, and the education of staff [2]. The main objectives of this study were to examine the extant conservation conditions of manuscripts in the historic library and improve them from a “preventive” point of view. In the literature, risks of mechanical, biological, and chemical degradation on paper-based collections were investigated from a preventive approach to conservation [2e4]. Fluctuations in temperature (T) and relative humidity (RH) are the main reasons for mechanical degradation that causes the dimensional alteration, shrinking, and swelling of manuscripts. The growth of mold, classified under biological degradation, may be seen on the surface of manuscripts, stimulated by optimal critical conditions of T, RH, and substrate over a certain time. The main reason behind chemical degradation is the high amount of moisture content in hygroscopic materials, which may result in the deterioration of text and discoloration of papers. These chemical processes slow down at a low RH and T. Thus storage conditions with lower microclimate values expand the lifetime of collections and archives [5,6]. There are several studies in historic buildings evaluating indoor thermo-hygrometric parameters with respect to the risk management of cultural properties. The degradation phenomenon was investigated with long-term monitoring in a historic church and a statistical risk-based evaluation of Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00011-1 Copyright © 2018 Elsevier Inc. All rights reserved.

179

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CHAPTER 1.11 VENTILATION STRATEGIES FOR THE PREVENTIVE CONSERVATION

thermo-hygrometric parameters. The indoor climate was assessed according to European standards EN 15757, PAS 198 and the set points of 20
C and 50% RH [7]. Another study examined a climate risk assessment in museums based on the influence of set points for T and RH on the indoor microclimate by changing the values in the model [5]. Two museums in the United Kingdom were observed over a long period, and their microclimate was analyzed. The results conveyed the significance of ventilation and humidification for the indoor environment of museums to preserve collections [3]. The indoor microclimate must be controlled with respect to defined instructions to avoid mechanical, chemical, and biological degradation. The American Society of Heating, Refrigerating and Air-Conditioning Engineers Handbook (ASHRAE) Chapter 21 guidelines present six control classes to evaluate the degradation potential of paper-based collections in libraries, museums, and archives [8]. It simply states that properties should be stored either at set points (T between 15
C and 25
C and RH at 50%) or at the historic annual average value for permanent collections. The guidelines control indoor climate conditions by avoiding excessive daily T change or seasonal RH rises and drops. Moreover, indoor microclimate requirements define a set of ranges that may differ as a result of recommended seasonal and short time fluctuations. Novel climate control systems are generally adapted to historic buildings to adjust the indoor environment in a preventive conservation manner. Studies conducted in historic libraries in the Mediterranean climate indicated that the free-floating hygrothermal behavior of historic buildings reasonably fulfills required indoor thermal conditions because of the choice of materials and high thermal mass specifications of the envelope, and low airtightness value of the buildings [4,9]. Hence, controlling the indoor microclimate with mechanical systems should be well scrutinized. The integration of active systems needs to be considered to satisfy requirements for preventive conservation [4]. The motivation of this chapter was to achieve a suitable indoor microclimate to preserve manu_ scripts in the Necip Pa¸sa Library, Tire-Izmir, Turkey. There is no heating, ventilation, and air conditioning (HVAC) system in the Main Hall, and doors and windows are used to ventilate the building. A wooden octagonal cage-like structure where manuscripts are separately preserved was located in the middle of the Main Hall. Yet, a new conditioning system was planned for installation in the Main Hall without a detailed analysis of the current behavior of the building and its impact on the manuscripts. Preliminary results of the ongoing study in this library depicted that the indoor microclimate might cause a chemical degradation risk to the manuscripts, although there was no indication about mechanical and biological risks [10,11]. In this study, two control strategies, mechanical and natural ventilation, were proposed to reduce the risk of chemical degradation to manuscripts in the Necip Pa¸sa Library with the help of a building energy performance (BEP) tool, DesignBuilder (Version 4.2.054) [12]. The study also aims to highlight the significance of quantitative research for any proposal that will be developed for the preventive conservation of manuscripts and other cultural properties in historic buildings. It anticipates contributing to the current literature in Turkey, in which the analysis of indoor environment and hygrothermal behavior of libraries, specifically those housing manuscripts, is limited.

2. NECIP PA¸SA LIBRARY The Necip Pa¸sa Library is a 190-year-old, standalone, load-bearing building that functions to house manuscripts dating from the 12th to the 20th centuries in the west of Turkey, Tire-Izmir. It was built by Mehmet Necip Pa¸sa to house his own collection, accumulated during his official service in several

2. NECIP PA¸SA LIBRARY

181

FIGURE 1 _ South view of Necip Pa¸sa Library, Tire-Izmir, Turkey.

places in the Ottoman Empire [13] (Fig. 1). The building housing one of the priceless manuscript collections in Turkey preserves 1156 manuscripts, 1312 books printed in the era of Ottoman Empire, and more than 9000 books in Latin letters, most of which were printed right after the foundation of the Republic of Turkey [13e15]. The library has undergone restoration work since July 2016 under the control and management of the Turkish Prime Ministry, Directorate General of Foundations. The library lies on a south to north axis with three main zones: originally a portico (Revak), newly the Entrance Hall; an almost square planned Main Hall; and an octagonal cage-like Manuscript Zone located inside the Main Hall, respectively (Fig. 2). After the spatial intervention undertaken in 1930, the portico was converted into the Entrance Hall by wooden framed windows to create an office space for the library administrator and a reading hall for visitors. The cube-shaped Main Hall was enclosed by a lead-covered brickwork dome. It has nonhomogeneous highethermal mass walls composed of rubble stone and brick. The thickness of the external walls is 1.08, 1.16, and 1.25 m for the eastern, western, and northern (and southern) walls, respectively. Seven windows on the Main Hall are single glazed with wooden frames and iron shuttered from inside. In addition, four fixed small windows on the drum of dome face the four main directions (Fig. 2). The only approach to the manuscripts is from a thick iron door between the Entrance and Main Halls. The manuscripts are separately preserved in a cage-like structure made of wood-framed glass shutters and fences, built in 1908 [16]. The openable shutters, fences, and a hole on top of the Manuscript Zone probably maintain air circulation. A split-type air-conditioner is placed into the Entrance Hall for cooling and heating purposes, whereas there is no HVAC system in the Main Hall and Manuscript Zone. Therefore, the manuscripts are preserved in a free-floating microclimate [10]. The natural thermal behavior of the building is kept by opening the windows and door through natural ventilation on weekday mornings. The Necip Pa¸sa Library was purposefully elevated over an approximately 2-m-high podium to protect books and manuscripts against humidity from the rich groundwater of Tire. Yet, the authors

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CHAPTER 1.11 VENTILATION STRATEGIES FOR THE PREVENTIVE CONSERVATION

FIGURE 2 Schematic plan of Necip Pa¸sa Library [17].

occasionally observed moisture from the ground surface that caused by condensation resulting from the T difference between the Main and Entrance Halls in winter. An interview with the administrator of the Library confirmed that the Library provided the desired indoor conditions, because most of the manuscripts were well preserved; in only few cases, such as the discoloration and embrittlement of pages, was observed due to misuse [18].

3. DESCRIPTION OF METHOD The main purpose of this study was to decrease the risk of chemical degradation on manuscripts kept in the Necip Pa¸sa Library by using natural and mechanical ventilation systems. Thus, the current condition of manuscripts was investigated via in situ monitoring. The proposed ventilation strategies was then assessed via a calibrated BEP model and simulations. The steps of the study are given in Fig. 3.

3.1 MEASUREMENTS The indoor and outdoor microclimates of the Necip Pa¸sa Library were monitored for 1 year by automatic sensors. Five data loggers, which recorded data with 10-min intervals, were used to measure T and RH from September 1, 2014 to August 31, 2015. Only one was placed outside; the others were placed inside. The locations of the data loggers are indicated in Fig. 2. In addition, a blower door test was carried out to measure the airtightness value of the library, which was found to be 0.52 air change rate (ACH). This indicated that roughly half of the air in the total volume (Main and Entrance Halls) changed over an hour.

3. DESCRIPTION OF METHOD

183

FIGURE 3 Methodology.

3.2 BUILDING ENERGY PERFORMANCE MODELING AND CALIBRATION A BEP tool, DesignBuilder, was used to model the library [12]. The model was divided into three thermal zones: the Main Hall, Manuscript Zone, and Entrance Hall. Real physical features for each space were entered into the program. The overall heat transfer coefficients (U) of external walls made of limestone and brickwork were 1.64, 1.76, and 1.89 W/m2K for the south/north, west, and east walls, respectively. The roof had a dome shape with a U value of 1.51 W/m2K. All windows of the library were modeled as wooden frames with single glazing (U ¼ 5.89 W/m2 K). The top surface material was the only difference between the ground floor sections of the Manuscript Zone (U ¼ 1.24 W/m2 K)

184

CHAPTER 1.11 VENTILATION STRATEGIES FOR THE PREVENTIVE CONSERVATION

and the Main Hall (U ¼ 1.38 W/m2 K). The internal loads including lighting, office equipment, and occupants, and operating schedules were specified based on site observations and interviews. Occupant density and schedule per space were determined. Weather data (based on T and RH) that were integrated into the model were obtained from the 1-year outdoor measurements. Calibration of model was carried out with respect to the comparison of measurements (T and RH) and simulation results according to ASHRAE Guideline 14 [19]. Two dimensionless error indicators, the mean bias error (MBE) and the coefficient of variation of the root mean squared error [CV(RMSE)], were used as criteria for the calibration process and were calculated by Eqs. (1) and (2), respectively [20]: Ni P

MBE ¼

ðMi  Si Þ

i¼1

(1)

Ni P

Mi

i¼1

22 N h i3312 Pi 2 ðMi  Si Þ 77 66 66i¼1 77 66 77 44 55 Ni CVðRMSEÞ ¼

(2)

Ni 1 X Mi Ni i¼1

The upper limit for the CV(RMSE) and MBE values were defined as 30% and 10% for hourly measurements according to ASHRAE Guideline 14. If the calculated values were lower than the upper limits, the model was assumed to be calibrated.

3.3 ASSESSMENT OF CHEMICAL DEGRADATION RISK Mechanical and natural ventilation systems were designed and introduced to the model to determine whether the manuscripts were risk of chemical degradation between the dates when the preliminary results exhibited such a risk [10,11]. The parameter called the lifetime multiplier (LM), which corresponds to the number of time spans an object remains unstable compared with an indoor climate of 20
C and 50% RH, was used to investigate the risk of chemical degradation for the manuscripts [5,7]. LM values below than 0.75 and greater than 1 are an indicator of high and low risk, respectively. Between these values is considered a medium risk level [5]. The equivalent lifetime multiplier (eLM) measures the annual response of objects with a unique value, enabling an evaluation of the annual impact. LMx and eLM values are calculated using Eqs. (3) and (4):    1:3 Ea 1 1  Tx þ273:15 293:15 R 50% LMx ¼ e (3) RHx eLM ¼

1 n X

1  n x¼1 

50% RHx

1:3

1  e

Ea R

1 1  293:15 Tx þ273:15

(4) 

4. RESULTS AND DISCUSSION

185

Table 1 Interpretation of Equivalent Lifetime Multiplier Values

Equivalent lifetime multiplier

Ideal

Good

Some Risk

Potential Risk

High Risk

>2.2

[1.7e2.2]

[1e1.7]

[0.75e1]

1 and l=D > Ral , the regime is a tall-enclosure regime. In this regime, the lateral temperature profile remains linear and NuD  1. Distinct fluid layers can be observed near the top and bottom horizontal boundaries. 1=4 1=4 If Ral > 1 and Ral < Dl < Ral , the regime is a boundary-layer regime. This is a convectiondominated regime. Distinct boundary layers form next to the vertical surfaces. The boundary layers thus constitute the recirculation flow loop whereas the core of the enclosure remains approximately stagnant, and the heat flux is on the order of: 00

qD z kðts  tp Þ=dth

(10)

where dth is the thermal boundary layer thickness (m). 1=4 If Ral > 1 and Dl < Ral , the regime is a shallow-enclosure regime. This regime is also dominated by convection. It is characterized by a counter-flow pattern in the horizontal direction and thermal boundary layers on the vertical sides. The boundary layers, as well as the long horizontal core, contribute to thermal resistance for heat transfer between the two isothermal sides. Empirical correlations result: RaD ¼ GrPr ¼

gbD3 Dt wa

(11)

For RaD  1, the flow field in the enclosure resembles the one described earlier for a tall enclosure. A large, slowly rotating cell is observed, but heat transfer across the enclosure is essentially by conduction, leading to NuD z 1. For the parameter range 2 < l/D < 10, Pr < 10, and RaD < 1010, Catton (1978) proposed [19]: ðNuD Þl ¼ 0:22

 1=4  0:28 l Pr RaD D 0:2 þ Pr

(12)

2. DESCRIPTION OF SYSTEMS

201

For the range 10 < l/D < 40, 1 < Pr < 2  104, and 104 < RaD < 107, McGregor and Emery (1969) recommended [20]: ðNuD Þl ¼

0:012 0:42Ra0:25 D Pr

 0:3 l D

(13)

The same authors recommended the following correlation for the range 1 < l/D < 40, 1 < Pr < 20, and 106 < RaD < 109: ðNuD Þl ¼ 0:046Ra0:33 D

(14)

2.2 VALIDATION Computer simulation was performed with Design Builder software. Using the results of an experiment, it was practically evaluated. To do so, a test room located on the campus of Islamic Azad University, Tabriz Branch, was used. In this experimental sample, a thermometer was installed on the glass to measure the temperature of the southern wall and several thermometers were installed in the room to measure the temperature of the room. For 3 days in the summer and 3 days in winter, the range of the measured temperatures was compared with the graph obtained from Design Builder. The features of the test room are listed in Table 1. There were windows on all walls, and the proportion of the area of the windows to the walls was 25%. Moreover, the features of the window glasses were the same as those of the model building. The practical example given earlier with all of its features was simulated exactly in Design Builder, the results of which are given in Figs. 8 and 9 for three summer days and three winter days. The results of these graphs indicated that the values given by the software were not much different from the measured values and had high accuracy, which confirmed the accuracy of the other results obtained with the software.

2.3 COMPUTER SIMULATION In the current study, Design Builder software was used for simulation and to analyze the results and compare thermal losses in regular and DSF buildings. To do so, a five-story building was selected with the ground floor dimensions of 20 m  19 m; for the other floors, it was 20 m  20 m. The height of each floor was 3.5 m and the total height of the building was 17.5 m. On each floor, 25% of each outer wall of the building was covered with windows of the double clear type. For the sake of simplicity, it was also assumed that no other buildings were around the building and that they had no effect on the thermal performance of it. The results of previous studies showed that if DSF is built in the southern wall of the building, it will have the highest efficiency. Therefore, the southern wall was simulated

Table 1 Features of the Room Wall U Value

Glass Type

Dimension

Row

0.351

Double Clear

10  10  3.5

1

202

CHAPTER 1.12 EFFECT OF DOUBLE-SKIN FAC¸ADE ON THERMAL ENERGY

FIGURE 8 Comparison of result of simulation and measurement for three winter days.

FIGURE 9 Comparison of results of simulation and measurement for three summer days.

twice: once with 25% double-walled windows and the second time with DSF. Fig. 10 shows the simulated building. As shown in Fig. 3, the DSF system in this study was of the interrupt type and was considered with closed natural convection. The inner skin was made of double clear glass and the outer skin was made of single clear glass. The length of the cavity between the two inner and outer skins is an important factor in DSFs; with proper design, energy consumption is reduced. Its improper design can sometimes increase energy consumption. The examination of different depths indicated that the depth of the middle cavity was between 0.7 and 1.2 m; good balance between the rate of air ventilation and heat transfer of the container was observed. It is clear that reducing this length leads to more airflow, greater loss of air in the container, and increased heat transmission. Therefore, in the current study this distance was considered to be 1 m. The specifications of the glass are presented in Table 2.

3. RESULTS AND DISCUSSION

203

FIGURE 10 The fac¸ade of simulated double-skin fac¸ade building.

Table 2 Specifications of Glass U Value (W/ m2 K)

Light Transmission

Direct Solar Transmission

Total Solar Heat Gain Coefficient

Glass Type

Row

2.785

0.781

0.604

0.697

Clear

1

Because the greatest amount of thermal load loss in the buildings in Tabriz happens in winter, the period was October 1 until the end of March.

3. RESULTS AND DISCUSSION According to the characteristics obtained from the simulation of regular and DSF buildings discussed above, the following results were obtained about the advantages of DSF buildings. Figs. 8 and 9 show that the results of Design Builder and the measured values is almost equal, thus this software has acceptable accuracy, which confirms its other results. According to Fig. 11, one point to be noticed is the coldest season in Tabriz, where the study that was carried out is reported to be January, and which in other cities is normally February. The figure

204

CHAPTER 1.12 EFFECT OF DOUBLE-SKIN FAC¸ADE ON THERMAL ENERGY

FIGURE 11 Comparison of heating load in double-skin fac¸ade (DSF) and single-skin fac¸ade (SSF) building.

shows the heating load of buildings from October 1 until the end of March. A comparison of the curves clearly shows that in both buildings, the greatest energy loss happens in January, when it is extremely cold in Tabriz. Moreover, the thermal load in all months for the building with DSF was less than the single-skin fac¸ade (SSF) buildings. During the cold season, the total thermal load of the SSF building was 67,761.18 kWh whereas for DSF building it was 46,307.35 kWh. Therefore, the rate of thermal loss for the regular building was 46.3% higher than for the DSF building. Table 3 shows the system heating load during different months. According to this table, the difference in minimum system heating load between the DSF and SSF buildings happens in January, which is the coldest season in Tabriz.

Table 3 System Heating Loads During Different Months System heating load in single-skin fac¸ade building (kWh) System heating load in double-skin fac¸ade building (kWh) Difference (%)

October

November

December

January

February

March

Total

311.56

4,802.18

18,335.93

23,997.87

14,874.14

5,429.50

67,761.18

24.45

2,266.46

12,691.69

18,227.45

10,225.21

2,872.10

46,307.35

92

53

31

24

31

47

46.3

3. RESULTS AND DISCUSSION

205

Figs. 12e14 show the rate of fossil fuels in the SSF and DSF buildings. Fig. 12 shows the rate of total fuel for electricity production and Fig. 13 shows the rate of natural gas for heating in the buildings. The total amount of fossil fuel used for DSF building is lower than that of the SSF building; however, the rate of fuel consumption to produce electricity in both buildings is equal. Also, total fuel for electricity production is almost constant between November and January, as shown in Fig. 12. The main reason is the constant consumption of electric energy to light office buildings. Table 4 lists the amount of fuel consumption for the buildings under study during different months. The rate of use of natural gas for heating and electricity production in DSF buildings is 17% lower than that in the SSF buildings.

FIGURE 12 Comparison of fuel consumption for electricity production. DSF, double-skin fac¸ade; SSF, single-skin fac¸ade.

FIGURE 13 Comparison of natural gas consumption in double-skin fac¸ade (DSF) and single-skin fac¸ade (SSF) buildings.

206

CHAPTER 1.12 EFFECT OF DOUBLE-SKIN FAC¸ADE ON THERMAL ENERGY

FIGURE 14 Comparison of total fuel consumption in double-skin fac¸ade (DSF) and single-skin fac¸ade (SSF) buildings.

Table 4 Consumption of Total Fuel During Different Months

Total fuel consumption in single-skin fac¸ade building (kg) Total fuel consumption in doubleskin fac¸ade building (kg)

October

November

December

January

February

March

Total

25,755

23,305

39,420

46,970

33,670

23,430

192,550

24,500

19,730

31,960

39,360

27,480

19,690

162,720

4. SUMMARY AND CONCLUSION In this study, we showed that DSF improves the energy performance of buildings. However, DSF has several impacts such as cost, optimization, solidity, lifetime, components, etc., that we did not discuss here. Therefore, research on DSF needs extended and complementary explorations to understand more clearly the challenge and effects of this fac¸ade in future. The main problem of DSF is its high cost beside the SSF. However, it is more cost-effective in the long run. The study’s findings are that: •

The rate of thermal energy loss of DSF buildings in mild conditions is lower than that of the regular buildings; in this way, thermal energy loss in Tabriz shows a reduction of 46.3%.

NOMENCLATURE

• • •

•

207

In the case of the use of DSF, the rate of the use of natural gas in office buildings decreases up to 17%, which can have an important role in preventing the loss of fossil fuels. In case of the use of DSF, the original cost of the mechanical equipment and repairing or maintaining them will decrease. The use of DSF is more suitable for office buildings than residential buildings, because office buildings are used longer during the day, when there is the possibility of the greater use of solar energy. The results of Design Builder and measured values are almost equal; thus this software has acceptable accuracy.

According to the discussions presented here, we can research improvements in DSF efficiency and decreasing its cost in the future. In addition, many works and research can be done on its effect on the environment and the rate of emissions.

NOMENCLATURE aR ar as cp D d Fs g Gr I IR Ir k l l/D Nu Pr Qas QasR Qasr Qs Q1 Q2 Q3 Q4 q00D Ra ti to t

Direct solar radiation absorption coefficient (-) Diffuse solar radiation absorption coefficient (-) Outer skin’s absorption coefficient (-) Specific heat of air (¼ 1005 J/kg (
C)) Distance between skins (m) Solar radiation transmittance (-) Outer skin area (m2) Gravitational acceleration (m/s2) Grashof number (-) Total radiation intensity on the outer surface (W/m2) Direct solar radiation on the outer skin (W/m2) Diffuse solar radiation on the outer skin (W/m2) Thermal conductivity (W/m K) Height of enclosure (m) Enclosure aspect ratio (-) Nusselt number (-) Prandtl number (-) Absorbed solar radiation (W) Absorbed direct solar radiation (W) Absorbed diffuse solar radiation (W) Heat in the glass mass (W) Heat flow from outer skin to outside by radiation (W) Heat flow from outer skin to outside by convection (W) Heat flow from outer skin to interspace by radiation (W) Heat flow from outer skin to interspace by convection (W) Heat transfer rate per unit surface area of the sidewall (W/m2) Rayleigh number (-) Inner space of building temperature (
C) Outside air temperature (
C) Inner skin’s outer surface’s temperature (
C)

208

ts 0 tm 0 ts a ap1 as1 as2 b Dt dth n r

CHAPTER 1.12 EFFECT OF DOUBLE-SKIN FAC¸ADE ON THERMAL ENERGY

Outer skin’s inner surface’s temperature (
C) Interspace temperature in previous period (
C) Outer skin’s inner surface’s temperature in previous period (
C) Thermal diffusivity (m2/s) Inner skin’s outer surface’s coefficient for heat transfer by convection (W/m2
C) Outer skin’s outer surface’s coefficient of heat transfer by convection (W/m2
C) Outer skin’s inner surface’s coefficient of heat transfer by convection (W/m2
C) Coefficient of volumetric thermal expansion (1/K) Temperature difference between skins (
C) Thermal boundary layer thickness (m) Kinematic viscosity (m2/s) Air density (¼ 1.25 kg/m3)

REFERENCES [1] Kim YM, Lee JH, Kim SM. Effect of double skin envelopes on natural ventilation and heating loads in office buildings. Energy and Buildings 2011;43:2118e26. [2] Baldinelli G. Double skin facades for warm climate region: analysis of a solution with an integrated movable shading system. Building and Environment 2009;44:1107e18. [3] Hien WN, Liping W, Chandra AN, Pandey AR, Xiaolin W. Effects of double glazed facade on energy consumption, thermal comfort and condensation for a typical office building in Singapore. Energy and Buildings 2005;37:563e72. [4] Yilmaz Z, Cetintas F. Double skin fac¸ade’s effects on heat losses of office buildings in Istanbul. Energy and Buildings 2005;37:691e7. [5] Gratia E, Herde AD. Are energy consumptions decreased with the addition of a double skin? Energy and Buildings 2007;39:605e19. [6] Høseggen R, Wachenfeldt BJ, Hanssen SO. Building simulation as an assisting tool in decision-making case study: with or without a double-skin fac¸ade. Energy and Buildings 2008;40:821e7. [7] Coussirat M, Guardo A, Jou E, Egusquiza E, Cuerva E, Alavedra P. Performance and influence of numerical sub-models on the CFD simulation of free and forced convection in double-glazed ventilated fac¸ades. Energy and Buildings 2008;40:1781e9. [8] Chan ALS, Chow TT, Fong KF, Lin Z. Investigation on energy performance of double skin fac¸ade in Hong Kong. Energy and Buildings 2009;41:1135e42. [9] Shameri MA, Alghoul MA, Sopian K, Fauzi M, Zain M, Elayeb O. Perspectives of double skin fac¸ade systems in buildings and energy saving. Renewable and Sustainable Energy Reviews 2011;15:1468e75. [10] Zeng Z, Li X, Li C, Zhu Y. Modeling ventilation in naturally ventilated double-skin fac¸ade with a venetian blind. Building and Environment 2012;27:1e6. [11] Barbosa S. Perspectives of double skin facades for naturally ventilated buildings. Renewable and Sustainable Energy Reviews 2014;40:1019e29. [12] Manz H. Total solar energy transmittance of glass double fac¸ades with free convection. Energy and Buildings 2004;36:127e36. [13] Manz H, Schaelin A, Simmler H. Airflow patterns and thermal behavior of mechanically ventilated glass double facades. Building and Environment 2004;39:1023e33. [14] Ding W, Hasemi Y. Smoke control through a double-skin facade used for natural ventilation. ASHRAE Journal 2006;112(Part 1):181e8. [15] Zhang R, Lam KP, Yao SC, Zhang Y. Coupled energy plus and computational fluid dynamics simulation for natural ventilation. Building and Environment 2013;68:100e13.

REFERENCES

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[16] Todorovic B, Cvjetkovic T. Double fac¸ades buildings heat losses and cooling loads calculation based on inter-space temperature. In: Proceedings, ECOS 2002, Berlin, Germany; July 3e5, 2002. [17] Ghiaasiaan SM. Convective heat and mass transfer. New York: Cambridge University Press; 2011. [18] Bejan A. Convection heat transfer. 3rd ed. Wiley; 2004. [19] Cotton MA, Jackson JD. Vertical tube air flows in the turbulent mixed convection regime calculated using a low Reynolds number keε model. International Journal of Heat Mass Transfer 1990;33. [20] McGregor RK, Emery AP. Free convection through vertical plane layers: moderate and high Prandtl number fluids. Journal of Heat Transfer 1969;91.

CHAPTER

ENERGY AND EXERGY ANALYSES OF A GEOTHERMAL-BASED INTEGRATED SYSTEM FOR TRIGENERATION

2.1

Osamah Siddiqui1, Ibrahim Dincer1, 2 UOIT, Oshawa, ON, Canada1; YTU, Istanbul, Turkey2

1. INTRODUCTION In this modern era, energy production forms an integral part of any economy. Global primary energy demands have been estimated to increase by 50% between the years 2016 and 2030 [1]. In order to meet incessantly increasing energy demands, fossil fuels have been the primary source of energy production globally. In 2013, fossil fuels accounted for approximately 81% of total global energy consumption [2]. The usage of fossil fuels is detrimental to the environment as they are primary contributors to carbon-based emissions. In addition, fossil fuel reserves are depleting due to continuous consumption. Renewable energy sources provide solutions to the problems associated with fossil fuels [3]. Solar, wind, geothermal, biomass, and hydroelectric power are currently the main renewable energy sources in use [4]. The utilization of renewable energy resources has increased rapidly in the recent years and is expected to rise continuously in the future [5]. Geothermal resources have been utilized for electricity generation since the 1900s [6]. Geothermal power plants are mainly classified into three major types: flash-steam, dry-steam, and binary-cycle. Flash-steam plants convert highpressure hot water found deep inside the earth to steam that drives the generator turbines. However, dry-steam plants utilize steam directly from geothermal reservoirs to drive the turbines. In binary-cycle power plants, the hot geothermal water is utilized to transfer heat to a secondary fluid with a low boiling temperature. The secondary fluid is converted to vapor, which drives the turbine. In order to make renewable energy systems more efficient and cost-effective, multigeneration systems can be implemented [7]. Various studies have proposed and analyzed renewable energye based multigeneration systems. AlZaharani et al. [8] proposed and analyzed a geothermal-based integrated system. The system consisted of a supercritical carbon dioxide Rankine cycle integrated with an organic Rankine cycle, electrolyzer, and a space heating system. The overall system energy and exergy efficiencies were found to be 14% and 32%, respectively. Al-Sulaiman et al. [9] conducted an exergy analysis on a novel trigeneration system. The system was comprised of parabolic trough solar Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00013-5 Copyright © 2018 Elsevier Inc. All rights reserved.

213

214

CHAPTER 2.1 ENERGY AND EXERGY ANALYSES

collectors and an organic Rankine cycle. In addition, a single-effect absorption chiller was included to provide the required cooling. Furthermore, the trigeneration system was designed to provide heating. The exergy efficiency of the trigeneration system was found to be considerably higher than the base case that included only electricity generation. The maximum exergy efficiency of the trigeneration system was found to be 20%. Heberle and Bru¨ggemann [10] analyzed geothermal-based combined power and heat generation systems. Geothermal resources at temperature levels below 177
C were considered in the study. The exergy efficiencies of combined power and heat generation systems were found to be significantly higher than systems with only power generation. Malik et al. [11] conducted a thermodynamic analysis on a renewable energyebased multigeneration system. Biomass and geothermal sources were included in the study. The system was designed to provide five useful outputs for residential applications. The energy and exergy efficiencies of the overall system were determined to be 57% and 20%, respectively. In addition, the boiler and combustion chamber were found to have the highest exergy destruction rates. Al-Ali and Dincer [12] proposed and analyzed a solargeothermal-based multigeneration system. The system outputs included electricity, space cooling and heating, and hot water. Furthermore, the energy and exergy efficiencies of the multigeneration system were compared with a system having electricity as the only output. The energy and exergy efficiencies of the multigeneration system were determined to be 78% and 37%, respectively. However, the system with only electricity as the output had energy and exergy efficiencies of 16% and 26%, respectively. Suleman et al. [13] also studied a renewable energyebased multigeneration system. Solar and geothermal sources were utilized. The system included two organic Rankine cycles for power generation, a drying system for drying wet products, and an absorption chiller to provide cooling. The overall energy and exergy efficiencies of the system were found to be 55% and 76%, respectively. Panchal et al. [14] investigated a solar and geothermal-based integrated system for multigeneration. The outputs of the system included power generation, cooling, heating, and drying. The overall system energy efficiency was found to be 37%. This was higher than the system efficiency of 7%, which was obtained for a system with single generation. Demir and Dincer [15] studied a hybrid solarenatural gas integrated system for electricity production and water desalination. A flash distillation unit was considered for desalination. The cogeneration system included solar-driven volumetric pressurized air receivers. In addition, the system included thermoelectric materials for electricity generation from waste heat of the Rankine cycle. The overall system energy efficiency was determined to be 44.5%. Furthermore, the overall system exergy efficiency was obtained as 54.9%. The desalination unit was found to be capable of producing 3.36 kg/s of fresh water from the proposed system. Ground or surface freshwater resources have been declining due to continuous usage. Azhar et al. [16] designed and analyzed a renewable energyebased multigeneration system with multistage flash desalination, electricity generation, space cooling, and industrial heating. The system was comprised of integrated solar, ocean thermal energy and geothermal resources of energy. The energy efficiency and exergy efficiency of the integrated system were evaluated to be 13.9% and 17.9%, respectively. Ezzat and Dincer [17] investigated a geothermal and solar-based multigeneration system. The useful system outputs included electricity, heating, cooling, and drying. The energy and exergy efficiencies of the overall system were obtained as 69.6% and 42.8%. Bicer and Dincer [18] proposed and analyzed a multigeneration system based on geothermal and solar PV/T renewable resources of energy. The integrated system provided power, cooling, heating, and drying. The overall system energy efficiency was obtained as 11%. The overall system exergy efficiency was obtained as 28%. Furthermore,

2. SYSTEM DESCRIPTION

215

Khalid et al. [19] proposed and analyzed integrated systems for power generation and desalination based on nuclear energy. The overall system exergy efficiencies were evaluated as 36.8% and 32.8% for different nuclear reactor technologies. Ozgener et al. [20] studied the applications of geothermal energy including power generation, cooling, drying, and heating depending on the temperature of the geothermal source. Moreover, Coskun et al. [21] conducted an exergoeconomic analysis of geothermal-based power generation facilities. In addition, El Emam and Dincer [22] conducted an economic and thermodynamic analysis of a regenerative geothermal organic Rankine cycle. The energy and exergy efficiencies were obtained as 16.4% and 48.8%. Ozlu and Dincer [23] investigated a solar-based multigeneration system for power generation, heating, cooling, and hydrogen production. The maximum energy and exergy efficiencies obtained were 57% and 36%, respectively. The previous studies were mainly focused on utilizing different combinations of renewable energy sources for multigeneration systems. However, conventional renewable energyebased power plants do not include a combination of different renewable energy sources. Hence, it is important to design and analyze multigeneration systems that are based on a single renewable source, as this reflects existing renewable energyebased power plants. In this study, a geothermal-based trigeneration system is proposed and analyzed thermodynamically. The system is designed to provide electricity as well as district heating and cooling. The technical specifications reported for Miravalles geothermal power plant have been utilized [24]. The specific objectives of the present study are as follows: (1) to develop a geothermal-based trigeneration system for electricity production, district heating, and district cooling; (2) to assess the performance of the system using energy and exergy analyses; and (3) to conduct a parametric study to investigate the effects of varying operating conditions on the overall performance of the system.

2. SYSTEM DESCRIPTION The proposed geothermal-based trigeneration system is shown in Fig. 1. The hot geothermal fluid is withdrawn from the production well at a mass flow rate of 760 kg/s, a temperature of 240
C, and a pressure of 3.3 MPa [24]. The withdrawn fluid is flashed to a pressure of 600 kPa in a flash chamber by an isenthalpic process. The resulting vapor is separated from the liquid in a separator and is directed to turbine 1. Turbine 1 generates electricity that is supplied to the grid. The steam leaving turbine 1 provides heat to the generator of an absorption cooling system before returning to the reinjection well. The absorption cooling cycle utilizes an ammonia-water mixture to provide district cooling. The heat provided to the generator by the steam is utilized to vaporize ammonia from the ammonia-water mixture. The vapor leaving the generator has an ammonia mass fraction of 0.99. This vapor rejects heat as it passes through the condenser. After rejecting heat in the condenser, it passes through a throttle valve to reach the required evaporator temperature and pressure. In the evaporator, the concentrated ammonia vapor absorbs heat to provide district cooling. In addition, the weak solution leaves the generator at a high temperature and passes through a heat exchanger where it transfers heat to the strong solution coming from the absorber. This reduces the amount of heat required in the generator to vaporize ammonia. After leaving the heat exchanger, the weak solution is throttled to the absorber pressure. In the absorber, the weak solution and the ammonia vapor from the evaporator combine to form a strong solution.

216

CHAPTER 2.1 ENERGY AND EXERGY ANALYSES

FIGURE 1 Schematic diagram of proposed trigeneration system.

The saturated liquid collected in the separator (state 6) passes through heat exchanger 1 with a mass flow rate of 650 kg/s, where it provides the required heat to the steam turbine 2 cycle. The saturated liquid at high temperature flows with a significantly high mass flow rate, which is utilized to provide district heating. After leaving heat exchanger 1, it passes through heat exchanger 2, where it rejects heat to a district heating system.

3. THERMODYNAMIC ANALYSIS

217

Conventional geothermal power plants are utilized solely for electricity generation. However, this study proposes and analyzes a trigeneration system, which can be employed for electricity generation, district heating, and district cooling. The technical specifications reported for Miravalles geothermal power plant have been utilized [24].

3. THERMODYNAMIC ANALYSIS The proposed trigeneration system is analyzed using energy and exergy analyses. The system performance is assessed using energy and exergy efficiencies. In addition, information about exergy destruction rates in different system components is also obtained. The analysis includes the assumptions: • • • • • •

The turbines and pumps operate adiabatically. The changes in kinetic and potential energies and exergies are negligible. The isentropic efficiencies of the turbines and pumps are 80%. The pressure losses in pipelines and heat exchangers are negligible. The reference or dead-state temperature is T0 ¼ 25
C and pressure is P0 ¼ 101.3 kPa. The system operates in a steady-state condition. The general mass rate balance for a control volume is written as: X X dmcv m_ i  m_ e ¼ dt e i

(1)

The general energy rate balance for a control volume is expressed as:  X   X  V2 V2 dEcv Q_  W_ þ m_ i hi þ i þ gZi  m_ e he þ e þ gZe ¼ 2 2 dt e i

(2)

Entropy is generated during a process due to irreversibilities. The entropy generation rate for a control volume is expressed by Bejan [25] as: dScv S_gen ¼ þ dt

X

m_ e se 

X

e

m_ i si 

i

X Q_k k

Tk

(3)

Exergy analysis is a significant aspect of thermodynamic analyses of thermal systems [26]. The exergy rate balance for a given control volume can be written as: X X _ Qþ _ w þ Ex _ d Ex (4) m_ i exi ¼ m_ e exe þ Ex i

e

where the physical exergy at a given state point can be evaluated as: ex ¼ h  ho  T0 ðs  s0 Þ

(5)

The rate balance equations for each system component follow: Flash chamber: The mass balance equation for the flash chamber is written as: m_ 1 ¼ m_ 2

(6)

218

CHAPTER 2.1 ENERGY AND EXERGY ANALYSES

The energy balance equation for the flash chamber is written as: m_ 1 h1 ¼ m_ 2 h2

(7)

The entropy balance equation for the flash chamber is written as: m_ 1 s1 þ S_gen;FS ¼ m_ 2 s2

(8)

The exergy balance equation for the flash chamber is written as: _ d;FS m_ 1 ex1 ¼ m_ 2 ex2 þ Ex

(9)

Turbine 1: The mass balance equation for turbine 1 is written as: m_ 3 ¼ m_ 4

(10)

The energy balance equation for turbine 1 is written as: m_ 3 h3 ¼ W_ T1 þ m_ 4 h4

(11)

The entropy balance equation for turbine 1 is written as: m_ 3 s3 þ S_gen;T1 ¼ m_ 4 s4

(12)

The exergy balance equation for turbine 1 is written as: _ d;T1 m_ 3 ex3 ¼ W_ T1 þ m_ 4 ex4 þ Ex

(13)

The electricity generated by turbine 1 can evaluated as: E_elec1 ¼ hg W_ T1

(14)

where hg denotes the efficiency of the electrical generator. Heat exchanger 1: The mass balance equation for heat exchanger 1 is written as: m_ 6 ¼ m_ 7 and m_ 10 ¼ m_ 11

(15)

The energy balance equation for heat exchanger 1 is written as: m_ 6 h6 þ m_ 10 h10 ¼ m_ 7 h7 þ m_ 11 h11

(16)

The entropy balance equation for heat exchanger 1 is written as: m_ 6 s6 þ m_ 10 s10 þ S_gen;HX1 ¼ m_ 7 s7 þ m_ 11 s11

(17)

The exergy balance equation for heat exchanger 1 is written as: _ d;HX1 m_ 6 ex6 þ m_ 10 ex10 ¼ m_ 7 ex7 þ m_ 11 ex11 þ Ex

(18)

Heat exchanger 2: The mass balance equation for heat exchanger 2 is written as: m_ 7 ¼ m_ 8 and m_ 13 ¼ m_ 14

(19)

The energy balance equation for heat exchanger 2 is written as: m_ 7 h7 þ m_ 13 h13 ¼ m_ 8 h8 þ m_ 14 h14

(20)

3. THERMODYNAMIC ANALYSIS

219

The entropy balance equation for heat exchanger 2 is written as: m_ 7 s7 þ m_ 13 s13 þ S_gen;HX2 ¼ m_ 8 s8 þ m_ 14 s14

(21)

The exergy balance equation for heat exchanger 2 is written as: _ d;HX2 m_ 7 ex7 þ m_ 13 ex13 ¼ m_ 8 ex8 þ m_ 14 ex14 þ Ex

(22)

The district heating provided is expressed as: Q_DH ¼ m_ 13 ðh14  h13 Þ

(23)

Turbine 2: The mass balance equation for turbine 2 is written as: m_ 11 ¼ m_ 12

(24)

The energy balance equation for turbine 2 is written as: m_ 11 h11 ¼ W_ T2 þ m_ 12 h12

(25)

The entropy balance equation for turbine 2 is written as: m_ 11 s11 þ S_gen;T2 ¼ m_ 12 s12

(26)

The exergy balance equation for turbine 2 is written as: _ d;T2 m_ 11 ex11 ¼ W_ T2 þ m_ 12 ex12 þ Ex

(27)

The electricity generated by turbine 2 can be evaluated as: E_elec2 ¼ hg W_ T2

(28)

where hg denotes the efficiency of the electrical generator. Condenser 1: The mass balance equation for condenser 1 is written as: m_ 12 ¼ m_ 9

(29)

The energy balance equation for condenser 1 is written as: m_ 12 h12 ¼ Q_l;C1 þ m_ 9 h9

(30)

The entropy balance equation for condenser 1 is written as: m_ 12 s12 þ S_gen;C1 ¼ m_ 9 s9 þ

Q_l;C1 T0

The exergy balance equation for condenser 1 is written as:   T0 _ _ d;C1 þ Ex m_ 12 ex12 ¼ m_ 9 ex9 þ Ql;C1 1  TC1

(31)

(32)

Pump 1: The mass balance equation for pump 1 is written as: m_ 9 ¼ m_ 10

(33)

220

CHAPTER 2.1 ENERGY AND EXERGY ANALYSES

The energy balance equation for pump 1 is written as: m_ 9 h9 þ W_ P1 ¼ m_ 10 h10

(34)

The entropy balance equation for pump 1 is written as: m_ 9 s9 þ S_gen;P1 ¼ m_ 10 s10

(35)

The exergy balance equation for pump 1 is written as: _ d;P1 m_ 9 ex9 þ W_ P1 ¼ m_ 10 ex10 þ Ex

(36)

The rate balance equations for the absorption cooling system follow [27]: Generator: The heat supplied to the generator by the steam can be written as follows: Q_gen ¼ m_ 5 ðh4  h5 Þ

(37)

The total mass rate balance equation for the generator of the absorption cooling system can be written as: m_ 21 ¼ m_ 15 þ m_ 22

(38)

The ammonia mass rate balance equation for the generator can be written as: x21 m_ 21 ¼ x15 m_ 15 þ x22 m_ 22

(39)

where x represents the ammonia mass fraction. The energy rate balance equation for the generator can be written as: m_ 21 h21 þ Q_gen ¼ m_ 15 h15 þ m_ 22 h22

(40)

Condenser 2: The mass balance equation for condenser 2 is written as: m_ 15 ¼ m_ 16

(41)

The energy balance equation for condenser 2 is written as: m_ 15 h15 ¼ Q_l;C2 þ m_ 16 h16

(42)

The entropy balance equation for condenser 2 is written as: m_ 15 s15 þ S_gen;C2 ¼ m_ 16 s16 þ

Q_l;C2 T0

The exergy balance equation for condenser 2 is written as:   T0 _ _ d;C2 þ Ex m_ 15 ex15 ¼ m_ 16 ex16 þ Ql;C2 1  TC2

(43)

(44)

Throttling valve 1: The mass balance equation for throttling valve 1 is written as: m_ 16 ¼ m_ 17

(45)

The energy balance equation for the throttling valve 1 is written as: m_ 16 h16 ¼ m_ 17 h17

(46)

3. THERMODYNAMIC ANALYSIS

221

The entropy balance equation for the throttling valve 1 is written as: m_ 16 s16 þ S_gen;TV1 ¼ m_ 17 s17

(47)

The exergy balance equation for the throttling valve 1 is written as: _ d;TV1 m_ 16 ex16 ¼ m_ 17 ex17 þ Ex

(48)

Evaporator: The mass balance equation for the evaporator is written as: m_ 17 ¼ m_ 18

(49)

The energy balance equation for the evaporator is written as: m_ 17 h17 þ Q_EV ¼ m_ 18 h18

(50)

The entropy balance equation for the evaporator is written as: m_ 17 s17 þ

Q_EV þ S_gen;EV ¼ m_ 18 s18 T0

The exergy balance equation for the evaporator is written as:   T0 _ _ d;EV ¼ m_ 18 ex18 þ Ex m_ 17 ex17 þ QEV 1  TEV

(51)

(52)

Absorber: The total mass balance equation for the absorber is written as: m_ 18 þ m_ 24 ¼ m_ 19

(53)

The ammonia mass balance equation for the absorber is written as: x18 m_ 18 þ x24 m_ 24 ¼ x19 m_ 19

(54)

where x represents the ammonia mass fraction. The energy balance equation for the absorber is written as: m_ 18 h18 þ m_ 24 h24 ¼ m_ 19 h19 þ Q_abs

(55)

The exergy balance equation for the absorber is written as: m_ 18 ex18 þ m_ 24 ex24

  T0 _ ¼ m_ 19 ex19 þ Qabs 1  Tabs

(56)

Throttling valve 2: The mass balance equation for throttling valve 2 is written as: m_ 23 ¼ m_ 24

(57)

The energy balance equation for the throttling valve 2 is written as: m_ 23 h23 ¼ m_ 24 h24

(58)

The entropy balance equation for the throttling valve 2 is written as: m_ 23 s23 þ S_gen;TV2 ¼ m_ 24 s24

(59)

222

CHAPTER 2.1 ENERGY AND EXERGY ANALYSES

The exergy balance equation for the throttling valve 2 is written as: _ d;TV2 m_ 23 ex23 ¼ m_ 24 ex24 þ Ex

(60)

Pump 2: The mass balance equation for pump 2 is written as: m_ 19 ¼ m_ 20

(61)

The energy balance equation for pump 2 is written as: m_ 19 h19 þ W_ P2 ¼ m_ 20 h20

(62)

The entropy balance equation for pump 2 is written as: m_ 19 s19 þ S_gen;P2 ¼ m_ 20 s20

(63)

The exergy balance equation for pump 2 is written as: _ d;P2 m_ 19 ex19 þ W_ P2 ¼ m_ 20 ex20 þ Ex

(64)

Heat exchanger 3: The mass balance equations for heat exchanger 3 is written as: m_ 20 ¼ m_ 21 and m_ 22 ¼ m_ 23

(65)

The energy balance equation for heat exchanger 3 is written as: m_ 20 h20 þ m_ 22 h22 ¼ m_ 21 h21 þ m_ 23 h23

(66)

The entropy balance equation for heat exchanger 3 is written as: m_ 20 s20 þ m_ 22 s22 þ S_gen;HX3 ¼ m_ 21 s21 þ m_ 23 s23

(67)

The exergy balance equation for heat exchanger 3 is written as: _ d;HX3 m_ 20 ex20 þ m_ 22 ex22 ¼ m_ 21 ex21 þ m_ 23 ex23 þ Ex

(68)

Neglecting the pump work, the COP of the absorption cooling system is calculated as: COPABCS ¼

Q_EV Q_gen

(69)

where Q_EV denotes the cooling load that is obtained from the evaporator, and Q_gen denotes the heat input to the absorption cooling system in the generator. The efficiency of an integrated system can be evaluated as the ratio of the total useful energy output to the total energy input [28]. The overall system energy and exergy efficiencies are calculated as: E_elec1 þ E_elec2 þ Q_EV þ Q_DH m_ 1 h1  m_ 8 h8  m_ 5 h5     T0 T0 E_elec1 þ E_elec2 þ Q_EV 1  þ Q_DH 1  TEV TDH ¼ m_ 1 ex1  m_ 8 ex8  m_ 5 ex5 hov ¼

jov

(70)

(71)

4. RESULTS AND DISCUSSION

223

4. RESULTS AND DISCUSSION

The values of mass flow rate (kg/s), temperature (
C), pressure (kPa), specific enthalpy (kJ/kg), specific entropy (kJ/kg K), and specific exergy (kJ/kg) determined for each state of the system are listed in Table 1. A temperature of 25
C and a pressure of 101.3 kPa have been taken as the referenceenvironment conditions. The thermodynamic properties are calculated using the Engineering Equation Solver (EES) software [29]. The output and input values of various system components are tabulated in Table 2. The heating load considered in this study is 6000 kW [30]. The work output of turbine 1 is calculated as 21,258 kW.

Table 1 Input and Calculated Process Data for the Trigeneration System State No. 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Fluid Type

P (kPa)

m_ (kg/s)

T (
C)

h (kJ/kg)

s (kJ/kg K)

ex (kJ/kg)

Water Water Water Water Water Water Water Water Water Water Water Water Water Water Water Water/ Ammonia Water/ Ammonia Water/ Ammonia Water/ Ammonia Water/ Ammonia Water/ Ammonia

101.3 3345 600 600 150 150 600 600 600 10 3000 3000 10 110 110 1555.76

e 760 760 110 110 110 650 650 650 10 10 10 10 28.7 28.7 7.55

25 240 158.9 158.9 111.4 111.4 158.9 149.6 147.5 45.8 46.1 233.9 45.8 35 85 44.7

104.8 1037 1037 2757 2563 2430 670.9 630.9 621.6 191.8 195.6 2796 2121 146.7 356 1308.9

0.37 2.70 2.78 6.76 6.89 6.54 1.93 1.84 1.82 0.64 0.65 6.17 6.69 0.51 1.13 4.22

0 236.4 213 745.9 515.2 485.1 99.4 87.3 84.6 2.8 5.9 960.5 128.7 0.69 22.3 371.4

1555.76

7.55

40

190.76

0.658

315.3

244.85

7.55

14.14

190.76

0.753

287

244.85

7.55

10.00

1258.83

4.86

130.5

244.85

55

40.00

43.26

0.48

1.70

1555.76

55

40.44

40.22

0.47

7.72 Continued

224

CHAPTER 2.1 ENERGY AND EXERGY ANALYSES

Table 1 Input and Calculated Process Data for the Trigeneration Systemdcont’d State No. 21 22 23 24 25 26

Fluid Type

P (kPa)

m_ (kg/s)

T (
C)

h (kJ/kg)

s (kJ/kg K)

ex (kJ/kg)

Water/ Ammonia Water/ Ammonia Water/ Ammonia Water/ Ammonia Water Water

1555.76

55

110.00

302.15

1.45

57.91

1555.76

47.452

130.29

396.09

1.64

69.03

1555.76

47.452

40.442

0.72

0.531

2.86

244.85

47.452

40.711

0.72

0.535

1.67

110 110

34.41 34.41

60 4

251.2 16.93

0.831 0.061

7.98 3.26

Table 2 Input and Output Values of Important System Components System Component

Value (kW)

Turbine 1 Turbine 2 District cooling District Heating Work input to Pump 1

21,258 6,742 8,061 6,000 [30] 37.7

In addition, the turbine 2 has a work output of 6742 kW. The exergy destruction rates of various system components are shown in Fig. 2. The maximum exergy destruction rate occurs in the flash chamber, followed by turbine 1 and turbine 2. The overall energy efficiency of the system is found to be 32.4%. However, if the system is considered without any district heating or cooling, the energy efficiency is found to be 20.3%. Hence,

FIGURE 2 Exergy destruction rates of system components.

4. RESULTS AND DISCUSSION

225

the energy efficiency of the proposed trigeneration system is 12.1% higher than a system with only electricity generation. In addition, the overall exergy efficiency of the system is found to be 36.1%. However, if district heating and cooling are excluded, the system has an overall exergy efficiency of 33.3%. Thus, the trigeneration system is found to have 3.2% higher exergy efficiency than a system comprising only electricity generation. Moreover, the coefficient of performance of the absorption cooling system is found to be 0.55.

4.1 EFFECT OF DISTRICT COOLING ON SYSTEM EFFICIENCIES The proposed system can be utilized to provide higher district cooling loads than considered in the analyses earlier. The effect of the district cooling load on the overall system energy and exergy efficiencies is shown in Fig. 3. The overall system energy efficiency is found to increase to 35.8% from 32.4% if the cooling load increases to 20,000 from 8000 kW. However, the overall system energy efficiency decreases to 31.6% from 32.4% if the cooling load decreases to 6000 from 8000 kW. In addition to this, the exergy efficiency of the overall system is found to decrease with increasing cooling load. The exergy efficiency decreases to 34.1% at a cooling load of 20,000 kW. However, the exergy efficiency is found to be 36.5% at lower cooling load of 6000 kW. This can be attributed to the temperature, enthalpy, and entropy change of state 5 with the cooling load. State 5 has been included in the efficiency definitions. As the cooling load increases, the heat provided to the generator also increases. As more heat is supplied to the generator by the steam, the exergy of state 5 decreases with increasing cooling load.

0.37 η ov ψov

Overall System Efficiency

0.36 0.35 0.34 0.33 0.32 0.31 6000

8000

10000

12000

14000

16000

District Cooling (kW)

FIGURE 3 Effect of district cooling on the overall system energy and exergy efficiencies.

18000

20000

226

CHAPTER 2.1 ENERGY AND EXERGY ANALYSES

4.2 EFFECT OF DISTRICT HEATING ON SYSTEM EFFICIENCIES In addition, the current system can be utilized to provide higher district heating loads. Fig. 4 shows the effect of varying heating load on the overall system energy and exergy efficiencies. The energy efficiency is found to increase to 35.7% from 32.4% as the heating load increases to 12,000 from 6000 kW. However, the energy efficiency drops to 31.1% from 32.4% when the heating load decreases to 4000 from 6000 kW. Furthermore, the overall system exergy efficiency is found to vary from 35.6% to 37.6% as the heating load changes from 4000 to 12,000 kW.

4.3 EFFECT OF TURBINE ISENTROPIC EFFICIENCIES ON OVERALL SYSTEM PERFORMANCE The isentropic efficiency of the turbines affects the overall system performance. Fig. 5 shows the effect of the isentropic efficiencies of turbine 1 and turbine 2 on the overall system energy and exergy efficiency. The energy efficiency of the overall system changes from 26.6% to 34.1% as the isentropic efficiencies of the turbines varies from 50% to 90%. In addition, the exergy efficiency of the overall system increases from 24.2% to 39.9% as the isentropic efficiencies of the turbines increases from 50% to 90%. As the isentropic efficiency of the turbine increases, the irreversibilities decrease. Hence, a turbine with a higher isentropic efficiency is capable of producing more power. This leads to an increase in the overall system efficiencies.

4.4 EFFECT OF GEOTHERMAL FLUID TEMPERATURE ON SYSTEM EFFICIENCIES The temperature of the geothermal fluid extracted from the production well affects the overall system efficiencies. Fig. 6 shows the effect of varying geothermal fluid temperature on the overall system 0.38

η ov

Overall System Efficiency

0.37

ψov

0.36 0.35 0.34 0.33 0.32 0.31 0.3 4000

5000

6000

7000 8000 9000 10000 District Heating (kW)

FIGURE 4 Effect of district heating on the overall system energy and exergy efficiencies.

11000

12000

4. RESULTS AND DISCUSSION

227

0.42 ηov

0.4

ψov

Overall System Efficiency

0.38 0.36 0.34 0.32 0.3 0.28 0.26 0.24 0.22 0.5

0.6

0.7 0.8 Turbine Isentropic Efficiency

0.9

FIGURE 5 Effect of turbine isentropic efficiency on the overall system energy and exergy efficiencies. 0.9 ηov

Overall System Efficiency

0.8

ψov

0.7 0.6 0.5 0.4 0.3 0.2 220

230

240 T1 (°C)

250

260

FIGURE 6 Effect of geothermal fluid temperature on the overall system energy and exergy efficiencies.

energy and exergy efficiencies. The energy efficiency of the overall system is found to increase considerably with decreasing fluid temperature. At a geothermal fluid temperature of 220
C, the energy efficiency is found to be 82.8%. However, at a fluid temperature of 260
C, at the same pressure of 3345 kPa, the energy efficiency reduces to 19.8%. In addition, the exergy efficiency decreases from 61.7% to 24.8% as the geothermal fluid temperature increases from 220 to 260
C. This can be

228

CHAPTER 2.1 ENERGY AND EXERGY ANALYSES

Overall System Exergy Efficiency

0.38

0.37

0.36

0.35 280

290

300

310 T0 (K)

320

330

340

350

FIGURE 7 Effect of ambient temperature on the overall system exergy efficiency.

attributed to the enthalpy and entropy of state 1. State 1 affects the energy input to the overall system. At a higher geothermal fluid temperature, at the same pressure, the enthalpy of state 1 increases. Hence, as the energy input to the system increases, the overall system efficiency decreases for the same overall output from the system.

4.5 EFFECT OF AMBIENT TEMPERATURE ON SYSTEM EFFICIENCIES Variations in the ambient temperature affect the performance of thermodynamic systems. The efficiencies may increase or decrease with changing ambient temperature. Fig. 7 shows the effect of varying ambient temperature on the overall system exergy efficiency. At an ambient temperature of 280K, the system exergy efficiency is found to be 35.7%. However, the exergy efficiency increases to 37.3% as the ambient temperature increases to 350K. Hence, the exergy efficiency of the proposed system is found to increase with increasing ambient temperature. This can be attributed mainly to the exergy of state 1. State 1 has the highest mass flow rate, and it affects the exergy input to the system. As the ambient temperature increases from 280 to 350K, the specific exergy of state 1 decreases from 281.1 to 133.2 kJ/kg. This decreases the exergy input to the system considerably.

5. CONCLUSIONS A geothermal-based trigeneration system for electricity production, district heating, and district cooling is proposed and analyzed. The system performance is assessed using energy and exergy analyses. The overall system energy efficiency of the system is found to be 32.4%. Electricity generation output is significantly higher than the cooling or heating load. Higher efficiencies can be obtained if higher cooling and heating loads are considered. However, 32.4% energy efficiency corresponds to a 12.1% increase in the efficiency as compared to a system with only electricity

NOMENCLATURE

229

generation. In addition, the overall exergy efficiency of the system is found to be 36.1%. This represents a 3.2% increase in exergy efficiency as compared to a system comprising only electricity generation. Moreover, the coefficient of performance of the absorption cooling system is found to be 0.55. The exergy efficiency of the system is found to increase considerably with increasing turbine isentropic efficiencies. In addition, the geothermal fluid temperature is found to affect the system performance significantly. Geothermal power plants with a high geothermal fluid mass flow rate can be utilized to achieve multiple system outputs such as district heating and cooling. As is shown in the current study, the overall system performance of geothermal power plants can be increased by implementing trigeneration systems.

NOMENCLATURE COP _ Ex ex h m_ P Q_ s T V W_

Coefficient of performance Exergy rate (kW) Specific exergy (kJ/kg) Specific enthalpy (kJ/kg) Mass flow rate (kg/s) Pressure (kPa) Heat rate (kW) Specific entropy (kJ/kg K) Temperature (
C) Velocity Work rate (kW)

Greek letters h j

Energy efficiency Exergy efficiency

Subscripts ABCS abs c cv d DH e eg elec EV FS gen HX i l ov P

Absorption cooling system Absorber Condenser Control volume Destruction District heating Exit Electric generator Electricity Evaporator Flash chamber Generator Heat exchanger Inlet Lost Overall Pump

230

T TV x

CHAPTER 2.1 ENERGY AND EXERGY ANALYSES

Turbine Throttle valve Mass fraction

REFERENCES [1] The monthly energy review. U.S. Energy Information Administration; April 2016. DOE/EIA-0035(2016/4). [2] Fossil fuel energy consumption (% of total). World bank. Retrieved from http://data.worldbank.org/ indicator/EG.USE.COMM.FO.ZS. [3] National Renewable Energy Laboratory. Available from: http://www.nrel.gov. [4] Ahmadi P, Dincer I, Rosen MA. Development and assessment of an integrated biomass-based multigeneration energy system. Energy 2013;56:155e66. [5] International Energy Agency. Available from: http://www.iea.org/. [6] Kanoglu M, Bolatturk A. Performance and parametric investigation of a binary geothermal power plant by exergy. Renewable Energy 2008;33:2366e74. [7] Dincer I, Zamfirescu C. Sustainable energy systems and applications. Springer; 2011. [8] AlZaharani AA, Dincer I, Naterer GF. Performance evaluation of a geothermal based integrated system for power, hydrogen and heat generation. International Journal of Hydrogen Energy 2013;38(34):14505e11. [9] Al-Sulaiman FA, Dincer I, Hamdullahpur F. Exergy modeling of a new solar driven trigeneration system. Solar Energy 2011;85(9):2228e43. [10] Heberle F, Bru¨ggemann D. Exergy based fluid selection for a geothermal Organic Rankine Cycle for combined heat and power generation. Applied Thermal Engineering 2010;30:1326e32. [11] Malik M, Dincer I, Rosen MA. Development and analysis of a new renewable energy-based multi-generation system. Energy 2015;79:90e9. [12] Al-Ali M, Dincer I. Energetic and exergetic studies of a multigenerational solar-geothermal system. Applied Thermal Engineering 2014;71:16e23. [13] Suleman F, Dincer I, Agelin-Chaab M. Development of an integrated renewable energy system for multigeneration. Energy 2014;78:196e204. [14] Panchal S, Dincer I, Agelin-Chaab M. Analysis and evaluation of a new renewable energy based integrated system for residential applications. Energy and Buildings 2016;128:900e10. [15] Demir ME, Dincer I. Development of an integrated hybrid solar thermal power system with thermoelectric generator for desalination and power production. Desalination 2017;404:59e71. [16] Azhar MS, Rizvi G, Dincer I. Integration of renewable energy based multigeneration system with desalination. Desalination 2017;404:72e8. [17] Ezzat MF, Dincer I. Energy and exergy analyses of a new geothermal-solar energy based system. Solar Energy 2016;134:95e106. [18] Bicer Y, Dincer I. Analysis and performance evaluation of a renewable based multigeneration system. Energy 2016;134:95e106. [19] Khalid F, Dincer I, Rosen MA. Comparative assessment of CANDU 6 and Sodium-cooled Fast Reactors for nuclear desalination. Desalination 2016;379:182e92. [20] Ozgener L, Hepbasli A, Dincer I. Energy and exergy analysis of Salihli geothermal district heating system in Manisa, Turkey. International Journal of Energy Research 2005;29:393e408. [21] Coskun C, Oktay Z, Dincer I. Modified exergoeconomic modeling of geothermal power plants. Energy 2011; 36:6358e66. [22] El Emam RS, Dincer I. Exergy and exergoeconomic analyses and optimization of geothermal organic Rankine cycle. Applied Thermal Engineering 2013;59:435e44.

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[23] Ozlu S, Dincer I. Analysis and evaluation of a new solar energy-based multigeneration system. International Journal of Energy Research 2016;40:1339e54. [24] DiPippo R. Miravalles power station, Guanacaste Province, Costa Rica. In: Geothermal power plants: principles, applications, case studies and environmental impact. Amsterdam: Butterworth-Heinemann; 2008. p. 331e47. [25] Bejan A. Fundamentals of exergy analysis, entropy generation minimization, and the generation of flow architecture. International Journal of Energy Research 2002;26:0e43. [26] Cengel YA, Boles MA. Thermodynamics: an engineering approach. 8th ed. Iowa, USA: McGraw-Hill; 2014. [27] Herold KE, Radermacher R, Klein SA. Absorption chillers and heat pumps. USA: CRC Press; 1996. [28] Dincer I, Rosen MA. Exergy. 2nd ed. Oxford, UK: Elsevier; 2013. [29] Klein SA. Engineering equation solver (EES) for Microsoft windows operating systems, Academic Professional V10.091. [30] Soltani R, Dincer I, Rosen MA. Thermodynamic analysis and performance assessment of an integrated heat pump system for district heating applications. Applied Thermal Engineering 2015;89:833e42.

CHAPTER

COMPARATIVE ASSESSMENT OF THREE INTEGRATED TRIGENERATION SYSTEMS FOR DAIRY FARMS

2.2

Eren Sevinchan1, Ibrahim Dincer1, 2 UOIT, Oshawa, ON, Canada1; YTU, Istanbul, Turkey2

1. INTRODUCTION Due to the implementation of fast-developing technologies and the increasing population, the energy requirements of the world have increased exponentially and this is expected to continue, particularly in developing countries. Because of this increase in energy consumption, more efficient use of energy and implementation of low-energy consuming systems have gained importance. It is also a critical issue to produce energy as cleanly as possible and achieve its effective use. It should not be forgotten that a great majority of today’s energy needs are met by fossil fuels. Thus, fossil resources will be exhausted one day, and people will have to use new energy sources. The most important and effective method for this situation is undoubtedly renewable energy sources. Another advantage of renewable energy sources over fossil sources is that they usually produce much less CO2 emissions (or become carbon neutral) and hence become environmentally friendly. A dairy farm is recognized as a farm where its purpose is to produce milk products and sell them accordingly. It may individually be run or run by a management team. The dairy farm animals are usually cows, and these dairy farms’ energy usages are evaluated by the annual energy consumption per cow. The energy usage differs among countries, depending on the location, animals, operating practices, management, energy systems, buildings, etc. Therefore, an average capacity should be considered to see how much electricity a dairy farm needs. The energy usage is not the same in every country due to several reasons, for example, the heating loads depend closely on a country’s climate, especially their winter seasons, which make the country’s climate one of the key reasons. In cold climate countries, more energy is needed to heat the farm and the water that is used to clean milking machines. A similar situation is valid in the hot climate countries. In such countries, the cooling processes need to be more energy efficient because of the hot weather outside. The fresh milk should be kept at 4
C to preserve it from bacteria that may spoil the milk. Thus, the hot climate increases the energy usage for cooling purposes. Secondly, the animal features are not the same in all countries, since some cows need little milking in a day, which makes their energy usage less than other cows that live in a different part of the world. When cows need less milking, this means less utilization of milking machines and hence less cooling load required for the Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00014-7 Copyright © 2018 Elsevier Inc. All rights reserved.

233

234

CHAPTER 2.2 INTEGRATED TRIGENERATION SYSTEMS FOR DAIRY FARMS

milk. According to some researchers [1], the highest energy usage of a dairy farm takes place in the mornings and early evenings when milking machines operate. The research on dairy farms in Ontario has found that on average dairy farms used 800e1400 kWh/cow/year [1]. Another research project in Wisconsin confirms that a dairy farm uses between 800 and 1200 kWh/cow-year of electricity, while in another study the range was from 424 to 1736 kWh/cow-year [2]. The electrical consumption is about 5800e6100 kWh in the months between June and August for dairy farms that have more than 100 cows. On the other hand, the lowest capacity is about 5000 kWh for dairy farms that have more than 100 cows [3]. If 1400 kWh is assumed to be an annual energy usage of a dairy farm per cow, the daily energy utilization is 762.12 kWh for 200 cows. When all these energy needs of a dairy farm in the forms of electricity heating and cooling loads are taken into consideration, trigeneration systems can play an effective role. Note that a trigeneration system is an integrated energy system that involves electricity generation, heating and cooling processes simultaneously from the same energy source. The key point of using the same power supply for all these applications is that waste heat from the prime mover is used for cooling and heating. Huicochea [4] presented a trigeneration system consisting of a microturbine of 28 kW as a prime mover, and a double-effect absorption chiller was used in the same study for cooling load of the system. Geetal [5] utilized an 80 kW micro-gas turbine in a trigeneration system where 10% of the exhaust gas is recovered by a 12 kW water-ammonia absorption chiller generator. Sun [6] harnessed the exhaust gas of a 24.5 kW micro-gas turbine in addition to an auxiliary burner to operate a double-effect absorption chiller of 52.7 kW cooling capacity. Moran [7] simulated the performance of a combined cooling, heating and power trigeneration system (CCHP) with an internal combustion engine (ICE) running on natural gas and diesel. Another study [8] was conducted by Maidment to investigate the feasibility of integrating a combustion engine with an absorption chiller for a supermarket application. Tracy [9] analyzed the performance of a small-scale ICE-driven CCHP system based on the first and second laws of thermodynamics. Ebrahimi [10] presented energy and exergy analysis of a micro-CCHP system for a residential application using a micro-scale steam turbine as a prime mover with a steam ejector refrigeration unit to meet the cooling demands. Based on the optimization process, system overall efficiency of 22.82% in summer and 62.15% in winter was reported with a fuel energy saving ratio of 69% and 25%, respectively. Lian [11] conducted a thermoeconomic analysis of a biomass-driven trigeneration system using a steam turbine as a prime mover coupled with an absorption chiller. It was found that the overall production cost is directly proportional to steam temperature and inversely proportional to steam pressure, where the furnace accounts for 60% of the overall exergy destruction. The efficiency of a trigeneration system depends primarily on the performance of each unit, such as prime movers, cooling and heating units. The objective of this study is to compare three unique trigeneration systems that use biomass as an energy source with different forms of it. System 1 consists of a gasifier to produce syngas from biomass. System 2 involves a biomass digester to produce biogas from biomass. Finally, system 3 includes a biomass burner to use biomass directly. As an additional objective of this study, the energy efficiencies of these three trigeneration systems were investigated parametrically and compared to each other for performance assessment.

2. SYSTEM DESCRIPTION Here, in this section some background details and energy utilization behavior as well as operational details are presented.

2. SYSTEM DESCRIPTION

235

2.1 BACKGROUND DETAILS Before the equations and analysis results, some background information needs to be mentioned. Systems 1, 2, and 3 contain the subsystems and components as described below, along with some other details about the operating conditions. Note that system 1 contains a gasifier that is an effective alternative process to use biomass as an energy source. After the gasification process of the biomass, syngas (synthesis gas) consists of a product of this operation. This gasifier is chosen as a fluid bed gasifier due to the syngas’s lower heating value, which is enough to use it in the system. The fluidized bed gasifiers are considered more advanced ones with excellent mixing features and high rates of gas-solid contacts. The fluidizing material is usually silica sand, although alumina and other refractory oxides have been used to avoid sintering, and some catalysts have also been used to reduce tars and modify product gas composition. The fluidized bed gasifier that is used in system 1 is adapted from a study in the literature [12]. Also, this time system 2 consists of a biomass digester that produces biogas to use as an energy source in the system. Biogas is a gas that contains methane, carbon dioxide, hydrogen, and nitrogen in different percentages. Biogas may be composed mostly of CH4 (50%e70%) and CO2 (25%e50%), with low fractions of H2 (1%e5%), N2 (0.3%e3%), and H2S traces [13]. The production of the biogas is completed in four consecutive stages: hydrolysis, acidogenesis, acetogenesis, and methanogenesis. In the hydrolysis stage, microorganisms excrete enzymes to break down organic matter like carbohydrates, lipids, and nucleic acids into the smaller units of glucose, glycerol, purines, and pyridines. Then, fermentative microorganisms process the products of hydrolysis into acetate, carbon dioxide, hydrogen, and volatile fatty acids in the acidogenesis stage. The third stage is acetogenesis, where the volatile fatty acids and alcohols are oxidized into acetate, hydrogen, and carbon dioxide before conversion into methane. Finally, methanogenesis takes place where the specialized single-celled microorganisms (archaea) produce methane from acetate, hydrogen, and carbon dioxide. Furthermore, the third system uses biomass directly as a source of energy by burning it directly in a biomass burner. Direct biomass use is one of the basic utilizations of the biomass as an energy source. Its usage dates back many years, and it is used in many farms and villages in various parts of the World. It can be used as coal by burning the biomass directly to heat a place or cook. If we investigate the wood as biomass, it can be easier to see how the biomass utilization is quite a basic and ancient method. First of all, the biomass needs to be converted to a biomass fuel supply for proper use in the generation system. Before the combustion process, the biomass should be under some specific moisture content point to make the combustion process more efficient. This dry biomass is mixed with air that comes from the combustion air supply in a furnace. Depending on the wet lower heating value (LHV) of received biomass fuel, the typical combustion efficiencies vary in the range of 65% in poorly designed furnaces up to 99% in highly sophisticated, well-maintained, and perfectly insulated combustion systems [14]. After combustion, all systems begin to produce power with the fluid reaching high pressure and temperature. Systems 1 and 2 use the open-type Brayton cycle, while system 3 uses the closed-type Brayton cycle. The outputs of the Brayton cycles are different for each system, depending on the lower heating values and air fuel rates of the fuels. The waste heat from the gas turbine generates electricity again by operating the organic Rankine cycle (ORC) unit and is also used in the production of hot water and hot air required for the dairy farm. The Rankine engines were designed to convert heat into useful work based on the thermodynamic Rankine cycle. The Rankine systems are divided mainly

236

CHAPTER 2.2 INTEGRATED TRIGENERATION SYSTEMS FOR DAIRY FARMS

into two classifications: steam Rankine systems that use water as a working fluid and organic Rankine systems that use an organic fluid as a working fluid. This difference is the main one between steam and ORCs [15]. The waste heat from the ORC unit also activates the single effect absorption chiller and provides the cooling load of the dairy farm. Absorption cooling is a mature and well-established cooling technology that has been employed for many years in various cooling and air conditioning applications [16]. The features and some values of the ORC and single-effect absorption chiller are adapted from the study by Al-Sulaiman et al. [17]. It should be specifically stated that the ORC and chiller properties are the same for all systems.

2.2 SYSTEM ENERGY DETAILS The annual energy utilization of a cow is assumed as 1400 kWh and the systems are designed to serve a dairy farm with 200 cows. Therefore, the total energy need for a 200-cow dairy farm per hour (ENDFH) can be calculated as: ENDFH ¼

200 cows  1400 kWh ¼ 31:96 kWh y 32 kWh 365 days  24 h

(1)

The other important output of the systems is heating load. The heating capacity can be divided into two main applications, water heating and air heating. Since there is a heating demand for the cleaning of the milking machines and hot water utilization of the dairy farm, it is necessary to analyze and assess their use. The water heating has a significant role for a dairy farm. A dairy farm that includes 200 cows needs to have 4000 kg water per day to be adequate for applications that use hot water, and the hot water should be heated up to 65
C [18]. The common usages of the water in a dairy farm are for milking system cleanup, milking parlor cleanup, and if used, milking parlor flushing, milk bulk tank cleanup, prepping cows for milking, and milk precooling [19]. Air heating is a less essential process than water heating because it is required in only cold seasons. However, heat stress is a feature of the cows that does not allow the increase of heat higher than 25
C. Therefore, the heat of the barns should be kept below 25
C. The environment temperature is assumed as 10
C, so the air should be heated from 10 to 25
C in a day. Also, the required fresh air for a 200-cow dairy farm is 1.35 kg/s. The cooling load of a 200-cow dairy farm depends on the milk production in a day and environment temperature. The average milking performance of a dairy cow is nearly 15 L per a day, and this amount of milk should be cooled to 4 from 25
C. Normally, this application composes the cooling load of a dairy farm. The amount of manure produced by cows has a vital role for all of the operations. According to many studies, average fertilizer production is around 30 kg/day, which means that 6000 kg of manure can be produced by 200 cows on a dairy farm.

2.3 SPECIFIC SYSTEM DETAILS System 1 is a trigeneration system that utilizes the syngas as a fuel that is produced by a gasifier. This syngas is combusted with air and depends on the air-fuel ratio of syngas and air in a combustion chamber. For the gasification process, a gasifier is adapted from the study of Anthony [12]. This compares the systems with a gasifier for three different biomass types, such as cotton gin trash, beef cattle manure, and high-tonnage sorghum. The values of the biomasses have a large range of differences based on many operating and environmental parameters. Therefore, there is no drawback

2. SYSTEM DESCRIPTION

237

to using the gasification applications for beef cattle manure in this study. Another significant parameter of syngas is the LHV, which is defined as 7835 kJ/kg for syngas as produced from beef cattle manure. The syngas leaves the gasifier at 750
C, then it advances to the combustion chamber to generate energy that is required to complete three other primary processes [20]. The air that is fired with the syngas is compressed in a compressor before the combustion chamber. The compressor is connected to a turbine by a shaft. Therefore, the conversion ratio of the system is the same for the compressor and the turbine, and it is assumed as 4 based on the previous tests. The gas composition of the synthesis gas is hydrogen (7.72%  0.26%), carbon monoxide (10.92%), carbon dioxide (14.18%  0.43%), methane (4.38%  0.13%), ethane (0.43% 0.02%), and nitrogen (56.67%  1.33%) [20]. The ORC unit of the trigeneration system is designed to generate the secondary electricity from the waste heat. The ORC unit consists of an evaporator, a turbine, a condenser, and a pump. To have an efficient ORC, the working fluid in the ORC should have a high critical temperature, so that the waste heat can be used more efficiently. One of the common organic fluid types used to operate the ORC is n-octane, which has a high critical temperature, 569K [21]. The single-effect absorption chiller includes a generator, a condenser, a refrigerant expansion valve, an evaporator, an absorber, a solution pump, a solution expansion valve, and a solution heat exchanger. Unlike conventional vapor-compression systems, the absorption cooling systems use heat, supplied at the generator level, to compress the refrigerant vapor instead of a rotating device or compressor. The amount of daily milk per cow is 15 L, and the dairy farm includes 200 cows. This means that 200 cows produce 3000 L of milk, and this amount of milk should be kept at 4
C. The density of milk could possess a wide range of values, but the average value of the density is 1.014 kg/ m3. Cp is also another important parameter to calculate the cooling load of milk, and its value was estimated as 1.95 kJ/kg K [22]. The cooling load of the dairy farm should be quite a bit higher than the cooling requirement of whole milk, since the cooled storage rooms could involve many kinds of other stuffs, such as agricultural products, fodders, agricultural pesticides, fresh meats, etc. Therefore, the cooling performance of the designed chiller system should be higher than what is obviously needed (Fig. 1). System 2 involves a biomass digester to produce biogas that is used as a fuel in the system. The production of the biogas is generally completed in four consecutive stages. Instead of designing a biomass digester, using the biogas efficiency of the cow manure is a more practical method. The biogas efficiency is defined as a value that shows the average amount of biogas that could be generated from a biomass per kg. The biogas efficiency of the cow manure is 90e310, and 270 L/kg is an assumed value for this study. One of the drawbacks of the biogas production by biomass digester is operational period (time), which may take up to 40 days. Note that the operational time is not considered in the analysis, and it is assumed that the biogas production comes down to average biogas production per second. A cow may produce lower or higher than 30 kg manure in a day. It means that 200 cows can easily produce 6000 kg manure. Furthermore, when it is come down to per second, the amount of biogas per second will be 0.02196 kg/s. The average LHV of the dairy cattle is assumed as 15,304 kJ/m3 [13] (Fig. 2). The airefuel ratio of the biogas is 17.25. Therefore, the mass flow rate of the Brayton cycle is 0.3788 kg/s. The total trigeneration process is similar to systems 1 and 2, consisting of a biomass digester, a Brayton cycle, an ORC, a heat recovery system, and a single-effect absorption chiller. The biogas is transferred to the combustion chamber for combustion process with the air that comes from the compressor, which has compression ratio of 3. All parameters of the ORC and the single-effect

FIGURE 1 Schematic diagram of system 1. Combustion Chamber

Biomass

Biogas Biomass Digester

3

4

2 Compresor

Electrical Generator

Turbine

Electrical Power

10

5

Electrical Generator

1 9 6 Heat Ex.-Water

7

Condenser

T

T

T

Heat Ex.-Generator

T

T

Generator

T

13

14

19

20

Solution Heat Ex.

Refrigerant Expansion Valve

21

18 Solution Pump

15

16

FIGURE 2 Schematic diagram of system 2.

T

22 Absorber

Evaporator

T

Solution Expansion Valve

17

T

Heat Ex.-Air

11 Pump 12

T

8

Electrical Power

Turbine

Heat Ex.-ORC

2. SYSTEM DESCRIPTION

239

absorption chiller of system 1 are taken the same as for system 2 for the sake of analysis. However, some outputs could be different based on the inlet parameters depending on the inputs of fuel and air. In the processes of system 3, the LHV of the fresh cattle manure is one of the most important factors; it is adapted as 15,863 kJ/kg [23]. The dry basis of the biomass is the main part of the manure that will be used to produce energy, and 15% of the total mass can be accepted as dry. Therefore, only 15% of total cow manure is ultimately burned in the biomass burner. After the combustion process of the cow manure, the generated thermal energy (heat) should be transferred to the closed Brayton cycle through an evaporator (Fig. 3). When the heat that is produced in the biomass burner is transferred to a closed Brayton cycle, the working fluid of this cycle, it is chosen as helium, which is adapted from the study of Giovanni and Andrea [24], evaporates, and it reaches high pressure and temperature. The working principle of the closed Brayton system is similar to that of the Brayton cycle that is used in systems 1 and 2, but the main difference is that the closed Brayton cycle works with a working fluid in a loop. The mass flow rate of the helium is 0.1871 kg/s, and the mass flow rate of the 0.01,042 kg/s that depends on the production amount of cow manure per second. All parameters of the ORC and the single-effect absorption chiller of systems 1 and 2 are considered the same as for system 3. However, some outputs could be different based on the inlet parameters of the fuel and its composition.

Biomass Biomass Burner

1

4 Evaporator

Air Ash

2

3

Electrical Generator

Turbine

Compresor

Electrical Power 5

10

Electrical Generator Electrical Power

5 Turbine

Heat Ex.-ORC

8

9 Heat Ex.-Air

7

Heat Ex.-Water

6

11 Pump

12 T

T

T

Heat Ex.Generator

T

T

Condenser

T

Generator

13

14

19

20

Solution Heat Ex.

21

18 Solution Pump

16

FIGURE 3 Schematic diagram of system 3.

T

22 Absorber

Evaporator

T

Solution Expansion Valve

17

T

15

240

CHAPTER 2.2 INTEGRATED TRIGENERATION SYSTEMS FOR DAIRY FARMS

3. THERMODYNAMIC ANALYSIS Energy balance equations are examined under the first law of thermodynamics for each unit of the systems as a control volume under the steady-state operations, then, results and some significant inlet parameters are tabulated in Table 1. Some of the inlet parameters are the same for all of them as well as some output values, but the overall efficiencies and the Brayton cycle efficiencies are different as listed in Tables 2e4. Before writing of the energy balance equations, the net electrical power of each system should be defined as: W_ netbrayton ¼ W_ T;b  W_ C;b

(2)

Table 1 Input Data Systems

System 1

System 2

System 3

Mass flow rate Electrical generator efficiency Conversion ratio Turbine inlet pressure

0.1531 kg/s 95% 4 405.3 kPa

0.3788 kg/s 95% 3 303.9 kPa

0.1871 kg/s 95% 3 20000 kPa

Organic Rankine Cycle Organic cycle pump isentropic efficiency Organic cycle turbine isentropic efficiency Electrical generator efficiency Electrical motor efficiency Mass flow rate

80% 80% 80% 95% 0.24 kg/s

Single-Effect Absorption Chiller Overall heat transfer coefficient of the absorber Overall heat transfer coefficient of the condenser Overall heat transfer coefficient of the generator Overall heat transfer coefficient of the evaporator Effectiveness of solution heat exchanger

75 kW/K 80 kW/K 70 kW/K 95 kW/K 70%

Heating Water heating inlet temperature Water heating outlet temperature Air heating inlet temperature Air heating outlet temperature

283K 338K 283K 298K

Ambient Conditions Ambient pressure Ambient temperature

101.3 kPa 293K

3. THERMODYNAMIC ANALYSIS

241

where W_ is the power, and subscripts T; b and C; b indicate the turbine of the closed and open Brayton cycle and the compressor of the closed and open Brayton cycle. The net electricity generation per second is defined as: W_ nete ¼ hg  W_ netbrayton

(3)

where W_ nete is the net electrical output for Brayton cycle, and hg is the efficiency of the generator. After the calculations, the electrical efficiency of the Brayton cycle is determined as:  hbrayton ¼ W_ nete Q_in (4) where Q_in is the total heat rate that is produced in the biomass burner by utilization of the fuel. Q_in is calculated by: Q_in ¼ m_ f  LHVf

(5)

LHVf is the lower heating value of the fuel. The net electrical power of the ORC is defined as: W_ net;ORC ¼ W_ T;ORC  W_ p

(6)

where W_ is the power, and subscripts, T; ORC and p indicate turbine and pump of the ORC unit. Then, the efficiency of the ORC can be defined as:  hORC ¼ W_ net;ORC Q_in;ORC (7) where Q_in;ORC determines the amount of heat that is transferred to ORC from the Brayton cycle. Q_in;ORC can be defined as: Q_in;ORC ¼ ðm_ 6  h6  m_ 5  h5 Þ

(8)

The mass balance and energy balance equations are defined for each system. Due to similarities of the systems, most of the balance equations are the same for all systems with different input and outputs. Balance equations of system elements that are only special and different from others will be examined in this section. The equations are given with state points that are estimated in the diagrams of the systems. The energy balance equations of the compressor and turbine of the Brayton cycles are written as: W_ C;b þ m_ 1  h1 ¼ m_ 2  h2

(9)

W_ T;b þ m_ 4  h4 ¼ m_ 5  h5

(10)

where m_ 1 equals to m_ 2 and m_ 4 equals to m_ 5 because of the mass balance. The other energy and balance equations are given for the heat exchanger between the Brayton and organic Rankine cycle as: m_ 9 ¼ m_ 10

(11)

m_ 5 ¼ m_ 6

(12)

m_ 5  h5 þ m_ 9  h9 ¼ m_ 6  h6 þ m_ 10  h10

(13)

242

CHAPTER 2.2 INTEGRATED TRIGENERATION SYSTEMS FOR DAIRY FARMS

Another significant balance equation is written for heating processes. The equations of the heating processes are the same for all systems, and they are also similar for water heating and air heating. The mass and energy balance equations of the heat exchanger for air heating are given as: m_ airin ¼ m_ airout

(14)

m_ 7 ¼ m_ 8

(15)

m_ 7  h7 þ m_ air  hairin ¼ m_ 8  h8 þ m_ air  hairout

(16)

The next energy balance equation is for the turbine of the ORC unit, and it is also the same for all systems. W_ T;ORC þ m_ 10  h10 ¼ m_ 11  h11

(17)

Finally, the energy and mass balance equations are written for the generator of the single-effect absorption chiller, which has one of the complicated balance equations: m_ 19 ¼ m_ 20 þ m_ 13

(18)

h11  m_ 11 þ h19  m_ 19 ¼ h13  m_ 13 þ h20  m_ 20 þ h12  m_ 12

(19)

The overall efficiency is another important performance criterion for the systems to compare them with each other, and the overall energy efficiency of the trigeneration systems become: hoverall ¼

W_ nete þ W_ net;ORC þ Q_heating þ Q_evp Q_in

(20)

where Q_heating is the total heating load of water and air, and Q_evp is the cooling load of the system.

4. RESULTS AND DISCUSSION The performance assessments of the three trigeneration systems are undertaken through balance equations, which were introduced in the previous section, and their results are listed in Tables 2e4. The state points of the systems are defined and are given accordingly. After writing the balance equations of systems 1, 2, and 3, the efficiencies of the Brayton cycle are found to be 0.274 (27.47%) for system 1, 0.256 (25.6%) for system 2, and 0.243 (24.3%) for system 3. On the other hand, the ORC unit’s efficiencies are calculated as 0.156 (15.6%) for system 1, 0.172 (17.2%) for system 2, and 0.139 (13.9%) for system 3. Furthermore, the turbine works are 86.73 kW for system 1, 136.6 kW for system 2, and 101 kW for system 3. The net electricity generations are defined as 58.38 kW for system 1, 86.09 kW for system 2, and 31.78 kW for system 3, depending on turbine works, the compressor works, and efficiency of the generator (90%). However, the organic Rankine unit that supplies secondary electric production has 15.61% electrical efficiency for system 1, 17.19% for system 2, and 13.93% for system 3. The turbine power of the ORC is 16.72 kW, and the net electricity generation of the ORC unit is 15.05 kW for system 1, and the others are given in Table 2. The systems also consist of the two heat recovery systems for water and air heating; the amount of heat recovered for use is 30.07 kW. The coefficient of performance of the single-effect absorption chiller is 0.70 based on the cooling output. Table 2 tabulates the advantageous outputs of all systems.

4. RESULTS AND DISCUSSION

Table 2 All Outputs of the Three Systems hBrayton hORC hoverall W_ C;b ðkWÞ W_ T;b ðkWÞ W_ e ðkWÞ W_ T;ORC ðkWÞ W_ e;ORC ðkWÞ Coefficient of performance Q_heat ðkWÞ

System 1

System 2

System 3

27.37% 15.61% 84.1% 21.87 86.73 58.38 16.72 15.08 0.70

25.61% 17.19% 63.27% 40.97 136.6 86.09 20.06 18.06 0.70

24.31% 13.93% 84.4% 65.73 101 31.78 20.06 18.06 0.70

30.07

30.07

30.07

Table 3 Thermodynamic Properties of the Stations of System 1 State

m_ (kg/s)

T (K)

h (kJ/kg)

P (kPa)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

0.1531 0.1531 0.03403 0.1531 0.1531 0.1531 0.1531 0.1531 0.2 0.2 0.2 0.2 0.037 0.037 0.037 0.037 0.173 0.173 0.173 0.037 0.037 0.037

293 434.5 983 1473 992 473 422.3 314.7 365.9 549 432.9 365 336.5 307.5 278.2 494.2 303.4 303.4 332.2 365 321.9 329

293.4 436.2 e 1603 1073 475.7 423.9 315 161.3 708.5 624.9 157.5 2618 144 144 4460 67.3 67.3 128.3 244.5 168.5 168.5

101.3 405.3 e 405.3 101.3 101.3 101.3 101.3 2000 2000 35.7 35.7 5.4 5.4 0.87 0.87 0.87 5.4 5.4 5.4 5.4 0.87

243

244

CHAPTER 2.2 INTEGRATED TRIGENERATION SYSTEMS FOR DAIRY FARMS

Table 4 Thermodynamic Properties of the Stations of System 2 State

m_ (kg/s)

T (K)

h (kJ/kg)

P (kPa)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

0.3788 0.3788 0.02196 0.3788 0.3788 0.3788 0.3788 0.3788 0.24 0.24 0.24 0.24 0.037 0.037 0.037 0.037 0.173 0.173 0.173 0.037 0.037 0.037

293 434.5 e 1173 857.5 614 598.7 546.3 365.9 549 432.9 365 336.5 307.5 278.2 494.2 303.4 303.4 332.2 365 321.9 329

293.4 436.2 e 1246 885.6 623.5 599.4 548.5 161.3 708.5 624.9 157.5 2618 144 144 4460 67.3 67.3 128.3 244.5 168.5 168.5

101.3 405.3 e 405.3 101.3 101.3 101.3 101.3 2000 2000 35.7 35.7 5.4 5.4 0.87 0.87 0.87 5.4 5.4 5.4 5.4 0.87

In the next section, the output of the systems and their overall efficiencies are examined by considering some operating conditions and state properties, such as turbine inlet temperature, the daily energy consumption per cow, and outdoor temperature, and hence the changes are interpreted by using graphs showing these changes. Fig. 4 shows the percentages of outputs for total useful generations from the systems. To illustrate this for system 1, 40% of total outputs is electricity generation and heating has the lowest percentage with 17%, respectively. It easily can be seen in these pie charts that the highest proportion of electricity generation is seen in system 2 with 49%. Tables 3e5 tabulate the thermodynamic properties of the state points of all three trigeneration systems. The graph shown in Fig. 5 is presented to study the effects of the inlet temperature of the turbine on the total electricity generation and the overall system efficiency. The turbine of the Brayton cycle is chosen for analysis on this part of the study because it has an essential role in all systems. The turbines of the Brayton cycle are employed to generate mechanical work, which can be converted into electricity through the generators.

4. RESULTS AND DISCUSSION

(A)

(B)

System 1

System 2 Electricity Generation (104.1 kW)

Electricity Generation (73.43 kW) 43%

40%

37%

Heating (30.07 kW)

49%

Cooling (78.3 kW)

Cooling (78.3 kW)

14%

17%

Heating (30.07 kW)

System 3

(C)

Electricity Generation (49.83 kW) 32%

Heating (30.07 kW)

49%

Cooling (78.3 kW)

19%

FIGURE 4 The output shares of trigeneration systems: (A) System 1, (B) System 2, (C) System 3.

Table 5 Thermodynamic Properties of the Stations of System 3 State

m_ (kg/s)

T (K)

h (kJ/kg)

P (kPa)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

0.01042 0.01042 0.1871 0.1871 0.1871 0.1871 0.1871 0.1871 0.24 0.24 0.24 0.24 0.037 0.037 0.037 0.037 0.173 0.173 0.173 0.037 0.037 0.037

1273 e 447.8 651.4 550.3 506.2 456 348 365.9 549 432.9 365 336.5 307.5 278.2 494.2 303.4 303.4 332.2 365 321.9 329

e e 839.7 1894 1333 509 457.3 348.3 161.3 708.5 624.9 157.5 2618 144 144 4460 67.3 67.3 128.3 244.5 168.5 168.5

e e 20,000 20,000 7630 7630 7630 7630 2000 2000 35.7 35.7 5.4 5.4 0.87 0.87 0.87 5.4 5.4 5.4 5.4 0.87

245

CHAPTER 2.2 INTEGRATED TRIGENERATION SYSTEMS FOR DAIRY FARMS

System 1

Total Electricity Generation [kW]

250

System 3

System 2

100

200

80

150

60

100

40

50

20

Overall Energy Efficiency (%)

246

0

0 1400 1456 1511 1567 1622 1678 1733 1789 1844 1900 1100 1156 1211 1267 1322 1378 1433 1489 1544 1600 650

705 761 816

872 927

983 1039 1094 1150

T4 [K]

FIGURE 5 Effects of varying T4 on the total electricity generation and the overall efficiency.

Fig. 5 presents the effects of the turbine inlet temperature on the overall energy efficiency and total electricity generation for all systems. The bar chart indicates the change of the total electricity generation, and the line graph indicates the effect of the turbine inlet temperature on overall efficiency. It can be seen in the graph that the overall efficiency of the systems increases when the inlet temperature of the turbine (T4) rises from 1400 to 1900K for system 1, from 1100 to 1600K for system 2, and from 1100 to 1900K for system 3. Since their thermodynamic behaviors and features differ from one to another, the range of the changes is different for each system. The change of the overall energy efficiency occurs between 82.02% and almost 86% for system 1, 60.58% and nearly 73.54% for system 2, and 84.24% and 86.36% for System 3. When such impactful effects are analyzed, certain conditions and parameters are considered in a reasonable manner as constant, for example, ambient conditions, compression ratio of the closed-type Brayton cycle, heat recovery load, cooling load, and ORC unit parameters, respectively. Note that the ambient temperature of the system is assumed as 20
C for this study, but the effects of the ambient temperature on the performance are investigated in this part of the study. The ambient temperature is changed between 20 and 30
C, and it directly affects the overall efficiency because T4 (turbine inlet temperature) increases when the ambient temperature rises. The effect of the turbine inlet temperature is analyzed in a previous section, and it is clear that the total efficiency of the system increases based on the increase in the temperature of the turbine inlet. Therefore, there is no doubt that the overall effectiveness increases with an increase in the ambient temperature. On the other hand, the same graph also displays the effects of the ambient temperature on the total electricity generation (kW). As seen in the graph, the ambient temperature has a slight increasing effect on the total electricity generation.

4. RESULTS AND DISCUSSION

247

Fig. 6 illustrates the effects of varying ambient temperature (T1) on the overall efficiencies of system 1, system 2, and system 3. The change of the overall efficiency remains almost constant, and the change occurs between 83.45% and 84.74% for system 1. It can be easily seen that the effect of the ambient temperature on overall efficiency is less significant than the difference of the turbine inlet temperature. For system 2, the situation is the same with system 1; this means that the total efficiency of the system increases while the ambient temperature rises too. The change between the first and last percentages of the total efficiency of the system is almost 2%. To illustrate, it increases from 62.21% to 64.24%, when the ambient temperature rises from 283 to 303K. The reason for the ambient temperature effect is the same with system 1. If ambient temperature increases, the turbine inlet temperature rises as well. Therefore, the working fluid (air) of the Brayton cycle enters into the turbine with higher temperature and enthalpy values. The results appear to be similar to others for system 3; the efficiency of the total system rises with the increase of the ambient temperature. The change occurs from 80% to 86%, respectively. The ambient temperature may be defined as Tambient for this graph because T1 is the outlet temperature of the biomass burner. Therefore, Tambient is examined as T1 that shows the ambient temperature in systems 1 and 2. Three designed trigeneration systems utilize biomass as an energy source with different kinds of usage methods. Therefore, the amount of the manure is a significant parameter in our calculations. The total electricity generation is not the same with all amounts of manures, as it usually depends on the kilograms of manure that are produced in a day. In this section of the chapter, the effect of the total manure (that a cow can produce in a day) is analyzed to see how the overall electrical power production System 1

120

System 2

System 3

100

100

80 60

60

40 40

20 20

0

0 283 285 287 289 291 293 295 297 299 301 283 285 287 289 291 293 295 297 299 301

283 285 287 289 291 293 295 297 299 301

T1 [K]

FIGURE 6 Effects of varying T1 on the total electricity generation and the overall system efficiency.

Overall Energy Efficiency (%)

Total Electricity Generation [kW]

80

248

CHAPTER 2.2 INTEGRATED TRIGENERATION SYSTEMS FOR DAIRY FARMS

changes with the different amount of manure. The manure quantity is changed from 20 to 30 kg per day, and the effects are shown in Fig. 7. The significant point from this analysis is that the total electricity generation should be higher than the total daily electricity usage of a dairy farm. The total electricity generation increases from 53.97 to 73.43 kW for system 1, while the manure quantity that can be produced by a cow in a day changes between 20 and 30 kg. When the amount of manure rises, the amount of fuel increases as well. Therefore, the mass flow rate of the Brayton cycle expands due to the air-fuel rate of the syngas. According to the balance equation of the turbine, this increase causes a rise in the total electrical energy production of system 1. The amount of the manure directly affects the fuel rate of the system. Therefore, the situation is the same with system 1 and for both system 2 and system 3. This means that when the amount of manure increases, the mass flow rate of the Brayton cycle rises depending on the air-fuel rate of the biogas. Note that the total electrical energy generation of the system increases with the change of the manure quantity; the total electricity generation changes between 31.43 and 49.83 kW, respectively. Fig. 8 demonstrates the energy efficiency variation with the change in the compression ratio of the Brayton cycle. The effect of the compression ratio (rp) on the performance is studied for four different energy efficiencies, including efficiency of trigeneration, efficiency of cogeneration (cooling), efficiency of cogeneration (heating), and electrical efficiency. All types of efficiencies rise with the change of the compression ratio by nearly 10%, respectively. The main point in this graph is that trigeneration system is more effective than other systems. In addition, cogeneration systems that produce electricity and cooling load are the second most effective system type. Therefore it can be said that trigeneration systems appear to be more advantageous solutions for dairy farms.

FIGURE 7 Effect of the amount of manure on the total electricity generations.

5. CONCLUSIONS

249

FIGURE 8 Effect of compression ratio on different types of energy efficiencies.

5. CONCLUSIONS The current study has presented the energy analyses of three types of trigeneration systems as three cases for comparative performance assessment and evaluation. In this regard, three unique systems were developed for this purpose. System 1 consists of a gasifier, an open-type Brayton cycle, an organic Rankine cycle, a single-effect absorption chiller, and a heat recovery subsystem. System 2 consists of a biomass decomposer, an open-type Brayton cycle, an organic Rankine cycle, a single-effect absorption chiller, and a heat recovery subsystem. System 3 consists of a biomass burner, a closed-type Brayton cycle, an organic Rankine cycle, a single-effect absorption chiller, and a heat recovery subsystem. These three trigeneration systems aim to generate electrical power, heat, and cooling for meeting the demands of a dairy farm. Furthermore, the main concluding remarks from this study are: •

•

•

• •

Turbine inlet temperature has an increasing effect on the total electricity generation and hence the overall efficiency. The best turbine inlet temperatures for all three systems are obtained at 1900K for system 1, 1600K for system 2, and 900K for system 3, respectively. The system efficiency can be increased by the rise of ambient temperature; 30
C was studied as the most effective ambient temperature for all three systems: 84.74% for system 1, 64.24% for system 2, and 86% for system 3. The effects of compression ratio on four different types of efficiencies (namely efficiency of trigeneration, efficiency of cogeneration (cooling), efficiency of cogeneration (heating), and electrical efficiency) were studied. The amount of daily manure per cow has a vital role on the net electricity generation of three systems. As the amount of fertilizer increases, the amount of electricity generated increases. Each system can be operated for a dairy farm that has livestock in necessary numbers, since the significant role of the amount of manure’s effect was studied. This amount was based on a farm’s

250

•

CHAPTER 2.2 INTEGRATED TRIGENERATION SYSTEMS FOR DAIRY FARMS

needs and manure quality of animals. According to results of this study, these three systems can be used for a dairy farm that has 200 cows. System 1 appears to be the most effective system for a dairy farm because of its practical fuel production processes, high electricity generation, and efficiencies, among three systems.

NOMENCLATURE h m_ P Q_ T W_

Enthalpy per unit mass, kJ/kg Mass flow rate, kg/s Pressure, kPa Heat rate, kW Temperature, K,
C Power, kW

Acronyms CCHP COP ENDFH ICE LHV ORC

Combined cooling, heating, and power Coefficient of performance Energy need for a 200-cow dairy farm per hour Internal combustion engine Lower heating value, kJ/kg Organic Rankine cycle

Greek Letters h

Efficiency

Subscripts

abs air,in air,out C; B co e; ORC evp f g heating in net,brayton net,e net,ORC p T; b T; ORC vol

Absorber Inlet air Outlet air Compressor of the Brayton Cycle Condenser Electricity generation ORC Evaporator Fuel Generator Heating load Inlet Net power of the Brayton cycle Net electrical generation of the Brayton cycle Net electrical generation of the ORC Pump Turbine of the Brayton cycle Turbine of ORC Volume

REFERENCES

251

REFERENCES [1] Clarke S. Using less energy on dairy farms. Queen’s Printer for Ontario; 2010. [2] College of Agricultural and Life Sciences e University of Wisconsin. Wisconsin energy efficiency and renewable energy resource; 2017. [3] Murgia L, Caria M, Pazzona A. Energy use and management in dairy farms. In: International conference: Innovation technology to empower safety, health and welfare in agriculture and agro-food systems; 2008. [4] Huicochea A, Rivera W, Gutie´rrez-Urueta G, Bruno JC, Coronas A. Thermodynamic analysis of a trigeneration system consisting of a microgasturbine and a double effect absorption chiller. Applied Thermal Engineering 2011;31. [5] Ge YT, Tassou SA, Chaer I, Suguartha N. Performance evaluation of a trigeneration system with simulation and experiment. Applied Energy 2009;86. [6] Sun ZG, Zie NL. Experimental studying of a small combined cold and power system driven by a micro gas turbine. Applied Thermal Engineering 2010;30. [7] Moran A, Mago PJ, Chamra LM. Thermoeconomic modeling of micro-CHP (micro-cooling, heating, and power) for small commercial applications. International Journal of Energy Research 2008. http://dx.doi.org/ 10.1002/er.1395. [8] Maidment GG, Zhao X, Riffat SB, Prosser G. Application of combined heat and power and absorption cooling in a supermarket. Applied Energy 1999;63. [9] Tracy T, Ordonez JC, Vargas JVC. First and second law thermodynamic analysis of a domestic scale trigeneration system. In: Proc ASME conference on energy sustainability, Long Beach, California, USA. June 27e30, 2007; 2007. [10] Ebrahimi M, Keshavarz A, Jamali A. Energy and exergy analyses of a microsteam CCHP cycle for a residential building. Energy and Buildings 2012;45. [11] Lian ZT, Chua KJ, Chou SK. A thermoeconomic analysis of biomass energy for trigeneration. Applied Energy 2010;87. [12] Anthony B. The technical and economic feasibility of biomass gasification for power generation. Birmingham (UK): Energy Research Group, Aston University; July 26, 1994. [13] Huang J, Crookes RJ. Assessment of simulated biogas as a fuel for the spark ignition engine. Fuel 1998;77. [14] Miro RS, Peter L, Sohif BM. Biomass energy utilization & environment protection e commercial reality and outlook. In: Power-gen Asia; 2003. [15] Wang J, Yan Z, Wang M, Song Y, Dai Y. Parametric analysis and optimization of a building cooling heating power system driven by solar energy based on organic working fluid. International Journal of Energy Research 2013. http://dx.doi.org/10.1002/er.2952. [16] Muhyiddine J, Saffa R. Tri-generation systems: Energy policies, prime movers, cooling technologies, configuration sand operation strategies. Elsevier; January 4, 2014. [17] Al-Sulaiman FA, Ibrahim D, Feridun H. Energy and exergy analyses of a biomass trigeneration system using an organic Rankine cycle. The International Journal 2012:975e95. [18] Joseph PH, Brouk MJ, Bradford JPB, Smith JF. Scientific data for developing water budgets on a dairy. Western dairy management conference; 2013. [19] Thomas CV. Estimating water usage on Michigan Dairy Farms (1,000 head). Michigan State University Extension; 2001. [20] Maglinao Jr AL, Capareda SC, Nam H. Fluidized bed gasification of high tonnage sorghum, cotton gin trash and beef cattle manure: evaluation of synthesis gas production. Energy Conversion and Management 2015;105. [21] Casten T. District energy with trigenerated ammonia cooling. ASHRAE Transactions 1994:1136.

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[22] Yunus C, Michael AB. Instructor solutions manual for thermodynamics: An engineering approach. 8th ed. McGraw-Hill Education; 2015. [23] Lijun W, Abolghasem S, Milford AH. Characterization of corn stover, distiller grains and cattle manure for thermochemical conversion. Biomass and Bioenergy 2010;35. [24] Giovanni M, Andrea L. Innovative biomass to power conversion systems based on cascaded supercritical CO2 Brayton cycles. Biomass and Bioenergy 2014;69.

CHAPTER

PERFORMANCE ASSESSMENT OF A BIOMASS-FIRED REGENERATIVE ORC SYSTEM THROUGH ENERGY AND EXERGY ANALYSES

2.3

Ozum Calli1, C. Ozgur Colpan2, Huseyin Gunerhan3 _ Izmir University of Economics, Izmir, Turkey ; Dokuz Eylul University, Izmir, Turkey2; Ege University, Izmir, Turkey3 1

1. INTRODUCTION As the human population increases and technological devices advance, the demand for energy continues to increase significantly. In this regard, converting energy resources efficiently and economically into useful forms of energy is an important issue. Depending on the conditions of the energy resource, this energy conversion can be done through thermal or electrochemical methods. Among the methods of thermal energy conversion, organic Rankine cycles (ORCs) represent an attractive solution to use energy resources with low and medium enthalpy values. The principle of electricity generation by means of an ORC is similar to the conventional Rankine cycle. The difference between these two cycles is that an organic working fluid (e.g., R134a, R245fa, and R123, and hydrocarbons such as butane, isopentane, and isooctane) with favorable thermodynamic properties at lower temperatures and pressures is used instead of water in the ORC [1e6]. ORC has been investigated extensively in the literature. The most well-investigated parameter is the working fluid, which depends on the design and operating conditions of the cycle [4,7e9]. Lakew et al. [10] investigated different working fluids for power production under different operating conditions and heat sources with different temperatures for a subcritical Rankine cycle. Their study showed that R227ea gives the highest power for a heat source temperature range of 80e160
C and R245fa produces the highest power in the range of 160e200
C. The main components of the ORC are the expander and the heat exchanger. The selection of expander is important in terms of both energy and cost issues in the ORC. In general, expanders can be divided into two types: velocity, such as axial turbine expanders, and volume, such as screw expanders and scroll expanders. Turbine expanders are generally applied in power cycles with higher power outputs (greater than 50 kWe), because in high power ratings, they perform with relatively highexpansion efficiency [11]. Below 50 kWe, the performance of turbine expanders becomes worse as low values of efficiencies are obtained. Moreover, small-scale turbine expanders are generally expensive. The scroll expander has the most complicated geometry [12]. Scrolls can be divided into Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00015-9 Copyright © 2018 Elsevier Inc. All rights reserved.

253

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CHAPTER 2.3 BIOMASS-FIRED REGENERATIVE ORC SYSTEM

two classes: compliant and kinematically constrained. Compliant scrolls require lubrication to operate efficiently without causing significant wear, whereas constrained scrolls can operate without lubrication. Another advantage of this device is that it does not require inlet or exhaust valves, which reduces noise and improves the durability of the unit; furthermore, the relative rolling motion of the contact points offer less resistance than sliding friction [13]. Screw expanders have been widely used in ORC, especially for geothermal and waste heat applications. Screw expanders are appropriate above 10 kWe power generation systems because leakage problems can occur in small-scale screw expanders, which affects the isentropic efficiency negatively. The design and selection of heat exchangers have significance because they affect the performance of the ORC. In ORCs, as shown in Fig. 1, two types of heat exchangers are generally used as an evaporator: condenser or regenerator. These are of the shell and tube type and plate type. Shell- and tube-type heat exchangers are built of tubes mounted in large cylindrical, rectangular, or arbitrarily shaped shells. Shell and tube heat exchangers are one of the most commonly used exchanger type owing to their availability for a wide range of pressures and temperatures, whereas ORCs with platetype heat exchanger are usually limited to a fluid stream with a pressure below 25 bar and a temperature below 250
C. Hence, the flow passages are small in plate heat exchangers, which provides high heat transfer coefficients and but also high pressure drops. On the other hand, compared with shell and tube heat exchangers, plate heat exchangers have a high construction cost [14]. There are many applications of ORCs, such as geothermal, solar, waste heat, and biomass. These applications are discussed in the following section. The aim of this chapter was to determine to what extent which parameters affected the energetic and exergetic performances of the regenerative biomass-fired ORC. Energy and exergy analyses were applied on the basis of both the entire system and smaller control volumes. Some suggestions are given for decreasing exergy destruction.

FIGURE 1 Schematic of (A) a shell and tube heat exchanger [15] and (B) a plate heat exchanger [14].

1. INTRODUCTION

255

1.1 ENERGY RESOURCES OF THE ORGANIC RANKINE CYCLE 1.1.1 Geothermal Applications Geothermal-powered ORC converts low-temperature geothermal energy into electricity. Geothermal water is drawn from deep in the earth to the ground and then it transfers its heat to the working fluid of the ORC to generate power [16]. There are some studies on geothermal-based ORC systems in the literature. Sakhrieh et al. [17] optimized the operating parameters of a geothermal-powered ORC system for six different hydrocarbon working fluids and found that the maximum power is produced when R600a is used for geothermal water inlet temperatures higher than 120
C and reinjection temperatures not less than 70
C. Bombarda et al. [18] compared a Kalina cycle and ORC-based geothermal system and found that the Kalina cycle has 17.8% lower levelized electricity costs compared with the ORC for an enhanced geothermal system working at 100
C and 200 kg/s. Sauret et al. [19] modeled a solar-based ORC and found that R134a produces 33% more net power than n-pentane for a 150
C and 10-kg/s hot source. Exploitation of a medium-temperature geothermal resource with ORCecombined heat and power (CHP) was investigated in a study by Fiaschi et al. [20]. They investigated a medium-temperature (up to 170
C) geothermal resource with ORCeCHP and found that it produced higher power (almost 55% more) compared a lowtemperature geothermal resource. In addition, they found that optimal working fluids varied with the characteristics of the heat demand. Liu et al. [21] found that condensation and reinjection temperature were the most important parameters for the performance optimization of ORC. They suggested that ORC using geothermal water be between 100 and 150
C and reinjection temperatures not be less than 70
C.

1.1.2 Solar Applications Solar power systems have been implemented with a variety of collector technologies such as the parabolic trough collector and flat plate collector [22]. Parabolic trough collectors concentrate sunlight into a receiver tube located along the focal line of the trough and a fluid flows along the tubes of the parabolic through collectors to transfer heat to the ORC. Parabolic trough collectors provide high temperatures more efficiently than do flat-plate collectors because the absorption surface area is smaller [23]. For instance, Al-Sulaiman [24] conducted an exergy analysis of a combined steam Rankine cycle and ORC, both of which are integrated with parabolic trough solar collectors. As a result of the study, it was found that the main source of exergy destruction was the solar collector. In addition, it was shown that as solar irradiation increased, exergetic efficiency increased. The highest and lowest exergetic efficiencies were obtained when R134a (26%) and R600 (20%), respectively, were used as the working fluid in the combined cycle. Tchance et al. [5] found that the best performance for a solar-based ORC was obtained with R134a. R134a was followed by R152a, R600, R600a, and R290 for low-temperature applications in which the temperature of the heat source was below 90
C. R152a, R600a, R600, and R290 were shown to have attractive performances but they needed safety precautions owing to their flammability. Baral et al. [25] studied solar-based ORCs operating with 15 different working fluids. R134a and R245fa were found to be the most appropriate working fluids for low- and medium-temperature solar ORC cogeneration systems, respectively.

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CHAPTER 2.3 BIOMASS-FIRED REGENERATIVE ORC SYSTEM

1.1.3 Waste Heat Applications Waste heat recovery is an economic method for increasing the overall efficiency of a plant. The lowgrade energy in the exhaust flue gas can be recovered and used to generate electric power. Over the past 2 decades, there has been considerable attention to the use of heat from exhaust gases for various applications and the optimization of units used to absorb heat from waste flue gases [26]. ORC can be used to recover waste heat and increase the overall system efficiency. Some industrial processes that produce enough waste heat to generate electricity in an ORC are [27,28]: • • • • • •

iron and steel industry cement and building material industry food and beverage processing industry pulp and paper industry chemical industry petroleum industry

In the literature, there are numerical and experimental studies on ORCs using waste heat sources. For example, Zhoua et al. [29] conducted an experimental study on ORC for waste heat recovery from low-temperature flue gas. The researchers found that heat recovery efficiency, expander output power, and exergetic efficiency increased with the heat source temperature. Larjola [30] investigated an ORC for waste heat recovery using a high-speed oil-free turbogenerator-feed pump. The conventional ORC turbine drives a standard generator by a high-speed gearbox. However, in this system, the turbine, pump, and electric machine are always directly linked and there is no gearbox. They found that small power outputs can be obtained with good efficiency, and because of the hermetic design, there is no leakage of process fluid.

1.1.4 Biomass Applications Biomass is an energy resource derived from organic matter. Examples of biomass are wood, agricultural waste, and municipal solid waste [31]. Biomass is a renewable energy resource that is available nearly everywhere. There are many biomass conversion technologies such as combustion, pyrolysis, and gasification. The combustion reaction of biomass with air forms mainly water and carbon dioxide at high temperatures. In the pyrolysis method, biomass is converted into liquid, solids, and gas by heating the biomass to around 500
C in the absence of air [32,33]. Gasification is the conversion of biomass into a combustible gas mixture by the partial oxidation of biomass at high temperatures. There are a few studies on biomass-fired ORC systems in the literature. For example, Liu et al. [34] investigated a 2-kWe biomass-fired CHP system based on an ORC using three different environmentally friendly refrigerants, namely HFE7000, HFE7100, and n-pentane, as the ORC working fluids. They found that the electrical efficiency of the CHP system mainly depended on the temperature of the hot water entering the biomass boiler and the temperature of the cooling water entering and exiting the ORC condenser, as well as the type of the ORC fluid. In another study by the same research group [35], a 0.8-kWe biomass-fired CHP system was investigated experimentally; the electricity generation efficiency was 1.41%, which was lower than that predicted by the thermodynamic modeling. With an evaporator temperature of 120
C, the thermodynamic modeling study gave an electrical efficiency in the range of 8e9%. Two significant factors cause the apparent difference in the electrical generation efficiency between the experiments and the thermodynamic model: The first is

2. SYSTEM DESCRIPTION

257

the expander efficiency. In the model, the value of this efficiency is assumed to be 85%, whereas the experimental results show this efficiency to be only 53.92%. The second is the alternator efficiency. In the model, it is assumed that this efficiency is 90% but the experimental results indicate that it is only 50.94%. Huang et al. [36] investigated regenerative and nonregenerative biomass ORC with dry and wet working fluids and found that the highest electric power was obtained for the regenerative system with methylcyclohexane used as the “dry” working fluid.

2. SYSTEM DESCRIPTION Fig. 2 shows a schematic diagram of the regenerative biomass-fired ORC system examined in this study. The system can be divided into two sections: the biomass side and the ORC cycle. On the biomass side, biomass fuel and air enter the burner; as a result of the combustion process, heat is generated. This heat is transferred to the biomass side working fluid. The working fluid on the biomass side then enters the heat exchanger that connects the biomass side and the ORC. In the ORC, the organic fluid first gets the heat from the biomass side through the heat exchanger. This fluid then expands in the turbine, producing mechanical energy, which is further transformed into electric energy through a generator. The fluid expanded in the turbine enters the regenerator, which is used to increase the electrical efficiency of the ORC. The exit of the regenerator enters the condenser and pump consecutively before reentering the regenerator. The regenerator increases the heat exchanger inlet temperature and decreases the heat gained from the burner. The fluid leaving the regenerator enters the heat exchanger, completing the cycle.

FIGURE 2 Schematic diagram of a regenerative biomass-fired organic Rankine cycle system.

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CHAPTER 2.3 BIOMASS-FIRED REGENERATIVE ORC SYSTEM

3. MATHEMATICAL MODEL The mathematical model of the integrated biomass-fired ORC system was developed using energy and exergy analyses, which are discussed in the following subsections. Commercially available software, Engineering Equation Solver (EES), was used to solve the equations. The main assumptions made to carry out the energy and exergy analyses of the ORC system were: • • • • •

The system is assumed to work at steady state. The pressure drops along the components and the lines connecting the components are neglected except in the pump and ORC turbine. The heat loss from the components to the surroundings is neglected. The kinetic and potential energy and exergy changes are neglected. Air and the combustion gases are assumed to be ideal gases and the biomass-side fluid (thermal oil) is assumed to be an incompressible fluid.

3.1 ENERGY ANALYSIS This subsection presents the energy analysis of the system. Energy balance for steady-state control volumes can be shown as:    X X  v2 v2 Q_cv  W_ cv ¼ n_o $ h þ þ g$z  n_i $ h þ þ g$z (1) 2 2 o i where Q_cv and W_ cv are the heat transfer rate and power rate of the control volume, respectively, and n_i n_o are the molar flow rate of the working fluid at the inlet and outlet of the control volume, respectively. In this study, the molar unit system is selected for convenience because some of the modeling equations are written as a function of the molar compositions of the chemical species. Hence, most of the equations given in this study are indicated according to the molar unit system. v, g, and z denote the velocity, gravitational acceleration, and elevation, respectively, according to a reference point. In the burner, a combustion process occurs in which air and biomass fuel react. The combustion gases are emitted into the atmosphere. The chemical reaction for the combustion of biomass, which mainly consists of C, H, and O atoms, can be shown as follows: Cx Hy Oz þ ðl$g ÞðO2 þ 3:76N2 Þ/xCO2 þ ðy=2ÞH2 O þ ða$gÞO2 þ ð3:76$l$gÞN2

(2)

In this equation, l and a denote the theoretical air and excess air coefficients, respectively. g is the stoichiometric air coefficient for the complete burning reaction of CxHyOz when there is no excess air. The relation between the excess air coefficient and the theoretical air can be shown as: a¼l1¼lþ

2z  4x  y 4g

(3)

Energy balance for the burner can be shown as:

  n_air $hair þ n_biomass $hbiomass ¼ n_excess gases $hexcess gases þ n_biomass fluid $ houtlet  hinlet

(4)

3. MATHEMATICAL MODEL

259

Energy balance around the control volume enclosing the heat exchanger that connects the biomass side with the ORC is:     n_biomass fluid $ h4  h5 ¼ n_ORC fluid $ h7  h6 (5) Energy balance for the regenerator can be written in a similar way using Eq. (1). Using the energy balance for the condenser, the heat transfer rate from the condenser to the cooling water can be shown as:     Q_condenser ¼ n_ORC fluid $ h8  h9 ¼ n_cw $ h11  h10 (6) Applying the energy balance for the control volumes enclosing the turbine and pump, the power output of the turbine (Eq. 7) and the power input to the pump (Eq. 8), respectively, can be found. In these equations, hs,t denote the isentropic efficiency of the turbine, which can be defined as the actual work output of the turbine to the work output of the turbine if the turbine undergoes an isentropic process. hs,p is the isentropic efficiency of the pump, which is the ratio of the work input, for an isentropic process, to the work input for the actual process:   W_ turbine ¼ hs;t h7  h8;s (7)   h11;s  h10 y7 ðP11  P10 Þ W_ pump ¼ ¼ (8) hs;p hs;p

3.2 EXERGY ANALYSIS An exergy analysis is generally used to quantify the magnitudes of the irreversibilities in the thermal energy systems. Exergy balance, which is derived by combining the energy and entropy balances, is applied to the components of the system to find the exergy flow rates at each state and the exergy destruction of each component. Exergy destruction can also be regarded as the potential work lost owing to irreversibilities. At steady-state conditions, the exergy destruction rate of a control volume can be found by applying the exergy balance for a control volume: ! X X X T 0 _ d¼ _ _ Ex ðn$exÞ ðn$exÞ (9) $Q_j  W_ cv þ 1 i o Tj _ Ex, _ and Ex _ d are the molar flow rate, temperature of the boundary where heat transfer where n,_ Tj, T0, Q, occurs, temperature of the environment, heat transfer rate between the control volume and the environment, exergy flow rate, and rate of exergy destruction. The summation of the exergy destruction rate of the each component is called the total exergy destruction of the system. The contribution of the exergy destruction of each component in the total exergy destruction rate can be found by calculating the exergy destruction ratio: y1;i ¼

_ d;i Ex _ Exd;total

(10)

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CHAPTER 2.3 BIOMASS-FIRED REGENERATIVE ORC SYSTEM

_ d;i and Ex _ d;total denote the exergy destruction rate of the component i and the total exergy where Ex destruction of the system. Alternatively, the exergy destruction rate of a component can be compared with the chemical exergy rate of the fuel (Colpan, 2005), which is taken as the biomass for this study: y2;i ¼

_ d;i Ex _ Exbiomass

(11)

_ d;i denote the exergy flow rate of the fuel and the exergy destruction rate of the _ biomass and Ex where Ex component i, respectively. The exergy includes the physical and chemical exergy, if the kinetic and potential exergies are neglected: ex ¼ ex ch þ ex ph exph

(12)

exch

where is the specific physical exergy and is the specific chemical exergy at a given state. In general, if the chemical composition of a substance does not change at the inlets or exits of a control volume, the chemical exergy does not need to be calculated to find the exergy destruction in that control volume. For the system studied, chemical exergy is included in the calculations only in the burner because the chemical reaction takes place in the combustion process. The physical flow exergy rate at a given state is defined as:   ex ph ¼ h  h0  T0 ðs  s0 Þ (13) where h and s are the specific enthalpy on a molar basis and specific entropy on a molar basis. s0 and h0 denote the specific enthalpy and specific entropy on a molar basis for the dead state, which defines the conditions of the reference environment in this study. The specific chemical exergy of an ideal gas mixture is defined as [37]: X X ex ch ¼ exoch þ R$To $ln xi (14) Here, xi is the molar fraction of species i and ex ch o is the standard specific chemical exergy (on a molar basis) at the reference temperature and pressure. The chemical exergy of biomass can be defined as [37]:    _ biomass ¼ b$ n_biomass $ LHV biomass þ w$hfg (15) Ex         H O H 1:044 þ 0:016$  0:3493$ $ 1 þ 0:0531$ C C C    b¼ (16) O 1  0:4124$ C where n_biomass is the molar flow rate of the biomass, w is the percentage of moisture in the biomass, hfg is the molar specific enthalpy of vaporization of water, and LHV biomass is the molar lower heating value of the biomass. C, H, O, and S denote the dry-biomass weight percentages of carbon, oxygen, hydrogen, and sulfur.

3. MATHEMATICAL MODEL

261

3.3 PERFORMANCE ASSESSMENT PARAMETERS As a result of the energy analysis of the integrated system, the heat input to the burner and ORC, the net power output of the system, the heat transferred to ORC, and the electrical efficiency of the ORC and the entire system can be found using Eqs. (17)e(20), respectively. Q_burner ¼ n_biomass $LHV biomass

Q_ORC; in

W_ net ¼ W_ turbine  W_ pump     ¼ n_ORC; fluid $ h4  h3 ¼ n_bio; fluid $ h1  h2 hel; ORC ¼

W_ net

Q_ORC; in

(17) (18) (19) (20)

where n_ORC; fluid and n_bio; fluid denote the working fluid circulating throughout the ORC and the fluid providing the heat transfer from the biomass side to the ORC. The lower heating value of the biomass can be calculated knowing the higher heating value of the biomass, as shown in Eq. (21): LHV biomass ¼ HHV biomass ehfg

(21)

According to Dulong’s formula (Cho et al., 1995), the higher heating value of the biomass is a function of the dry-biomass weight percentages of carbon, oxygen, hydrogen, and sulfur, as shown in Eq. (22): HHV biomass ¼ 338:3$C þ 1442$ðH  O=8Þ þ 94:2

(22)

The exergy efficiency is defined as the ratio of the rate of desired exergy outputs to the rate of exergy inputs expended to generate these outputs. Exergy efficiency is defined differently for each component as they have different working principles. For a pump: ex11  ex10 win

(23)

wout ex7  ex8

(24)

n_ORC; fluid $ðex7  ex6 Þ n_bio; fluid $ðex4  ex5 Þ

(25)

ðex6  ex11 Þ ðex8  ex9 Þ

(26)

hex; pump ¼ For a turbine: hex;tur ¼ For a heat exchanger: hex; HX ¼ For a regenerator: hex; reg ¼

262

CHAPTER 2.3 BIOMASS-FIRED REGENERATIVE ORC SYSTEM

For the ORC and entire system, exergy efficiencies can be found using Eqs. (27) and (28), respectively: W_ net _ biomass Ex

(27)

W_ net n_biomass fluid $ðex4  ex5 Þ

(28)

hex; system ¼ hex; ORC ¼

4. RESULTS AND DISCUSSION 4.1 VALIDATION A computer code was developed for the modeling equations presented in Section 3 using EES software. As a case study, the code was run considering the experimental data from a laboratory-scale ORC unit given in a study found in the literature [38], as shown in Table 1. The results of the code were compared with those of the experiment to validate the model. The results of this comparison are given in Table 2. As can be seen in the table, the deviation between the numerical and experimental studies is less than 5%.

4.2 PARAMETRIC STUDIES After the model was validated, the effects on the performance of the system of some important input parameters were investigated. These parameters included the turbine inlet temperature, the excess air ratio, the mass flow rate of the dry biomass, and the biomass types. The baseline conditions used are given in Table 3. With these data, the results that give all of the thermodynamic properties of each state within the system are listed in Table 4.

Table 1 Data Taken From Experimental Laboratory-Scale Organic Rankine Cycle (ORC) Unit Parameter

Value

Type of working fluid in ORC Type of heat transfer fluid Mass flow rate of the working fluid in ORC ðm_ ORC Þ Regenerator inlet pressure (P5) Turbine inlet temperature (T4) Heat exchanger pressure at ORC side (P3) Outlet temperature of heat transfer fluid (T2) Inlet temperature of cooling water (T9) Temperature difference between inlet and outlet of cooling water stream (T10  T9) Heat transferred to ORC side

R245fa Therminol 66 0.3 kg/s 171 kPa 372.3K 931 kPa 383K 294.7K 3.7K 61.78 kW

4. RESULTS AND DISCUSSION

Table 2 Comparison Between Experimental and Numerical Results

Output power   of turbine W_ T Heat exchanger inlet temperature at ORC side (T3) Regenerator outlet temperature (T6)

Experimental Value

Numerical Value

Deviation Rate (%)

4.7 kW

4.9 kW

4

334.3K

329.6K

1

302.2K

303.7K

0.4

Table 3 Baseline Conditions Used in Parametric Studies Parameter

Value

Burner Type of fuel Chemical composition of fuel Mass flow rate of dry biomass Temperature of exhaust gases Excess air coefficient

Wood CH1.44O0.66 0.004 kg/s 400K 0.2

Heat Transfer Fluid Type of heat transfer fluid Mass flow rate of heat transfer fluid Pressure of heat transfer fluid Temperature of heat transfer fluid entering the heat exchanger

Therminol VP-1 0.5 kg/s 780 kPa 673K

ORC Type of working fluid in ORC Mass flow rate of working fluid in ORC ðm_ ORC Þ Pressure of working fluid entering heat exchanger (P3) Condenser pressure (P5) Turbine inlet temperature (T4) Temperature difference between inlet and outlet of cooling water stream (T10  T9) Isentropic efficiency of turbine Isentropic efficiency of pump Ambient temperature Ambient pressure

R134a 0.3 kg/s 3300 kPa 700 kPa 473K 10K 0.68 0.8 298K 100 kPa

263

264

CHAPTER 2.3 BIOMASS-FIRED REGENERATIVE ORC SYSTEM

Table 4 Thermodynamic Properties of Each State of Integrated Organic Rankine Cycle System State

Substance

T (K)

P (kPa)

h (kJ/kmol)

s (kJ/ kmol K)

n_ (kmol/s)

exph (kJ/kmol)

1

Therminol VP-1 Therminol VP-1 R134a R134a R134a R134a R134a R134a Water Water

673

780

133,004

283.3

0.003012

48,639

624.3

780

112,493

251.6

0.003012

37,553

299.8 371.6 308.7 308.6 299.8 299.8 288 298

3300 3300 700 700 700 3300 100 100

9,072 30,084 27,968 27,960 9,062 9,063 1,124 1,877

33.2 93.63 96.91 96.88 33.91 33.18 4 6.572

0.00294 0.00294 0.00294 0.00294 0.00294 0.00294 0.07373 0.07373

4,607 7,611 4,519 4,519 4,389 4,607 12.93 0

2 3 4 5 6 7 8 9 10

4.2.1 Variation of Turbine Inlet Temperature The turbine inlet temperature (TIT) is an important operating parameter that affects the performance of the integrated system. The effect of the TIT on the electrical and exergy efficiencies were investigated; the results are shown in Fig. 3A. As the TIT increased, the net power output increased. As a result, the electrical and exergy efficiencies increased. Because heat transferred to the ORC is not a function of the TIT for this study, as shown in Fig. 3B, the trend of the electrical and exergetic efficiencies mainly depended on that of the net power output. To understand the reason for the trend of the change in exergy efficiency of the overall system shown in Fig. 3A, the exergy destruction rates and efficiencies of each component of the system were calculated. In this way, the components that had the highest exergy destruction rate (i.e., irreversibility rate) and lowest exergetic efficiency were found. Hence, the components that had more potential to improve the performance of the overall system were identified. Figs. 4 and 5 show that the main reason for the increase in exergy efficiency with an increase in TIT was the comparatively higher increase in the exergy efficiency of the heat exchanger or decrease in the exergy destruction rate. It can be seen from these figures that for this component, as the temperature increased from 377 to 470K, the exergy destruction rate decreased by 25%. This decrease can be attributed to the increase in the change of the molar-specific exergy change of the working fluid between the inlet and outlet of the heat exchanger. The exergy destruction rate decrease in the condenser was the second significant reason for the increase in the exergetic performance of the overall system. The exergy destruction rate in this component mainly decreased because of the decrease in the heat transfer rate from the working fluid to the cooling water (i.e., the enthalpy of state 6 decreased whereas the enthalpy of state 7 did not change with the turbine inlet temperature). On the other hand, these figures show that the exergy destruction rate of the regenerator and the turbine increased from 0.2428 to 1.836 kW and from 2.97 to 3.5 kW, respectively, in this temperature range. Although there was an increase in the exergy destruction rate in these components, the exergy efficiency of the overall system increased as the total exergy destruction rate decreased more than total exergy destruction rate increased. The exergy

4. RESULTS AND DISCUSSION

265

FIGURE 3 Change in (A) efficiency (Eff.) and (B) energy transfer with the turbine inlet temperature. ORC, organic Rankine cycle.

266

CHAPTER 2.3 BIOMASS-FIRED REGENERATIVE ORC SYSTEM

0.9 0.8

Exergy Efficiency

0.7 0.6 0.5 0.4 Heat Exchanger Turbine Pump Regenerator Burner

0.3 0.2 0.1 0 370

390

410

430

450

470

Turbine Inlet Temperature (K)

FIGURE 4 Change in exergy efficiency with the turbine inlet temperature.

destruction rate and exergy efficiency of the pump and burner did not change because the inlet and outlet conditions of their control volumes did not change with respect to the turbine inlet temperature in this study; hence these components do not have an effect on the exergetic performance of the integrated system.

4.2.2 Variations in Excess Air Ratio A combustion process is complete if all of the carbon, hydrogen, and sulfur (if any) in the fuel burns to become CO2, H2O, and SO2, respectively. The minimum amount of air that allows the complete combustion of the fuel is called stoichiometric air. In this case, the products contain no oxygen. In practice, any additional amount of air, which is called excess air, is fed into the burner. This excess air results in oxygen appearing in the products. Excess air also increases turbulence, which increases mixing in the combustion chamber. Because there is more mixing of the air and fuel, these components have more of a chance to react. Hence, excess air prevents the fuel from remaining unburned. On the other hand, supplying more than theoretical air provides safety. To ensure complete safety, it is essential to control the levels of CO and check the amount of unburned hydrocarbon fuel. CO is a toxic gas that can be lethal at higher concentrations. Hydrocarbons that contains unburned fuel can cause explosions. The addition of excess air greatly lowers the formation of CO and unburned hydrocarbons by allowing them to react with O2. A high excess air ratio also reduces air pollution. Because toxic compounds such as sulfur dioxide, carbon monoxide, and nitrogen oxides can occur at high concentrations, smog, acid rain, and respiratory problems can occur [39]. An excess air ratio was an important parameter affecting the performance of the system studied. In this study, the effects of this ratio on the energy and exergy efficiencies of the integrated system, and the exergy efficiency and exergy destruction of each component were examined. Fig. 6A shows that the electrical and exergy efficiencies of the ORC increased with an increase in the excess air ratio. This increase can be explained as follows. Heat transferred to ORC decreased at higher excess air ratios. As

4. RESULTS AND DISCUSSION

(A)

267

1 0.9 0.8

Exergy Destrucon Rao

0.7 0.6 0.5

Burner

0.4

Heat Exchanger

0.3 0.2 0.1 0 370

390

410 430 Turbine Inlet Temperature (K)

450

470

(B) 0.06

Exergy Destrucon Rao

0.05 Turbine Condenser Pump Regenerator

0.04 0.03 0.02 0.01

0 370

390

410

430

450

470

Turbine Inlet Temperature (K) FIGURE 5 Change in exergy destruction ratio of (A) heat exchanger and burner, and (B) pump, turbine, condenser, and regenerator with the turbine inlet temperature.

the excess air ratio increased, the enthalpy of state 2 increased whereas the enthalpy of state 1 did not change. When energy balance was applied to the control volume enclosing the heat exchanger, it is clearly seen that the enthalpy of state 3 (heat exchanger inlet of the ORC side) increased whereas the enthalpy of state 4 (turbine inlet) did not change. Because the net power output did not change with the excess air ratio, both the electrical and exergy efficiencies of the ORC increased. The decreases in

268

CHAPTER 2.3 BIOMASS-FIRED REGENERATIVE ORC SYSTEM

(A)

0.35 0.3

Efficiency

0.25 0.2 0.15 0.1

Electrical Eff -System Electrical Eff -ORC Exergy Eff. -System Exergy Eff. -ORC

0.05 0 0.1

0.3

0.5

0.7

0.9

Excess Air Rao

(B)

70

Energy Transfer (kW)

60 50 40

Heat Transferred to ORC Net Output Power Heat Transfer -Condenser Heat Input to Burner

30 20 10 0 0.1

0.3

0.5

0.7

0.9

Excess Air Rao

FIGURE 6 Change in (A) efficiency (Eff.) and (B) energy transfer with the turbine excess air ratio. ORC, organic Rankine cycle.

exergy destructions in the heat exchanger, the regenerator, and the condenser were responsible for the increase in the exergy efficiency of the ORC. The electrical and exergy efficiencies of the overall system also did not change because the heat that occurred in the burner did not change with the excess air ratio. In addition, the increase in the exergy destruction rate of the burner was equal to the total decrease in the exergy destruction rates of other components; thus, the exergy efficiency of the overall system did not change. On the other hand, the excess air ratio had no effects on the exergy efficiency and exergy destruction rate of the turbine and pump (Fig. 7). When the exergetic efficiencies of the components were observed, it could be seen that exergy efficiency of the heat exchanger slightly

4. RESULTS AND DISCUSSION

269

0.9 0.8

Exergy Efficiency

0.7 0.6

0.5 0.4 0.3

Heat Exchanger Burner Turbine Pump

0.2 0.1 0 0.1

0.3

0.5

0.7

0.9

Excess Air Rao FIGURE 7 Change in exergy efficiency of the components with the excess air ratio.

increased because the decrease in the specific molar exergy difference between states 1 and 2 was greater than the decrease in the specific molar exergy difference between states 4 and 3. On the other hand, the exergy efficiency of the regenerator increased significantly because the increase in the molar exergy difference between states 5 and 6 was less than the increase in the difference between states 3 and 8 (Fig. 8).

4.2.3 Variations in Mass Flow Rate of Dry Biomass This section examines the effect of the mass flow rate of the dry biomass on the performance. An increase in the mass flow rate of dry biomass meant an increase in the heat gain from the burner and the heat transferred to ORC, which could also be interpreted from Eqs. (17) and (19). These increases caused decreases in the electrical and exergy efficiencies because the net output power of the cycle did not change with the change in the mass flow rate of the dry biomass. The trends of the changes of these efficiencies are shown in Fig. 9A. From the energy balance for a control volume enclosing the regenerator, an increase in the enthalpy of state 9 caused a decrease in the enthalpy of state 6. The enthalpy of state 10 did not change with the mass flow rate of the dry biomass. Hence, heat transfer by the condenser increased with an increase in the mass flow rate of the dry biomass. The exergy efficiency of the regenerator and heat exchanger denoted the ratio of exergy lost in the hot stream to the exergy gained in the cold stream, as shown in Eq. (26). The most considerable decrease in exergy efficiency with an increase in the mass flow rate of biomass was in the regenerator (Fig. 10). As the mass flow rate increased, the exergy recovered from the cold stream of the regenerator (stream that came from pump) decreased more than its hot stream (stream that came from the turbine). Hence, the ratio became lower. The exergy efficiency of the heat exchanger slightly decreased with the increase in the mass flow rate because the increase in the hot stream (stream that came from the burner) was more

270

CHAPTER 2.3 BIOMASS-FIRED REGENERATIVE ORC SYSTEM

(A) Exergy Destrucon Rao

0.7 0.6 0.5 0.4 0.3 0.2

Heat Exchanger Burner

0.1 0 0.1

0.3

0.5

0.7

0.9

Excess Air Rao

(B) 0.045

Exergy Destrucon Rao

0.04 Turbine Pump Condenser Regenerator

0.035 0.03 0.025 0.02 0.015 0.01 0.005 0 0.1

0.3

0.5

0.7

0.9

Excess Air Rao FIGURE 8 Change in exergy destruction ratio of (A) burner and heat exchanger, and (B) pump, turbine, regenerator, and condenser with the excess ratio.

than the increase in the cold stream (stream that circulated in the ORC). The exergy destruction rate of the regenerator increased with the increase of the mass flow rate of the dry biomass because the total molar specific exergy rates of states 6 and 3 (outlet of the regenerator) increased with the increase in the mass flow rate of the dry biomass whereas states 5 and 8 did not change. The exergy destruction of the heat exchanger also increased because the decrease in the specific molar exergy of the outlet conditions of the heat exchanger was more than the decrease in the specific molar exergy of the inlet conditions of the heat exchanger. Hence the exergy destruction rate of the heat exchanger decreased, as shown in Eq. (9). As shown in Fig. 11, the decrease or increase in the exergy destruction rate of the regenerator depends on the mass flow rate. The increase in the specific flow exergy of the turbine-side outlet

(A) 0.6 0.5

Electrical Eff. -ORC Electrical Eff. -System Exergy Eff. -ORC Exergy Eff. -System

Efficiency

0.4 0.3 0.2 0.1 0 3.4

3.8

(B)

4.2 4.6 5 5.4 Mass Flow Rate Dry Biomass (g/s)

5.8

6.2

120

Energy Transfer (kW)

100 80 60 Heat Transferred to ORC Net Output Power Heat transfer -Condenser Heat Input to Burner

40 20 0 3.4

3.8

4.2

4.6

5

5.4

5.8

6.2

Mass Flow Rate Dry Biomass (g/s)

FIGURE 9 Change in (A) efficiency (Eff.) and (B) energy transfer with the mass flow rate of dry biomass. ORC, organic Rankine cycle. 1 0.9 0.8

Exergy Efficiency

0.7 0.6 0.5 0.4

Burner Heat Exchanger Turbine Pump Regenerator

0.3 0.2 0.1 0 3.4

3.8

4.2 4.6 5 5.4 Mass Flow Rate Dry Biomass (g/s)

5.8

FIGURE 10 Change in exergy efficiency of the components with the mass flow rate of dry biomass.

6.2

272

CHAPTER 2.3 BIOMASS-FIRED REGENERATIVE ORC SYSTEM

(A) 0.7

Exergy Destrucon Rao

0.6 0.5 Burner Heat Exchanger

0.4 0.3 0.2 0.1 0

Mass Flow Rate Dry Biomass (g/s)

(B) 0.07

Exergy Destrucon Rao

0.06

0.05 0.04 0.03 0.02 0.01

Turbine Pump Condenser Regenerator

0

Mass Flow Rate Dry Biomass (g/s) FIGURE 11 Change in exergy destruction ratio of (A) heat exchanger and burner, and (B) pump, turbine, condenser, and regenerator with the mass flow rate of dry biomass.

of the regenerator was less than the decrease in that of the pump-side outlet of the regenerator until the mass flow rate value became 5 g/s. Hence exergy destruction increased. When the mass flow rate was higher than 5 g/s, the increase in the specific flow exergy of the turbine-side outlet of the regenerator was more than the decrease in that of the pump-side outlet of the regenerator. Thus, exergy destruction increased.

4. RESULTS AND DISCUSSION

90

273

Heat Transferred to ORC Net Output Power Heat Input to the Burner

80

Energy Transfer (kW)

70 60 50 40 30 20 10 0

Wheat Straw

Wood

Cypress

Paper

Hazelnut Shell

Peach Pit

FIGURE 12 Change of energy transfer with respect to the biomass type. ORC, organic Rankine cycle.

4.2.4 Variations in Biomass Fuels The lowest efficiency was gained when wheat straw was used as a biomass fuel because the chemical structure of wheat straw consists of the highest mass ratio of oxygen whereas paper has the lowest. The high oxygen mass ratio provides a high heating value and high enthalpy of the biomass. Hence the output heat increased, as shown in Fig. 12. The power consumed and produced by the pump and turbine did not change with the type of biomass. Because the net output power did not change, the electrical efficiency of the ORC and system decreased when the biomass with a high oxygen mass ratio was used as a fuel (Fig. 13). Accordingly, 0.35 Wheat Straw Wood Cypress Paper Hazelnut Shell Peach Pit

0.3

Efficiency

0.25 0.2 0.15 0.1 0.05 0 ORC Elec. Eff.

System Elec. Eff.

ORC Exergy Eff. System Exergy Eff.

FIGURE 13 The effect of the biomass type on the electrical (Elec.) and exergy efficiencies (Eff.) of the organic Rankine cycle (ORC) and the system.

274

CHAPTER 2.3 BIOMASS-FIRED REGENERATIVE ORC SYSTEM

0.9 0.8

Wheat Straw Wood Cypress Paper Hazelnut Shell Peach Pit

Exergy Efficiency

0.7 0.6 0.5 0.4

0.3 0.2 0.1 0

Pump

Heat Exchanger Turbine

Regenerator

Burner

FIGURE 14 The effect of the biomass type on the exergy efficiency of the components.

0.7

Exergy Destrucon Rao

0.6

Wheat Straw Wood Cypress Paper Hazelnut Shell Peach Pit

0.5 0.4 0.3 0.2 0.1

0

Burner

Heat Ex.

Turbine

Regen.

Conden.

Pump

FIGURE 15 The effect of the biomass type on the exergy (Ex.) destruction ratio. Conden., condenser; Regen., regeneration.

the type of biomass had no effects on the turbine and pump exergy efficiencies, as shown in Fig. 14. The biomass with a high oxygen mass ratio provided a high amount of heat gained from the burner. The more heat that was gained, the more exergy destruction occurred (Fig. 15).

5. CONCLUSIONS In this study, the effects of the change of various input parameters including the turbine inlet temperature, the mass flow rate of dry biomass, the excess air ratio, and the type of biomass were examined

REFERENCES

275

to determine in what way and to what extent each parameter changes the energy and exergy efficiency. Main conclusions derived from this study are: •

•

•

•

Electrical efficiency of the ORC increased from 0.09 to 0.16 and exergy efficiency of the ORC increased from 0.17 to 0.29 with an increase in the turbine inlet temperature from 377 to 473K. At the same range of TIT, the electrical efficiency of the overall system increased from 0.09 to 0.15 and the exergy efficiency increased from 0.08 to 0.13. An increase in the excess air ratio causes an increase in the electrical and exergy efficiencies of the ORC as the heat transferred to ORC decreased at higher excess air ratios and the net output power did not change. At higher excess ratios, a decrease in the heat transfer rate of the heat exchanger and condenser reduced the exergy destruction ratios of these components. Variations in the excess air ratio did not affect the electrical and exergy efficiencies of the system because the change in the excess air ratio did not change the net output work and the lower heating value of the biomass. The higher mass flow rate of the dry biomass caused lower electrical and exergy efficiencies   because the higher mass flow rate provided higher heat input to the burner Q_burner . Hence, the electrical and exergy efficiency of the overall system decreased with an increase in the mass flow rate of the biomass. An increase in the heat input to the burner also caused high exergy destruction in the burner. Wheat straw provided a high amount of heat input to the burner and transferred it to the ORC. Hence the highest electrical and exergy efficiencies were achieved when wheat straw was used as the biomass fuel for the input parameters taken for this study.

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[9] Guo T, Wang HX, Zhang SJ. Fluids and parameters optimization for a novel cogeneration system driven by lowtemperature geothermal sources. Energy 2011;36:2639e49. http://dx.doi.org/10.1016/j.energy.2011.02.005. [10] Lakew AA, Bolland O. Working fluids for low-temperature heat source. Applied Thermal Engineering 2010; 30:1262e8. http://dx.doi.org/10.1016/j.applthermaleng.2010.02.009. [11] Peterson RB, Wang H, Herron T. Performance of a small-scale regenerative Rankine power cycle employing a scroll expander. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy 2008;222:271e82. http://dx.doi.org/10.1243/09576509JPE546. [12] Zhang Y-Q, Wu Y-T, Xia G-D, Ma C-F, Ji W-N, Liu S-W, et al. Development and experimental study on organic Rankine cycle system with single-screw expander for waste heat recovery from exhaust of diesel engine. Energy 2014;77:499e508. http://dx.doi.org/10.1016/j.energy.2014.09.034. [13] Bao J, Zhao L. A review of working fluid and expander selections for organic Rankine cycle. Renewable and Sustainable Energy Reviews 2013;24:325e42. http://dx.doi.org/10.1016/j.rser.2013.03.040. [14] Kakac¸ S, Liu H, Pramuanjaroenkij A. Heat exchangers: selection, rating, and thermal design. 2012. p. 631. http://dx.doi.org/10.1016/0378-3820(89)90046-5. [15] Shah RK, Sekulic DP. Fundamentals of heat exchanger design; 2003. p. 941. http://dx.doi.org/10.1002/ 9780470172605. [16] Zhai H, Shi L, An Q. Influence of working fluid properties on system performance and screen evaluation indicators for geothermal ORC (organic Rankine cycle) system. Energy 2014;74:2e11. http://dx.doi.org/ 10.1016/j.energy.2013.12.030. [17] Sakhrieh A, Shreim W, Fakhruldeen H, Hasan H. Combined solar-geothermal power generation using organic Rankine cycle. Jordan Journal of Mechanical and Industrial Engineering 2016;10:1e9. [18] Bombarda P, Invernizzi CM, Pietra C. Heat recovery from diesel engines: a thermodynamic comparison between Kalina and ORC cycles. Applied Thermal Engineering 2010;30:212e9. http://dx.doi.org/10.1016/ j.applthermaleng.2009.08.006. [19] Sauret E, Rowlands AS. Candidate radial-inflow turbines and high-density working fluids for geothermal power systems. Energy 2011;36:4460e7. http://dx.doi.org/10.1016/j.energy.2011.03.076. [20] Fiaschi D, Lifshitz A, Manfrida G, Tempesti D. An innovative ORC power plant layout for heat and power generation from medium- to low-temperature geothermal resources. Energy Conversion and Management 2014;88:883e93. http://dx.doi.org/10.1016/j.enconman.2014.08.058. [21] Liu Q, Duan Y, Yang Z. Performance analyses of geothermal organic Rankine cycles with selected hydrocarbon working fluids. Energy 2013;63:123e32. http://dx.doi.org/10.1016/j.energy.2013.10.035. [22] Freeman J, Hellgardt K, Markides CN. An assessment of solar-powered organic Rankine cycle systems for combined heating and power in UK domestic applications. Applied Energy 2015;138:605e20. http:// dx.doi.org/10.1016/j.apenergy.2014.10.035. [23] Delgado-Torres AM, Garciaa-Rodriguez L. Analysis and optimization of the low-temperature solar organic Rankine cycle (ORC). Energy Conversion and Management 2010;51:2846e56. http://dx.doi.org/10.1016/ j.enconman.2010.06.022. [24] Al-Sulaiman FA. Exergy analysis of parabolic trough solar collectors integrated with combined steam and organic Rankine cycles. Energy Conversion and Management 2014;77:441e9. http://dx.doi.org/10.1016/ j.enconman.2013.10.013. [25] Baral S, Kim KC. Thermodynamic modeling of the solar organic Rankine cycle with selected organic working fluids for cogeneration. Distributed Generation and Alternative Energy Journal 2014;29:7e34. http://dx.doi.org/10.1080/21563306.2014.10879015. [26] Reddy BV, Ramkiran G, Ashok Kumar K, Nag PK. Second law analysis of a waste heat recovery steam generator. International Journal of Heat and Mass Transfer 2002;45:1807e14. http://dx.doi.org/10.1016/ S0017-9310(01)00293-9.

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[27] Ammar Y, Joyce S, Norman R, Wang Y, Roskilly AP. Low grade thermal energy sources and uses from the process industry in the UK. Applied Energy 2012;89:3e20. http://dx.doi.org/10.1016/j.apenergy.2011.06.003. [28] Karellas S, Leontaritis A-D, Panousis G, Bellos E, Kakaras E. Energetic and exergetic analysis of waste heat recovery systems in the cement industry. Energy 2013;58:147e56. http://dx.doi.org/10.1016/ j.energy.2013.03.097. [29] Yang F, Dong X, Zhang H, Wang Z, Yang K, Zhang J, et al. Performance analysis of waste heat recovery with a dual loop organic Rankine cycle (ORC) system for diesel engine under various operating conditions. Energy Conversion and Management 2014;80:243e55. http://dx.doi.org/10.1016/j.enconman.2014.01.036. [30] Larjola J. Electricity from industrial waste heat using high-speed organic Rankine cycle (ORC). International Journal of Production Economics 1995;41:227e35. http://dx.doi.org/10.1016/0925-5273(94)00098-0. [31] Field CB, Campbell JE, Lobell DB. Biomass energy: the scale of the potential resource. Trends in Ecology and Evolution 2008;23:65e72. http://dx.doi.org/10.1016/j.tree.2007.12.001. [32] McKendry P. Energy production from biomass (part 2): conversion technologies. Bioresource Technology 2002;83:47e54. http://dx.doi.org/10.1016/S0960-8524(01)00119-5. [33] Yang H, Yan R, Chen H, Lee DH, Zheng C. Characteristics of hemicellulose, cellulose and lignin pyrolysis. Fuel 2007;86:1781e8. http://dx.doi.org/10.1016/j.fuel.2006.12.013. [34] Liu H, Shao Y, Li J. A biomass-fired micro-scale CHP system with organic Rankine cycle (ORC) e thermodynamic modelling studies. Biomass and Bioenergy 2011;35:3985e94. http://dx.doi.org/10.1016/ j.biombioe.2011.06.025. [35] Qiu G, Shao Y, Li J, Liu H, Riffat SB. Experimental investigation of a biomass-fired ORC-based micro-CHP for domestic applications. Fuel 2012;96:374e82. http://dx.doi.org/10.1016/j.fuel.2012.01.028. [36] Huang Y, Wang YD, Rezvani S, McIlveen-Wright DR, Anderson M, Mondol J, et al. A techno-economic assessment of biomass fuelled trigeneration system integrated with organic Rankine cycle. Applied Thermal Engineering 2013;53:325e31. http://dx.doi.org/10.1016/j.applthermaleng.2012.03.041. [37] Szargut J. Exergy method e technical and ecological applications, vol. 9; 2005. Boston. [38] Gusev S, Ziviani D, Bell I, Paepe M, Broek M. Experimental comparison of working fluids for organic Rankine cycle with single-screw expander. In: 15th Int. Refrig. Air Cond. Conf., Purdue; 2014. [39] Basu P, Kefa C, Jestin L. Boilers and burners. 1st ed. New York: Springer-Verlag New York; 2000. http:// dx.doi.org/10.1007/978-1-4612-1250-8.

CHAPTER

THERMAL DESIGN AND MODELING OF SHELL AND TUBE HEAT EXCHANGERS COMBINING PTSC AND ORC SYSTEMS

2.4 Anil Erdogan, C. Ozgur Colpan _ Dokuz Eylul University, Izmir, Turkey

1. INTRODUCTION A heat exchanger is a device that transfers thermal energy or heat between two or more fluids. Heat exchangers are widely used in many engineering applications such as heating, ventilating, and cooling, geothermal energy applications and power plants, food processing, and petroleum refining [1,2]. Heat exchangers can be classified according to different criteria such as the flow arrangement (e.g., cross-flow, co-flow, and counterflow), the number of fluids (one, two, or more), and the construction type (shell and tube, fin, gasket, and compact-type heat exchangers). Among the different heat exchanger types, more than 35% to 40% are of the shell and tube variety, mainly because they are easy to repair and clean and they solve leakage problems, and fluids with high pressures and heat capacities can be used [3,4]. The main component of shell and tube heat exchangers is baffles. Baffles support the tube bundles and create turbulence, thus increasing the overall heat transfer coefficient. When the heat transfer rate is increased, the performance of the heat exchanger also increases. The most commonly used baffle type is segmental [1,5] as shown in Fig. 1A. This type of heat exchanger forces the shell-side fluid

FIGURE 1 Schematics of different baffle type of shell and tube heat exchangers: (A) segmental baffle and (B) helical baffle. Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00016-0 Copyright © 2018 Elsevier Inc. All rights reserved.

279

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CHAPTER 2.4 SHELL AND TUBE HEAT EXCHANGERS

through the device in a zigzag manner, improving the heat transfer rate and overall heat transfer coefficient. However, segmental baffle heat exchangers have disadvantages. The heat transfer rate and overall heat transfer coefficient are lower than for other types of heat exchangers. These result in a dead zone in each compartment between the two segmental baffles [3]. They also cause vibration failure on the tube bundle [6]. Another baffle type is helical, which overcomes the main drawbacks of segmental baffles. Helical baffles were proposed by Lutcha and Nemcansky [7]. They investigated flow fields with helical baffles with different helix angles and compared them with a segmental baffled heat exchanger. They found that heat transfer performance improved with a helical baffle heat exchanger. This baffle type is illustrated in Fig. 1B. The helix angle is referred as the angle between the axis of the heat exchanger and the normal line of the corresponding plate [1,8]. A schematic of this type of baffle is shown in Fig. 2. Zhang et al. [3] carried out a three-dimensional numerical model of a heat exchanger with middle overlapped helical baffles with 40 degrees of helical angle using Gambit and Fluent software. Then they implemented a validation study of the computational model and compared the pressure drop and Nusselt number of the heat exchanger with experimental data. The results of the study showed that for both the pressure drop and Nusselt number, experimental and numerical data had similar trends. In addition, numerical results showed that the second and fifth cycles were less than 2% for both the pressure drop and heat transfer. Yang et al. [9] offered the novel design of a shell and tube heat exchanger with two-layer continuous helical baffles and compared them with continuous helical baffles. Numerical solutions were applied to compare the pressure drop, heat transfer rate, shell-side heat transfer coefficient, and heat transfer rate per pressure drop for continuous, noncontinuous, and segmental baffle-type heat exchangers. Their results showed that the two-layer continuous baffle type heat exchanger had a lower pressure drop than did the continuous baffle heat exchanger by about 13%.

FIGURE 2 Schematic of a helical baffle.

1. INTRODUCTION

281

The heat transfer rate and shell-side heat transfer coefficient for the continuous helical baffle-type heat exchanger were higher than for the segmental baffle-type heat exchanger by about 2.4% and 4.2%, respectively. Nakaso et al. [10] investigated the convection heat transfer coefficient of a shell and tube heat exchanger with sheet fins using the numerical solution method. The overall heat transfer rate and pressure drop with fins were formulated considering the geometry of the heat exchanger, fin efficiency, and contact thermal resistance. The results showed that when sheet fins were used, the pressure drop increased by 10% to 15%; on the other hand, the overall heat transfer coefficient increased by 15% to 50%. Wang et al. [11] developed a combined multiple shell pass shell and tube heat exchanger with continuous helical baffles; they improved the heat transfer performance and simplified the manufacturing process. They compared the conventional shell and tube heat exchanger and the combined multiple shell pass shell and tube heat exchanger in terms of velocity and temperature distribution, and heat transfer and pressure drop performance. Numerical results showed that under the same mass flow rate of fluids and heat transfer rate, the average pressure drop of the combined multiple shell pass shell and tube heat exchanger with a continuous helical baffle was 13% lower than for the conventional one. For the same shell-side pressure drop, the heat transfer rate of the combined multiple shell pass shell and tube heat exchanger was 5.6% higher than for the conventional shell and tube heat exchanger. Lei et al. [8] experimentally as well as numerically studied the hydrodynamic and heat transfer characteristics of a heat exchanger with single helical baffles. Comparisons of the performance of three heat exchangers with a single segment baffle, a single helical baffle, and twolayer baffles were presented. Their results showed that under the same pressure drop, the heat exchanger with helical baffles had a higher shell-side heat transfer coefficient than did that of the heat exchanger with segmental baffles, and two-layer helical baffles had better performance than did that of the single helical baffle. Solar collectors absorb solar radiation and then transfer the heat to the heat transfer fluid (HTF), which is commonly used as thermal or synthetic oil. This fluid is used directly or its heat is transferred to another fluid for the required system (e.g., hot water for home applications or the production of steam) to increase temperature with high efficiency. Parabolic trough solar collectors (PTSCs) are generally preferred for energy production applications within the HTF temperature range of 50 and 400
C because they are inexpensive and provide high energy [12,13]. PTSCs are constructed using reflective materials and are in the form of a parabola. The schematics of a PTSC is given in Fig. 3. As can be seen in the figure, PTSC systems consist mainly of three components: the collector, receiver, and glass cover tubes. The receiver tube, which is black in this figure, is generally made of stainless steel or alloy steel [14]. The receiver tube is inside the glass cover; there is a vacuum between the receiver and the glass cover tubes. PTSCs provide higher thermal performance according to flat plate collectors. The thermal performance depends on the reflectivity, absorptivity, heat transfer fluid, tracking mechanism, and so on [13e15]. There are some studies on PTSC design and modeling in the literature. Kalogirou et al. [16] conducted a performance test of a PTSC according to American Society of Heating, Refrigerating and Air Conditioning Engineers standards. The collector’s efficiency and incidence angle were measured; as a result of these measurements, the collector’s acceptance angle was obtained in the range of 0.5 degrees. In addition, when the maximum error of the tracking mechanisms was 0.2 degrees, the system worked continuously at the maximum possible efficiency. In the study by Odeh et al. [17], the efficiency of PTSCs was determined for operation with Syltherm 800 oil and water as the working fluids. The absorber emissivity and internal working fluid convection effects

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CHAPTER 2.4 SHELL AND TUBE HEAT EXCHANGERS

FIGURE 3 Schematics of a parabolic trough solar collector (PTSC) and its layers.

were evaluated. An efficiency equation was developed and used in a simulation model to evaluate the performance of the system under different radiation conditions and for different absorber tube sizes. Herrmann et al. [18] proposed a concept according to which a less expensive liquid medium such as molten salt was employed as storage medium rather than the heat transfer fluid itself. The detailed performance was studied and a cost analysis was performed. The study concluded that the specific cost for two-tank molten salt storage was in the range of US $30 to $40/kWh, depending on the storage size. Kalogirou et al. [13] discussed the different types of solar collectors (flat plate, compound parabolic, evacuated, parabolic trough, Fresnel lens, and heliostat field collectors) and their applications. Optical, thermal, and thermodynamic analyses were performed for the collectors, and a description was given of the methods used to evaluate their performance. Brooks et al. [19] characterized the performance of PTSCs. Low-temperature testing was performed using water as the working fluid. An evacuated glass-shield and unshielded receiver were tested; the thermal efficiencies were 53.8% and 55.2%, respectively, for the receivers. Brooks et al. [20] developed a PTSC similar in size to small-scale commercial modules. In that study, the working collector length was 5 m, the aperture width was 1.5 m, and the rim angle was 82.2 degrees. In addition, an optical error analysis was conducted to estimate the intercept factor. In a study by Qu et al. [21], a performance model of a solar collector based on a linear and tracking parabolic trough reflector was programmed using the software Engineering Equation Solver. The model included fundamental radiative and convective heat transfer, and mass and energy balance relations. Typical performance showed that when the 165
C water flowed through a 6  2.3-m PTSC with 900 W/m2 solar insulation and 0 degree incident angle, the collector efficiency was estimated to be 35%. Patnode et al. [22] developed a model for a solar collector edriven Rankine cycle using the TRNSYS simulation program. Both the PTSC and Rankine cycle models were validated with the measured temperature and flow rate data of the SEGS VI plant for 1998e2005. These models were used to evaluate the effects of solar field collector degradation, flow rate control strategies, and alternative condenser design on the plant’s performance.

2. SYSTEM DESCRIPTION

283

A survey of the literature showed that there was limited research of shell and tube heat exchangers combining PTSC and ORC systems. In this study, a comprehensive mathematical model was formed to determine the effect of design parameters on the performance of shell and tube heat exchangers. In addition, an exergy assessment of shell and tube heat exchanger was conducted.

2. SYSTEM DESCRIPTION A schematic of the integrated system is shown in Fig. 4 and the input parameters of the heat exchanger model for baseline conditions are given in Table 1. The modeling equations of the shell and tube heat exchangers and PTSC are given in the following sections. The main assumptions for this model were that: • • • • •

The heat exchanger runs under steady-state conditions. The heat exchanger is well insulated; hence the loss of heat into the environment is neglected. Changes in the kinetic and potential energies and their effects on the flowing streams between the inlet and exit can be neglected. The pressure drop across the tube side of the heat exchanger is ignored. Leak flows between the tube and the baffle, and between the baffle and the shell are ignored.

FIGURE 4 Schematic of the integrated system. ORC, organic Rankine cycle.

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CHAPTER 2.4 SHELL AND TUBE HEAT EXCHANGERS

Table 1 Input Parameters of Heat Exchanger Model and Parabolic Trough Solar Collectors (PTSCs) for Baseline Conditions Parameter

Value

PTSC side fluid ORC side fluid Number of passes Tube length Inner diameter of tube Wall thickness Tube pitch Tube layout angle Baffle spacing Thermal conductivity of tube Mass flow rate of cold fluid Mass flow rate of hot fluid Pressure of the fluid on ORC side Outlet temperature of hot fluid Inlet temperature of cold fluid

Therminol VP1 R134a 1 12 m 0.016 m 0.0015 m 0.0254 m 90 degrees 0.5 m (for segmental baffle) 63.9 W/m K 213.368 kg/s 27.5 kg/s 4370 kPa 563K 420.7K

ORC, organic Rankine cycle.

3. MATHEMATICAL MODELING 3.1 MATHEMATICAL MODELING OF PARABOLIC TROUGH SOLAR COLLECTOR This section provides the modeling approach and equations for the PTSC. The aim of the PTSC model developed was to find the exit temperature of the PTSC for a set of given input parameters. The detailed PTSC model equations are given in Kalogirou [14] and Duffie and Beckman [23]. The main equations are summarized next. The rate of useful energy delivered by the collectors to the PTSC-side fluid can be found using Eq. (1): 2 0 13 Qu ¼

B m_ h $cp 6 61  expB 4 @ Ar $UL


m_ h $cp $

Ar




1 Do Do Do þ ln þ þ UL hfi Di 2k Di

 ½Gb $r$g$s$a$K$Aa  Ar $UL $ðTi  Ta Þ$NPTSC where UL is the solar collector heat loss coefficient and can be shown as: !1 Ar  UL ¼  hc;ga þ hr;ga $Ag

C7 7 C A5 (1)

(2)

3. MATHEMATICAL MODELING

The glass cover temperature can be found using Eq. (3):   Ar $hr;rg $Tr þ Ag $ hr;ga þ hc;ga $Ta   Tg ¼ Ar $hr;rg þ Ag $ hr;ga þ hc;ga

285

(3)

In this equation, hc,ga, hr,ga, and hr,rg can be found in Kalogirou [14] and Al-Sulaiman [15]. To find the exit temperature of the PTSC, an energy balance should be applied around the PTSC. This equation is given in Eq. (4). In this equation, thermal oil, which is flowing through the PTSC, is assumed to be an incompressible fluid: Th;i ¼ Th;o þ

Qu m_ h $cp;h

(4)

3.2 MATHEMATICAL MODELING OF SHELL AND TUBE HEAT EXCHANGERS This section provides the modeling equations for the shell and tube heat exchanger and baffle configuration calculations. The main equations for the shell and tube heat exchanger that were used to calculate the heat transfer rate, Nusselt and Reynolds numbers, overall heat transfer coefficient, and log-mean temperature difference were the same for all baffle configuration types (segmental, continuous, and noncontinuous). However, the cross-sectional area of the shell perpendicular to the flow direction and the baffle spacing formulas were different, as discussed subsequently. The overall heat transfer coefficient can be found using Eq. (5): 00 1 Do 1 lnðDo =Di Þ 1 Do 00 ¼ $ þ þ þ $Rfi þ Rfo U D i hi 2$p$k$L ho D i

(5)

00

where Rf is the fouling factor at the tube and shell sides. This parameter can be found in Ref [24,25], and is taken as 0.0002 m2 K/W. To calculate the heat transfer coefficient of the tube side, the Reynolds number of the tube side fluid was first identified. Then the flow regime was identified according to the Reynolds number, and finally the Nusselt number was found according to the flow regime. These formulas are shown in Table 2: Re ¼

4$m_ c m$p$Di $

(6)

NT npass

Table 2 Nusselt Correlations for Different Flow Regimes [24,25,28] Flow Regime

Equation

Condition

Laminar Turbulent

Nu ¼ 4.36 f $ðRe  1000ÞPr Nu ¼ 8  13   2 f

Re  2300 2300 < Re < 5  104

1þ12:7$ 8

$ Pr 3 1

where f ¼ ð0:79$lnðReÞ  1:64Þ2

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CHAPTER 2.4 SHELL AND TUBE HEAT EXCHANGERS

To calculate the heat transfer of the shell side, the Nusselt number can be calculated using the equation developed by McAdams Eq. (7):  1
ho $De mb 0:14 0:55 3 ¼ 0:36$Re $Pr$ Nu ¼ (7) k mw In Eq. (7), the equivalent diameter (De) for the square tube alignment was found using Eq. (8). In this equation, Pt is the tube pitch, which changes according to the tube diameter [24]: De ¼

 1:27  2 $ Pt  0:785D2o Do

(8)

The Reynolds number of the shell side can be found using Eq. (9). In this equation, As is the crosssectional area of the shell perpendicular to the flow direction, according to the segmental, continuous, or noncontinuous baffle type; it can be calculated using Eqs. (10) and (11), respectively: Reshell ¼

De $m_ h m$As

rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi CL A $ ðFor segmental baffle configurationÞ As ¼ 0:639$ðPt  Do Þ$e$ CTP Do $L

Dotl  Do As ¼ 0:5$e$ Dshell  Dotl þ $ðPt  Do Þ ðFor continuous and noncontinuous Pt

(9) (10)

(11)

baffle configurationsÞ where e is the baffle spacing and is calculated using Eqs. (12) and (13) for continuous and noncontinuous baffle configurations, respectively: e ¼ p$Dshell $tan b ðFor continuous baffle configurationÞ pffiffiffi e ¼ 2$Dshell $tan b ðFor non  continuous baffle configurationÞ

(12) (13)

In Eq. (10), the tube layout constant and tube count constant depend on heat exchanger geometry and can be found in Ref. [25]. To analyze the shell and tube heat exchanger, the logarithmic mean temperature difference method is used. The heat transfer rate can be found using Eq. (14):     Th;i  Tc;o  Th;o  Tc;i   Q ¼ U$A$F (14) Th;i  Tc;o   ln Th;o  Tc;i where F is the correction factor, which can be found using diagrams in Refs. [2,25]. The heat transfer surface area can be calculated using Eq. (15): A ¼ p$Do $L$NT

(15)

3. MATHEMATICAL MODELING

287

The pressure drop across the heat exchanger and the tubes of PTSC are important parameters for designing the shell and tube heat exchanger. The shell-side pressure drop can be found as: DPshell ¼

ffric $G2shell $ðNb þ 1Þ$Dshell 2$r$De $fshell

(16)

where ffric is the friction factor, Gshell is the mass velocity of the shell side, Nb is the baffle number, and fshell is the viscosity ratio between the bulk and wall temperatures. These parameters can be found as: ffric ¼ exp½0:576  0:19$lnðReshell Þ m_ h As
0:14 mb fshell ¼ mw 
L þ1 Nb ¼ e Gshell ¼

(17) (18) (19) (20)

The pressure drop across the tube of the PTSC can be found using Eq. (21): DPPTSC ¼ hloss $r$g

(21)

where hloss is the head loss resulting from the frictional losses, which can be found as: hloss ¼ f $

LPTSC Vh2 $ Di;receiver 2$g

(22)

where f is the friction factor, which can be found from the Moody chart [26]. The total pressure drop, including both the PTSC and the pressure drop of the shell side of the heat exchanger, can be found as: DPtotal ¼ DPPTSC þ DPshell

(23)

3.3 EXERGETIC ASSESSMENT OF THE HEAT EXCHANGER The previous section presented modeling equations for both the shell and tube heat exchanger and the PTSC. After finding the thermodynamic properties of each inlet and outlet of the PTSC and the shell and tube heat exchanger, the exergetic efficiency of the shell and tube heat exchanger should be calculated to define the performance assessment of the heat exchanger. To calculate the exergetic efficiency of the shell and tube heat exchanger, the flow exergy change of cold and hot fluids between the inlets and exits in the heat exchanger were first calculated using Eqs. (24) and (25):     _ f ;cold ¼ m_ cold; f $ hc;o  hc;i  T0 $ sc;o  sc;o DEx (24)     _ f ;hot ¼ m_ hot; f $ hh;i  hh;o  T0 $ sh;i  sh;o DEx (25) Finally, the exergetic efficiency of the heat exchanger was calculated using Eq. (26): hex ¼

_ f ;cold Ex _ f ;hot Ex

(26)

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CHAPTER 2.4 SHELL AND TUBE HEAT EXCHANGERS

4. RESULTS AND DISCUSSIONS In Section 3, the modeling equations of the PTSC and the shell and tube heat exchanger, including the baffle configuration and exergetic efficiency calculations, were given. These correlations were solved using the EES program, and parametric studies were conducted. The results of the parametric studies are presented in this section. These studies include the effect of the diameter of the heat exchanger tube, the tube length, and the mass flow rate of the shell-side fluid, helix angles, and different types of baffle configurations, which were segmental, continuous, and noncontinuous, on the performance of the heat exchanger. Performance parameters were the shell-side heat transfer coefficient, the total pressure drop, and the exergetic efficiency. The parametric studies were conducted in a range between the minimum and maximum values for the outer diameter of the heat exchanger tube, tube length, and mass flow rate of the shell-side fluid considering Tubular Exchanger Manufacturers Association (TEMA) standards [24]. These values are shown in Table 3. Helix angles were taken as 15, 30, 45, and 60 degrees, whereas different baffle configurations were taken as segmental, continuous, and noncontinuous.

4.1 RESULTS FOR THE SEGMENTAL BAFFLE CONFIGURATION 4.1.1 Effect of Outer Diameter of the Tube on the Performance of the System The effect of the outer diameter of the tube on the performance of the system was assessed. The different values for this diameter were taken from TEMA standards [24]. According to TEMA standards, tube diameters have 10 values: 0.0064, 0.0095, 0.0127, 0.0157, 0.0191, 0.0222, 0.0254, 0.0318, 0.0381, and 0.0508 m. Using the code developed in EES, a parametric study was conducted for these values for the outer diameter of the tube. As a result, a change was found in the overall heat transfer coefficient and a pressure drop with respect to this diameter. The parametric study was repeated for different numbers of passes (one, two, and three) and layout angles (30, 45, 60, and 90 degrees); the results for these studies are shown in Figs. 5 and 6, respectively. Fig. 5A and B shows the change in the overall heat transfer coefficient and the total pressure drop for different values of the outer diameter of the tube and the number of passes, respectively. The results show that in increasing the outer diameter of the tube, the overall heat transfer coefficient fluctuated. When this parameter was as small as possible (0.0064 m), the overall heat transfer coefficient required was at its maximum value. This was because of the change in the flow regime. On the other hand, as can be seen from Fig. 5B, the effect of this parameter on the total pressure drop was more significant when the outer diameter of the tube was less than 0.0222 m. When this diameter was 0.0127 m, the total pressure drop was at its maximum value. This finding can be explained as follows. As the outer diameter increased, the equivalent diameter (Eq. 8) increased, and thus the pressure drop decreased.

Table 3 Maximum and Minimum Values of Parameters for Parametric Studies

Minimum Maximum

Outer Diameter of Tube (m)

Tube Length (m)

Mass Flow Rate of Shell-Side Fluid (kg/s)

Solar Radiation (W/m2)

0.0064 0.0508

2.438 11.58

15 50

450 1000

4. RESULTS AND DISCUSSIONS

289

FIGURE 5 Effect of the outer tube diameter on the (A) overall heat transfer coefficient and (B) total pressure drop for different numbers of passes (npass).

These figures also show that the number of passes did not have a significant effect on the results but only changed the number of tubes required. Taking the number of passes as one yielded a slightly lower overall heat transfer coefficient compared with a heat exchanger with two or three tube passes.

4.1.2 Effect of Baffle Spacing on the Performance of the System Minimum and maximum baffle spacing values are shown in Table 3. Minimum baffle spacing was found using the TEMA standards [24], whereas the maximum baffle spacing was taken as 29:5$do0:75 , where do is in meters [27]. Fig. 6A and B show the change in the overall heat transfer coefficient and the total pressure drop for different values of baffle spacing and the number of passes, respectively. The results showed that increasing the baffle spacing decreased the overall heat transfer coefficient. This may have occurred because as the baffle spacing decreased, the effect of the turbulence and thus the shell-side heat transfer coefficient decreased. When the baffle spacing was 0.08 m, the overall heat transfer coefficient was at its maximum value (1040 W/m2 K). On the other hand, when the baffle spacing was 1.5 m, the overall heat transfer coefficient was at its minimum value (115 W/m2 K). These results showed that the baffle

290

CHAPTER 2.4 SHELL AND TUBE HEAT EXCHANGERS

FIGURE 6 Effect of baffle spacing on the (A) overall heat transfer coefficient and (B) pressure drop for different numbers of passes (npass).

spacing should be selected to be as low as possible (0.08 m). The effect of the number of passes on the results seemed to be negligible. Fig. 6A and B show that increasing the baffle spacing first sharply decreased the total pressure drop to the point where the baffle spacing was 0.32 m; then this parameter remained nearly constant with a further increase in the baffle spacing. This result was mainly due to the change in the flow regime. When the baffle spacing changed between 0.08 and 1.5 m, the Reynolds number decreased from 1,422,000 to 72,189; hence the flow regime became closer to the laminar flow when we increased the baffle spacing. Fig. 7A and B show the change in the overall heat transfer coefficient and the total pressure drop for different values of the baffle spacing and tube layout angle, respectively. When the tube layout angle was 45 and 90 degrees, the overall heat transfer coefficient decreased. Fig. 7B also shows that the effect of the tube layout angle on the pressure drop was not significant.

4.2 RESULTS FOR HELICAL BAFFLE CONFIGURATIONS 4.2.1 Effects of Tube Diameter on the Performance of the System The effects of the tube diameter on the performance of the system for the shell-side heat transfer coefficient and total pressure drop are presented in this section. Fig. 8A shows the shell-side heat transfer coefficient for different outer tube diameters and baffle configurations. The figure shows that

4. RESULTS AND DISCUSSIONS

291

FIGURE 7 Effect of baffle spacing on the (A) overall heat transfer coefficient (B) pressure drop for different tube layout angles.

when the outer tube diameter increased, the shell-side heat transfer coefficient fluctuated. This trend was mainly the result of a change in the flow regime. In addition, Fig. 8A illustrates that the shell-side heat transfer coefficient of noncontinuous baffles was higher than that of the segmental and continuous-type baffles. Fig. 8B shows the change in the total pressure drop of the system for different values of outer tube diameters and baffle configurations. The results showed that increasing the outer tube diameter resulted in fluctuations in the total pressure drop of the system. On the other hand, the noncontinuous baffle type causes a higher pressure drop than that of the segmental baffle and continuous baffle types. Fig. 8B also shows that when the tube diameter was 0.0258 m, the total pressure with the continuous baffle had the lowest value (32.79 kPa), and when the tube diameter was 0.0508 m, the total pressure drops for the segmental and non-continuous baffles type heat exchangers were 36.52 and 350.40 kPa, respectively. Fig. 9A presents the changes in the shell-side heat transfer coefficient for the outer tube diameter and continuous baffle type of shell and tube heat exchanger according to different helix angles. The figure shows that the shell-side heat transfer coefficient increased with a decrease in the helix angle. The change can be understood in two ways. First, at a fixed shell diameter, the baffle spacing and crosssectional area of the shell perpendicular to the flow direction increased with an increase in the helix angle. Second, the Reynolds number of the shell-side fluid decreased with an increase in the helix angle. Thus, the convective heat transfer coefficient of the shell side increased. On the other hand, Fig. 9B shows the change in the total pressure drop of the system for the outer tube diameter and

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FIGURE 8 Effect of outer tube diameter on the (A) shell-side heat transfer coefficient and (B) total pressure of the system for different baffle configurations.

continuous baffle-type heat exchanger according to different helix angles. The results showed that the pressure drop decreased with a decrease in the helix angles. This trend mainly resulted from the increase in the helix angle; hence the baffle spacing and cross-sectional area of the shell perpendicular to the flow direction increased with an increase in the helix angle, and the shell-side mass velocity decreased, and thus the total pressure drop decreased. Fig. 10A illustrates the change in the shell-side heat transfer coefficient for the different outer tube diameters and noncontinuous type baffle configurations. Decreasing the helix angle increased the shell-side heat transfer coefficient. On the other hand, Fig. 10B shows that a change in the total pressure drop for the noncontinuous heat exchanger and outer tube diameter. The results showed that an increase in the helix angle resulted in a decrease in the total pressure drop.

4.2.2 Effect of Tube Length on the Performance of the System This section discusses the effect of the tube length on the performance of the system. The values of tube length were taken from the TEMA standards [24]: 2.438, 3.048, 4.877, 6.096, 7.32, 8.53, 9.75,

4. RESULTS AND DISCUSSIONS

293

FIGURE 9 Effect of the outer tube diameter on the (A) shell-side heat transfer coefficient and (B) total pressure drop for different helix angles with continuous helical baffle-type configuration.

10.7, and 11.58 m. Using the EES code, parametric studies were conducted for these values and are presented and discussed subsequently. Fig. 11A shows the change in the shell-side heat transfer coefficient for the tube lengths and different baffle configurations. Increasing the tube length increased the shell-side heat transfer coefficient. At the same helix angle, shell diameter, and tube length, the shell-side heat transfer coefficient of the noncontinuous baffle was around 71.7% higher than that of the continuous baffle type. This may have resulted from the increase in the tube length, and thus the increase in the cross-sectional area of the shell perpendicular to flow direction, the increase in the Reynolds number of the shell side, and the increase in the convective heat transfer coefficient of the shell side. However, when the tube length was 2.438 m, the shell-side coefficient of the segmental baffle type was higher than that of the continuous type. Fig. 11B illustrates the change in the total pressure drop for the tube lengths and different baffle configurations. At the same tube length, the total pressure drop for the noncontinuous baffle type heat exchanger was the highest among the other baffle types. This trend can be understood in two ways. First, the shell-side mass velocity increased with an increase in the total pressure drop. Second, the shell diameter and helix angles were taken as constant in comparison. The baffle spacing of the continuous-type heat exchanger was higher than that of the other types, whereas the shell-side mass

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FIGURE 10 Effect of outer tube diameter on the (A) shell-side heat transfer coefficient and (B) total pressure drop for different helix angles with noncontinuous baffle-type configuration.

velocity decreased with a decrease in the total pressure drop. However, when the tube length was between 2 and 4 m, the total pressure drop for the continuous-type heat exchanger was lower than that for the segmental-type heat exchanger. Fig. 12A shows the change in the shell-side heat transfer coefficient for different tube lengths and helix angles for the continuous baffle type. The shell-side heat transfer coefficient increased with a decrease in the helix angle. This trend may have been because of the decrease in the helix angle with a decrease in the baffle spacing. Thus the shell-side heat transfer coefficient increased. Fig. 12B illustrates the change in the total pressure drop of the system among three helical angles within the range of the tube length. The total pressure drop decreased with an increase in the helix angles. As the helix angle increased, the baffle spacing increased, the cross-sectional area of the shell perpendicular to the flow direction increased, and the shell-side mass velocity decreases. Thus, the total pressure drop of the system decreased. Fig. 13A illustrates the differences in shell-side heat transfer coefficients with tube lengths for a noncontinuous baffle type heat exchanger. The shell-side heat transfer coefficient increased with a decrease in the helix angles. On the other hand, Fig. 13B shows a change in the total pressure drop of the system for the different tube lengths and helix angles for the noncontinuous baffle-type heat exchanger. The total pressure drop decreased with an increase in the helix angle.

4. RESULTS AND DISCUSSIONS

295

FIGURE 11 Effect of tube length on the (A) shell-side heat transfer coefficient and (B) total pressure drop of the system for different baffle configurations.

4.2.3 Effect of the Shell-Side Mass Flow Rate on the Performance of the System This section presents and discusses the effects of the shell-side mass flow rate on the performance of the system. The performance parameters were the shell-side heat transfer coefficient and the total pressure drop. The range of the shell side mass flow rates is shown in Table 3. Fig. 14A shows the change in the shell-side heat transfer coefficient with the mass flow rate of the shell-side fluid and different baffle configurations. The results demonstrated that increasing the mass flow rate increased the shell-side heat transfer coefficient. This coefficient for the noncontinuous-type baffle was higher than that for the continuous baffle type. This was because the baffle spacing of the continuous baffle type was higher than that of the noncontinuous baffle. Thus the shell-side heat transfer coefficient of the continuous baffle was lower than that of the noncontinuous baffle. In addition, increasing the mass flow rate increased the velocity of the shell-side fluid and the Reynolds number of the shell-side; hence the heat transfer coefficient of the shell side increased. Fig. 14B presents the change in the total pressure drop with the mass flow rate of the shell-side fluid and different baffle configurations. The total pressure drop of the continuous baffle type was higher than that of the noncontinuous baffle type. The total pressure drop of the noncontinuous baffle type was the highest among all of the types. This trend occurred mainly because the mass flow rate of the shellside fluid and the shell-side mass velocity increased; thus the pressure drop increased.

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FIGURE 12 Effect of the tube length on the (A) shell side heat transfer coefficient and (B) total pressure drop of the system for different helix angles with continuous-type heat exchanger.

Fig. 15A illustrates the changes in shell-side heat transfer coefficient with the shell-side mass flow rate and different helix angles for the continuous baffle type. Increasing the helix angle decreased the shell-side heat transfer coefficient. This happened because the Reynolds number of the shell side increased with a decrease in the helix angles. On the other hand, Fig. 15B shows the change in the total pressure drop for the shell-side mass flow rate and different helix angles in continuous helical baffles. Increasing the helix angle decreased the total pressure drop of the system. As the helix angle increased, the baffle spacing increased; thus the total pressure drop decreased. Fig. 16A presents the change in the shell-side heat transfer coefficient for the shell-side mass flow rate and different helix angles for noncontinuous helical baffles. Decreasing the helix angle increased the shell-side heat transfer coefficient. On the other hand, Fig. 16B shows the pressure drop of the system versus the shell side mass flow rate for the noncontinuous baffle type. The total pressure drop decreased with an increase in the helix angle. However, when the helix angle was between 45 and 60 degrees, the total pressure drop for each helix angle were close to each other in value.

4.2.4 Effect of Solar Radiation on the Performance of the System This section presents the effect of solar radiation on the performance of the system. Solar radiation was selected considering the minimum and maximum values in Turkey. The minimum and maximum

4. RESULTS AND DISCUSSIONS

297

FIGURE 13 Effect of the tube length on the (A) shell-side heat transfer coefficient and (B) total pressure drop of the system for different helix angles with noncontinuous-type heat exchanger.

values of solar radiation are shown in Table 3. The change in the shell-side heat transfer coefficient and the total pressure drop with respect to solar radiation according to different baffle configurations are presented and discussed in Fig. 17A and B, respectively. Fig. 17A shows the change in solar radiation with respect to the shell-side heat transfer coefficient according to different baffle configurations. Increasing the solar radiation decreased the shell-side heat transfer coefficient. This occurred mainly because when the solar radiation increased, the outlet temperature of the PTSC fluid increased and the thermophysical properties of the fluid, such as viscosity, density, and conductivity, increased. Hence, the shell-side heat transfer coefficient decreased. On the other hand, with the same solar irradiation, the shell-side heat transfer coefficient of the noncontinuous type baffle was higher than for the other baffle types of the shell and tube heat exchanger. Fig. 17B shows the effect of solar radiation on the total pressure drop of the system according to the different types of baffle. When the noncontinuous baffle was used, the total pressure drop was the highest. On the other hand, increasing the solar radiation decreased the total pressure drop. As the solar radiation increased, the outlet temperature of the PTSC side fluid increased; thus the density of PTSC fluid and the rate of viscosities (fshell) increased. Therefore, the total pressure drop decreased. In addition, when the solar radiation was approximately 970 W/m2, the total pressure drop of the segmental and continuous baffle types were close to each other.

FIGURE 14 Effect of the shell-side mass flow rate on the (A) shell-side heat transfer coefficient and (B) total pressure drop of the system for different baffle configurations.

FIGURE 15 Effect of shell-side mass flow rate on (A) shell side heat transfer coefficient (B) the total pressure drop for continuous baffle type for different helix angles.

4. RESULTS AND DISCUSSIONS

299

FIGURE 16 Effect of the shell side mass flow rate on the (A) shell-side heat transfer coefficient and (B) the total pressure drop for noncontinuous baffle type for different helix angles.

4.2.5 Results for the Exergetic Performance Assessment This section presents the exergetic performance of the shell and tube heat exchanger for different mass flow rates of the shell-side fluid, the working fluid types, and the solar radiation values. Fig. 18 shows the change in exergetic efficiency for different values of the mass flow rate of the shell-side fluid. When the mass flow rate of the shell-side fluid increased, the exergetic efficiency of the heat exchanger increased. However, when the mass flow rate of the shell-side fluid was higher than 40 kg/s, the exergetic efficiency of the heat exchanger remained almost constant. This was because the change in the outlet temperature of the cold fluid remained almost constant with a further increase in the mass flow rate of the shell-side fluid. Fig. 19 shows the effect of different PTSC fluids on the exergetic efficiency of the heat exchanger. When Syltherm XLT was used as a PTSC fluid in the integrated system, the exergetic efficiency of the heat exchanger had the highest value. This trend was mainly related to the favorable thermophysical properties of the fluid at this temperature range. However, Syltherm XLT can be used up to 260
C. If the system is operating at a high temperature, Dowtherm Q and Therminol VP1 should be used. Fig. 20 shows the change in exergetic efficiency for solar radiation and different shell-side heat transfer fluids. Apart from Syltherm XLT, the exergetic efficiency of each fluids increased with an

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FIGURE 17 Effect of solar radiation on the (A) shell-side heat transfer coefficient and (B) total pressure drop of the system for different baffle configurations.

FIGURE 18 Effect of the mass flow rate of the shell-side fluid on the exergetic efficiency of the heat exchanger.

5. CONCLUSIONS

301

FIGURE 19 Effect of different parabolic trough solar collector fluids on the exergetic efficiency of the heat exchanger.

FIGURE 20 Effect of solar radiation on the exergetic efficiency of the heat exchanger for different parabolic trough solar collector fluids.

increase in solar radiation. However, this efficiency for Syltherm XLT decreased with an increase in solar irradiation. This occurred because when the outlet temperature of the cold fluid (or PTSC fluid) is high, Syltherm XLT does not have favorable thermophysical properties. Hence, this fluid should not be selected for high-temperature applications. If the system is operating at high temperatures, Therminol VP1 and Dowtherm Q should be selected. In addition, Dowtherm T behaves more steadily with an increase in solar radiation.

5. CONCLUSIONS In this chapter, the thermal design and analysis of a shell and tube heat exchanger, which integrates a PTSC and an ORC system, were performed. For this purpose, thermal models of PTSC and the heat exchanger were first formed and then solved in EES for a case study. Parametric studies were conducted to find the shell-side heat transfer coefficient and the total pressure drop of the system. In

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addition, a performance assessment was presented for three different baffle configurations: segmental, continuous, and noncontinuous. Furthermore, an exergy assessment was conducted. The effects of solar radiation and the different working fluids on the exergetic efficiency of the shell and tube heat exchanger were investigated. The major conclusions of the study are that: • •

• • •

• •

•

The outer tube diameter does not have a significant effect on the pressure drop. However, increasing the diameter decreases the overall heat transfer coefficient. If baffle spacing decreases, the Reynolds number of the shell side increases and the flow regime might become turbulent. Thus, the overall heat transfer coefficient increases as the spacing decreases. If baffle spacing is between 0.08 and 1.5 m, the overall heat transfer coefficient decreases from 1040 to 115 W/m2 K. The parametric studies showed that if the tube layout angle is 30 or 60 degrees instead of 45 or 90 degrees, the overall heat transfer coefficient and total pressure drop both increase. The number of passes does not have a significant effect on the overall heat transfer coefficient and the pressure drop. When the tube length is between 2 and 4 m, the total pressure drop of the continuous baffle type is about 8.74% lower than that of the segmental baffle type. In addition, lower values of the tube length are selected to design the heat exchanger. The helix angle has a significant effect on the performance of the shell and tube heat exchanger. A 15-degree helix angle possesses the best performance among the different types studied. Noncontinuous baffle type heat exchangers are preferred because the shell-side heat transfer coefficient is the highest. However, it is difficult to manufacture this type of heat exchanger. Thus, continuous baffle-type heat exchangers may be preferable. When Syltherm XLT is used as the PTSC fluid in the integrated system, the exergetic efficiency of the heat exchanger has the highest value.

The results of this chapter are expected to guide researchers, heat exchanger designers, power plant managers, and engineers in designing more efficient solar-geothermal heat exchangers.

NOMENCLATURE Aa As Ar cp D Ds _ f Ex e F ffric g Gb h hc,ga hfi

Aperture area (m2) Cross-sectional area of the shell perpendicular to the direction of flow (m2) Receiver area (m2) Specific heat capacity (kJ/kg K) Diameter (m) Shell diameter (m) Flow exergy (kW) Baffle spacing (m) Correction factor Friction factor Gravitational acceleration (m/s2) Solar radiation (W/m2) Heat transfer coefficient (W/m2K), enthalpy (kJ/kg) Convective heat transfer coefficient for glass cover to ambient temperature (W/m2 K) Heat transfer coefficient of inside receiver tube (W/m2 K)

NOMENCLATURE

hi hloss ho hr,ga hr,rg k L m_ Nb npass NPTSC Nt Pr Pt Q_ Q_u 00 Rf Re s S T U UL V DTlm DPtotal DPPTSC DPshell

Tube-side heat transfer coefficient (W/m2 K) Head loss (m) Shell-side heat transfer coefficient (W/m2 K) Radiative heat transfer coefficient for glass cover to ambient temperature (W/m2 K) Radiative heat transfer coefficient for glass cover (W/m2 K) Thermal conductivity (W/m K) Single collector length (m), length of heat exchanger (m) Mass flow rate (kg/s) Number of baffles Number of passes Number of PTSCs Number of tubes Prandtl number Tube pitch (m) Heat transfer rate (W) Rate of useful energy gain delivered by collectors (W) Fouling factor (m2 K/W) Reynolds number Specific entropy (kJ/kg K) Heat absorbed by receiver (W/m2) Temperature (K) Overall heat transfer coefficient (W/m2 K) Heat loss coefficient for solar collector (W/m2 K) Velocity (m/s) Logarithmic mean temperature difference (K) Total pressure drop (kPa) PTSC side pressure drop (kPa) Shell-side pressure drop (kPa)

Greek Symbols

a b g ε hex K m r s so

Absorptivity Helix angle (degrees) Specific weight (N/m3) Emissivity Exergetic efficiency Incidence angle modifier Viscosity Reflectance of mirror, density (kg/m3) StefaneBoltzmann constant (W/m2 K4) Transmittance of glass cover

Subscripts a b c e fric g

Ambient, aperture Bulk Cold Equivalent Friction Glass cover

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h i o otl r s sur w 0

Hot Inner, inlet Outer, outlet Outer tube limit Receiver Surface Surroundings Wall Dead state

Abbreviations CL EES ORC PTSC

Tube layout constant Engineering Equation Solver Organic Rankine cycle Parabolic trough solar collector

REFERENCES [1] Zhang J, He Y, Tao W. 3D numerical simulation on shell-and-tube heat exchangers with middle-overlapped helical baffles and continuous baffles e Part II : simulation results of periodic model and comparison between continuous and noncontinuous helical baffles. International Journal of Heat and Mass Transfer 2009;52:5381e9. http://dx.doi.org/10.1016/j.ijheatmasstransfer.2009.07.007. [2] Shah RK, Sekulic DP. Fundamentals of heat exchanger design. 1st ed. John Wiley & Sons, Ltd; 2002. http:// dx.doi.org/10.1007/BF00740254. [3] Zhang J, He Y, Tao W. 3D numerical simulation on shell-and-tube heat exchangers with middle-overlapped helical baffles and continuous baffles e Part I : numerical model and results of whole heat exchanger with middle-overlapped helical baffles. International Journal of Heat and Mass Transfer 2009;52:5371e80. http:// dx.doi.org/10.1016/j.ijheatmasstransfer.2009.07.006. [4] Parikshit B, Spandana KR, Krishna V, Seetharam TR, Seetharamu KN. A simple method to calculate shell side fluid pressure drop in a shell and tube heat exchanger. International Journal of Heat and Mass Transfer 2015;84:700e12. http://dx.doi.org/10.1016/j.ijheatmasstransfer.2015.01.068. [5] Zeyninejad S, Nemati F, Razmi K, Tasouji R. Tube bundle replacement for segmental and helical shell and tube heat exchangers : performance comparison and fouling investigation on the shell side. Applied Thermal Engineering 2013;51:1162e9. http://dx.doi.org/10.1016/j.applthermaleng.2012.10.025. [6] Mukherjee R. Effectively design shell-and-tube heat exchangers. Chemical Engineering Progress 1998; 94(2):21e37. [7] Lutcha J, Nemcansky J. Performance improvement of tubular heat exchangers by helical baffles. Chemical Engineering Research and Design n.d.;68:263e270. [8] Lei Y, He Y, Chu P, Li R. Design and optimization of heat exchangers with helical baffles. Chemical Engineering Science 2008;63:4386e95. http://dx.doi.org/10.1016/j.ces.2008.05.044. [9] Yang J, Zeng M, Wang Q. Numerical investigation on combined single shell-pass shell-and-tube heat exchanger with two-layer continuous helical baffles. International Journal of Heat and Mass Transfer 2015; 84:103e13. http://dx.doi.org/10.1016/j.ijheatmasstransfer.2014.12.042. [10] Nakaso K, Mitani H, Fukai J. Convection heat transfer in a shell-and-tube heat exchanger using sheet fins for effective utilization of energy. International Journal of Heat and Mass Transfer 2015;82:581e7. http:// dx.doi.org/10.1016/j.ijheatmasstransfer.2014.11.033. [11] Wang Q, Chen Q, Chen G, Zeng M. Numerical investigation on combined multiple shell-pass shell-and-tube heat exchanger with continuous helical baffles. International Journal of Heat and Mass Transfer 2009;52: 1214e22. http://dx.doi.org/10.1016/j.ijheatmasstransfer.2008.09.009.

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´ , Almanza R. Solaregeothermal hybrid system. Applied Thermal Engineering 2006;26:1537e44. [12] Lentz A http://dx.doi.org/10.1016/j.applthermaleng.2005.12.008. [13] Kalogirou S. Solar thermal collectors and applications. Progress in Energy and Combustion Science 2004; 30. http://dx.doi.org/10.1016/j.pecs.2004.02.001. [14] Kalogirou S. Solar energy engineering processes and systems. Elsevier Inc.; 2009. http://dx.doi.org/10.1016/ B978-0-12-374501-9.00014-5. [15] Al-Sulaiman FA. Exergy analysis of parabolic trough solar collectors integrated with combined steam and organic Rankine cycles. Energy Conversion and Management 2014;77:441e9. http://dx.doi.org/10.1016/ j.enconman.2013.10.013. [16] Kalogirou S. Parabolic trough collector system for low temperature steam generation: design and performance characteristics. Applied Energy 1996;55:1e19. http://dx.doi.org/10.1016/S0306-2619(96)00008-6. [17] Odeh SD, Morrison GL, Behnia M. Modelling of parabolic trough direct steam generation solar collectors. Solar Energy 1998;62:395e406. http://dx.doi.org/10.1016/S0038-092X(98)00031-0. [18] Herrmann U, Kelly B, Price H. Two-tank molten salt storage for parabolic trough solar power plants. Energy 2004;29:883e93. http://dx.doi.org/10.1016/S0360-5442(03)00193-2. [19] Brooks MJ, Mills I, Harms TM. Performance of a parabolic trough solar collector. Journal of Energy in Southern Africa 2005;17:71e80. [20] Brooks M, Mills I, Harms T. Design, construction and testing of a parabolic trough solar collector for a developing-country application. In: Proc. ISES Sol. World Congr. Orlando, FL; 2005. [21] Qu M, Archer DH, Masson SV. A linear parabolic trough solar collector performance model. Renewable Energy Resources and a Greener Future 2006;8. http://dx.doi.org/10.4017/gt.2006.05.04.024.00. [22] Patnode A. Simulation and performance evaluation of parabolic trough solar power plants. University of Wisconsin-Madison; 2006. [23] Duffie J, Beckman W. Solar engineering of thermal processes. Wiley; 2013. [24] Harrison J. Standards of the Tubular Exchangers Manufacturers Association. 8th ed. New York: Tubular Exchangers Manufacturers Association; 2007. [25] Kakac¸ S, Liu H, Pramuanjaroenkij A. Heat exchangers: selection, rating, and thermal design. 2nd ed. CRC Press; 2002. http://dx.doi.org/10.1016/0378-3820(89)90046-5. [26] White FM. Fluid mechanics. 7th ed., vol. 1. Mc Graw Hill; 2009. http://dx.doi.org/10.1017/ CBO9781107415324.004. [27] Fettaka S, Thibault J, Gupta Y. Design of shell-and-tube heat exchangers using multiobjective optimization. International Journal of Heat and Mass Transfer 2013;60:343e54. http://dx.doi.org/10.1016/ j.ijheatmasstransfer.2012.12.047. [28] Incropera FP, Bergman TL, Lavine AS. Fundamentals of heat and mass transfer. 7th ed. Wiley; 2012.

CHAPTER

CFD ANALYSIS OF A SOLAR-GEOTHERMAL SHELL AND TUBE HEAT EXCHANGER

2.5

David Ouellette1,2, Anil Erdogan1, C. Ozgur Colpan1 _ Dokuz Eylul University, Izmir, Turkey1; University of Toronto, Toronto, ON, Canada2

1. INTRODUCTION Heat exchangers are devices that transfer heat from one medium to another (e.g., between two fluids) and are classified according to flow regulation, number of fluids, surface compactness, and construction geometry (tubular, plate, finned, and compact) [1]. A common heat exchanger type is the shell and tube heat exchanger (STHX), which is a type of tubular heat exchanger. The design of this heat exchanger consists of a bank of tubes assembled inside a shell. Baffles are placed inside the shell to provide flow regulation [1]. The STHX is widely used in steam and power cycle plants; heating, ventilating, and cooling (HVAC) systems; and chemical and food processing. There are many reasons for the widespread use of the STHX. For instance, high temperature and pressure operations are possible, tube leaks can be easily located, and the design facilitates the selection of materials during manufacturing. However, the STHX requires more space than other heat exchanger types, which makes cleaning and maintenance more difficult in large-scale applications. The STHX can be classified according to different parameters (e.g., number of tubes and shells, tube layout angle, and baffle types). Fig. 1 shows classification of the STHXs according to the number of tube passes. Fig. 1A shows a single tube pass, Fig. 1B shows two tube passes, and Fig. 1C shows three tube passes. In the literature, several computational fluid dynamic (CFD) studies on STHXs have been conducted [1e15]. The majority of these studies focused on how different STHX geometries (e.g., multishell designs [4,7,8], integration of phase change materials [13], oval-shaped tubes [14]), and baffle designs (e.g., trefoil [2], helical [6,9,10,12], and sheet fins [11]) affect the STHX’s thermohydraulic performance, along with the development and applicability of different heat transfer coefficients and correlations (e.g., Bell and Delaware method) [3], and numerical and discretization methodologies (e.g., realizable k-ε turbulence model with first-order discretization [3,5,14]) to model the STHX. From these advances, several authors have developed STHXs for use in solar organic Rankine cycles (ORCs). An example of such a system is shown in Fig. 2. In this system, the heat input for the Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00017-2 Copyright © 2018 Elsevier Inc. All rights reserved.

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FIGURE 1 The types of shell and tube heat exchangers: (A) one tube pass, (B) two tube passes, and (C) three tube passes.

ORC is obtained from the concentrated solar energy from a series of solar collectors (e.g., parabolic trough solar collector). The heat from this working fluid is transferred to the working fluid within the ORC through use of an HX (e.g., STHX). To help increase the thermal efficiency of the cycle, a geothermal cycle can be integrated to the ORC to help preheat the ORC’s working fluid before it enters the solar geothermal HX. Examples of studies that have examined STHXs in such a system (shown in Fig. 2), include Refs. [16,17]. These studies focused on the effects that the choice of working fluid (e.g., R123, R134a, R141b, R245fa, R600, Therminol VP1, and Dowtherm A) and STHX design (e.g., outer tube diameter, tube length and baffle spacing) have on the thermoeconomics and exergetic efficiency of the STHX. However, it should be noted that these studies used a low-dimensional modeling methodology that does not capture the detailed thermohydraulic processes within the STHX. Therefore, to help remedy this situation, a three-dimensional (3D) model of an STHX was developed and reported in this work, with particular application to the system shown in Fig. 2.

2. MODELING

309

FIGURE 2 Schematic of a typical solar-geothermal power plant. The heat exchanger in the dashed box represents the unit examined in this work.

The model was developed in a COMSOL Multiphysics environment. The simulated results presented in this study focus on the temperature and velocity variations within the shell and tubes of the STHX for different inlet shell-side mass flow rates. These results are subsequently used to identify the energetic and exergetic performance of the heat exchanger (i.e., heat exchanger effectiveness, heat transfer rate, and exergetic efficiency).

2. MODELING 2.1 MODEL DOMAIN AND INPUT PARAMETERS The STHX analyzed in this study is the component that couples the parabolic trough solar collector (PTSC) and ORC loops together. In this configuration, Therminol VP1 is heated by the PTSCs and passed through the shell of the STHX. The R134a is heated by a separate heat exchanger that is connected to a geothermal reservoir, and the R134a is passed through the tubes of the heat exchanger, in a counterflow configuration with the Therminol VP1 (shell-side fluid). This process preheats the R134a, which is subsequently passed to an ORC for electrical energy generation. A schematic of this single-pass heat exchanger is shown in Fig. 3, which has been shortened in length for clarity. Due to the symmetry of the problem, only half of the heat exchanger is considered. The shell and tubes are considered to be composed of stainless steel, and the height of the shell’s evenly spaced baffles are considered to be equal to the shell’s radius. The dimensions, material properties, and operating conditions of this heat exchanger are provided in Table 1.

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FIGURE 3 Schematic of a repeating segment of the shell and tube heat exchanger geometry that is 1/12 of the total length of the heat exchanger. (A) Shows the COMSOL model, (B) shows a simplified 2D schematic of the domain.

2.2 MODEL ASSUMPTIONS AND GOVERNING EQUATIONS To model the 3D STHX, the following assumptions were considered: • • • • • •

The heat exchanger operates under steady-state conditions. The shell walls are well insulated (adiabatic). Both working fluids are Newtonian, and their thermophysical properties are taken as constant. The shell-side and the tube-side flows are turbulent and can be modeled using the realizable k-ε model. The baffles and tube walls are sufficiently thin to be treated as interfaces imposing a conductive thermal resistance to the flow. Viscous heating and pressure force effects are neglected.

Considering these assumptions, the hydrodynamics of the heat exchanger are modeled using the conservation of mass, momentum, energy, kinetic energy, and energy dissipation equationsdthe realizable k-ε model. These equations are provided in this section [18,19]. To begin the discussion, the flow field’s mean velocity, pressure, and temperatures are calculated from the conservation of mass, momentum, and energy, given by Eqs. (1)e(3), shown here: rðV$uÞ ¼ 0

(1)

2. MODELING

311

Table 1 Input Parameters for the Solar-Geothermal Heat Exchanger [17,20] Name of the Parameter

Value

Units

Therminol VP1 0.1306 27.5 563 63.9

e m kg/s K W/m K

R134a 12 0.016 0.0015 0.0254 90 1 420.7 213.368 63.9

e m m m m degree e K kg/s W/m K

0.5 0.003 63.9

m m W/m K

101.3 298

kPa K

Shell Working fluid Shell diameter Mass flow rate Outlet temperature Thermal conductivity Tube Working fluid Tube length Inside diameter Wall thickness Pitch Layout angle Number of passes Inlet temperature Mass flow rate Thermal conductivity Baffle Spacing Thickness Thermal conductivity Exergetic Properties Dead-state pressure Dead-state temperature






ruðV$uÞ ¼ V$  pI þ meff Vu þ ðVuÞ rucp ðVTÞ ¼ V$½leff ðVTÞ

T

 2  rkI 3

(2) (3)

Here, r is the fluid’s mass density, u is the fluid’s velocity vector, p is the pressure, I is the identity matrix, meff is the effective (intrinsic plus turbulent) dynamic viscosity, k is the turbulent kinetic energy, cp is the specific heat at constant pressure, T is the temperature, and leff is the effective (intrinsic plus turbulent) thermal conductivity. The effective dynamic viscosity and thermal conductivity are given by Eqs. (4) and (5). The subscripts l and t in these equations refer to the liquid state and turbulent properties, respectively. leff ¼ ll þ lt

(4)

meff ¼ ml þ mt

(5)

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CHAPTER 2.5 CFD ANALYSIS OF A SOLAR-GEOTHERMAL SHELL AND TUBE HEAT

Table 2 Summary of the k-ε Model Constants [19,21] k-ε Model Constants

Values

Cm Cε1 Cε2 sK sε kV

0.09 1.44 1.92 1.00 1.30 0.41

The turbulent thermal conductivity and dynamic viscosity are calculated using Eqs. (6) and (7), respectively. These are obtained from the KayseCrawford equation and the k-ε model, respectively. The turbulent Prandtl number at infinity, PrTN , is taken as 0.85 [18]. " !!#1 pffiffiffiffiffiffiffiffiffi   PrTN Cp mT C p mT 2 1 0:3 Cp mT l  0:3 PrT ¼ ¼ þ pffiffiffiffiffiffiffiffiffi 1  exp  2$PrTN 0:3 0:3Cp mT lT l PrTN l (6) mT ¼ rCm

k2

(7) ε To determine the fluids’ turbulent kinetic energy, k, and energy dissipation, ε, the following equations are applied.
   mT rkðu$VÞ ¼ V$ m þ (8) ðVkÞ þ Pk  rε sK
   mT ε ε2 rεðu$VÞ ¼ V$ m þ (9) ðVεÞ þ Cε1 Pk  Cε2 r k sε k The k-ε model constants (Cm , Cε1 , Cε2 , sK , and sε ) are summarized in Table 2, whereas the turbulent kinetic energy production rate, Pk , is calculated using Eq. (10).
  2 2 T 2 (10) Pk ¼ mT ðVuÞ: ðVuÞ þ ðVuÞ  ðV$uÞ  rkðV$uÞ 3 3

2.3 EXERGETIC AND HEAT EXCHANGER EFFECTIVENESS CALCULATIONS The exergetic efficiency, hex , and the effectiveness of the STHX, ε, can be calculated using Eqs. (11) and (12), respectively.    

m_ t ht;o  ht;i  T0 st;o  st;i   

hex ¼  (11) m_ s hs;i  hs;o  T0 ss;i  ss;o ε¼

Q_ Q_max

(12)

2. MODELING

313

Here, m_ is the mass flow rate of the working fluids, h and s are the enthalpy and entropy of the working fluids (obtained from Engineering Equation Solver, EES), T0 is the temperature of the dead state, whereas the subscripts t and s refer to the working fluids of the tube and shell, respectively, and i and o refer to the conditions at the inlet and outlet of the respective working fluid within the STHX. The total and maximum rates of heat transfer within the STHX, Q_ and Q_max , can be calculated using Eqs. (13) and (14), respectively.   (13) Q_ ¼ m_ s $ hs;i  hs;o Q_max ¼ C_min DTmax

(14)

Here, C_min and DTmax are the minimum heat capacity and the maximum temperature difference within the heat exchanger. These are given by Eqs. (15) and (16). The subscripts h and c refer to the conditions of the hot and cold fluids (Therminol VP1 and R134a), respectively. _ P Þmin C_min ¼ ðmc

(15)

DTmax ¼ Th;i  Tc;i

(16)

2.4 INLET AND BOUNDARY CONDITIONS The velocity inlets of the tubes and shells were specified with a known mass flow rate, m_ inlet . The kinetic energy and energy dissipation at the inlets are calculated based off of the flow’s incoming turbulence intensity, IT (considered to be 0.05). And the energy equation is treated with a constant and known inlet temperature, T0. These conditions are given by Eqs. (17aed), respectively. Z m_ inlet ¼ rðuinlet $nÞdA (17a) 3 kinlet ¼ ðjujIT Þ2 2

(17b)

3=2

εinlet ¼ Cm3=4

kinlet LT

Tinlet ¼ T0

(17c) (17d)

Here, n is the normal vector, A is the surface area, and LT is the turbulence length scale (considered to be 0.01 m). The outlets are treated with a specified zero-gauge pressure boundary condition, Poutlet , and standard outlet (convective) boundary conditions, given by Eqs. (18a and b). Here, f is an arbitrary variable (i.e., energy dissipation, kinetic energy, stress, and temperature). The symmetry condition on the midplane of the heat exchanger, as shown in Fig. 3, uses the same form of boundary condition shown in Eq. (18b). 
  2  pI þ meff Vu þ ðVuÞT  rkI $n ¼ 0 (18a) 3 outlet ðVfÞ$n ¼ 0

(18b)

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CHAPTER 2.5 CFD ANALYSIS OF A SOLAR-GEOTHERMAL SHELL AND TUBE HEAT

All walls (shell, tube, and baffles) were specified with no slip for smooth walls and impermeable wall conditions, as given by Eqs. (19a and b).


u$n ¼ 0



  2 us  pI þ meff Vu þ ðVuÞT  rkI n ¼ r þ utang 3 dw

(19a) (19b)

The corresponding stress, given by the right-hand side of Eq. (19b), is composed of the friction velocity, us , the nondimensional position normal to the wall’s surface, dþ w , and the tangential velocity, utang . The us and dþ are obtained from standard wall functions (which is also true for all quantities w near-wall), whereas utang is obtained from Eq. (19c). utang ¼ u  ðu$nÞn

(19c)

The kinetic energy and energy dissipation are treated with the conditions given by Eqs. (19d and e), respectively, which are a homogeneous Neumann condition and based off of the standard wall functions, respectively. ðVkÞ$n ¼ 0 ε¼r

k2

Cm mkV dþ w

(19d) (19e)

Furthermore, the baffles and tube walls are considered numerically, as interfaces. However, to account for their presence in the heat transfer model, they are treated as standard thermal resistances. The shell wall is also considered thermally insulated, given by Eq. (20). ½  leff ðVTÞ$n ¼ 0

(20)

2.5 MESH GENERATION AND SOLUTION PROCEDURE In this study, COMSOL Multiphysics 5.0, a commercially available finite element solver, is used to solve the equations discussed earlier. After entering all the necessary equations using the software’s built-in modules (“Turbulent Flow, k-ε”, and “Heat Transfer in Fluids”), the mesh is generated for the geometry. Tetrahedral elements are used to mesh the shell and tubes, with increase resolution imposed at the walls to capture the hydraulic boundary layers. A total of w8.5 million elements are used to mesh the geometry in this study. Three different segregated groups (pressure and velocity [P and u], temperature [T], and kinetic energy [k] and energy dissipation [ε]) are set up to solve each set of the equations, each using the multifrontal massively parallel sparse (MUMPS) direct solver. The solution progresses until the residuals fall below 104. To ensure a robust solution, underrelaxation is applied to each segregated step, and the kinetic energy and energy dissipation variables are considered to be greater than zero. Furthermore, to prevent excessive turbulence production in the limit where k/0 (see Eq. 9), a mixing length limiter is introduced, as given by Eqs. (21) and (22). Here, lmix;max is the maximum mixing length and S is the strain rate vector, given by Eq. (23). The derivation of this limiter is provided in Ref. [18].

3. RESULTS AND DISCUSSIONS

lmix

k1=2 ; lmix;max ¼ max Cm ε sffiffiffiffiffiffiffiffiffiffiffiffiffiffi k lmix;max  6ðS$SÞ S¼

1 ðVuÞ þ ðVuÞT 2

315

! (21)

(22) (23)

3. RESULTS AND DISCUSSIONS In this section, the temperature and velocity distributions for different shell-side mass flow rates (28, 55, and 138 kg/s) are compared and the energetic and exergetic performance of the heat exchanger is reported and discussed.

3.1 THE EFFECT OF THE SHELL-SIDE MASS FLOW RATE ON THE STHX’S VELOCITY AND TEMPERATURE DISTRIBUTIONS Beginning with the velocity variation within the STHX shown in Fig. 4, it can be seen that the velocity and velocity variations of the shell-side fluid increased linearly with increasing inlet mass flow rates. For instance, the standard deviation in the velocity variations in each case was 3.7, 7.4, and 13 m/s, for the 28, 55, and 138 kg/s cases, respectively. These velocity variations primarily occurred due to the

FIGURE 4 The velocity magnitude variation of the shell-side fluid, for different inlet shell-side mass flow rates, with respect to the axial position along the midplane of the HX.

316

CHAPTER 2.5 CFD ANALYSIS OF A SOLAR-GEOTHERMAL SHELL AND TUBE HEAT

FIGURE 5 The normalized velocity distribution (juj/uinlet) within the shell, along the midplane. The axial position under consideration is from 2.5 to 3.5 m along the shell.

shell-side fluid passing across the baffles within the shell. However, the detailed explanation of the observed fluctuations in the velocity field can be explained as follows. As the bulk flow approaches a baffle, the velocity begins to sharply increase due to the smaller cross-sectional area. Directly after this baffle, the cross-sectional area for the flow decreases, causing a sharp decrease in velocity. Due to the sharp differences in the fluid’s shear stress distribution, from above to behind the baffle, this causes a recirculation zone to appear. This recirculation can be seen by the “low velocity pocket” (the bluecolored zone behind each of the baffles in Fig. 5). This recirculation causes fluctuations to occur within the bulk flow. However, as this recirculation zone is entrained into the bulk flow, the linear velocity of the bulk flow begins to decrease. At this point, the fluid is near the next baffle, and the process repeats. There also a few important features of the flow that should be noted. For instance, as the flow crosses a baffle, the velocity at the baffle, especially near the baffle-wall interface on both sides of the baffle, will stagnate. This will cause poor mixing, causing the flow to have a nonuniform temperature distribution. As such, HX designs should be careful to avoid such flow conditions. One possible route would be the inclusion of helical baffles as examined in Refs. [6,9,10,12]. From this velocity distribution, the STHX’s temperature distribution will be better understood. The temperature distribution of the shell-side fluid along the length of the STHX is shown in Fig. 6. As can

FIGURE 6 The temperature variation of the shell-side fluid along the symmetry lane of the STHX.

3. RESULTS AND DISCUSSIONS

317

FIGURE 7 The temperature distribution, in  C, within the shell, along the midplane for an axial position from 2.5 to 3.5 m along the shell. The subfigures (AeC) refer to the inlet mass flow rate cases of (A) 28 kg/s, (B) 55 kg/s, and (C) 138 kg/s.

be seen, as the flow rate is increased the temperature difference, DT, across the shell-side fluid decreases (DT ¼ 133, 114 and 78.0 C, for the 28, 55, and 138 kg/s cases, respectively). There are also temperature fluctuations along the shell’s length (w10 C each) due to the conductive thermal resistance imposed by the baffles. Furthermore, the recirculation zones behind each of the baffles, as shown in Fig. 5 and discussed in the previous paragraph, shrink as the bulk fluid travels along the length of the STHX because of the entrainment of the lower velocity recirculated fluid. This allows the colder recirculated fluid to mix with the hot bulk fluid. This causes the average fluid temperature to increase. This distribution can be seen in the temperature contour plot in Fig. 7.

3.2 THE RATE OF HEAT TRANSFER, EXERGETIC EFFICIENCY, AND HEAT EXCHANGER EFFECTIVENESS FOR DIFFERENT SHELL-SIDE MASS FLOW RATES The effects of different shell-side mass flow rates on the heat transfer, exergetic efficiency, and the heat exchanger effectiveness are shown in Figs. 8 and 9, respectively. Fig. 8 shows the change of shell-side mass flow rate with respect to the amount of heat transfer and shell-side pressure drop. As can be seen from Fig. 8 increasing the shell-side mass flow rate, increased the heat transfer between the shell-side and tube side fluid, and the pressure drop between the inlet and outlet of the shell-side. When the shell-side mass flow rate increases 28 to 138 kg/s, the heat transfer increases 7.61e29.8 MW whereas the shell-side pressure drops 2.00e49.4 MPa. This heat transfer increase is due to the increase of the mass flow rate of shell-side fluid, and the increase of the outlet temperatures of the both side fluids. Hence, the increase of enthalpy with the amount of heat transfer increases. In Fig. 9, the effect of the shell-side mass flow rate on exergetic efficiency is investigated. As can be seen in this figure, the shell-side mass flow rate increases with the increase of exergetic efficiency of the heat exchanger. When the mass flow rate of the shell-side fluid increases, the exergetic efficiency increases by 8.50%e57.2%. This trend occurs because as the shell-side mass flow rate increases, so do the outlet temperatures of the shell’s and the tubes’ fluids. In turn, this causes the fluids’ enthalpy, entropy, and flow exergy to increase. This allows the exergetic efficiency of the heat exchanger to increase. On the other hand, the reason for the increasing shell-side pressure drop is primarily the increasing mass flow rate and due to the presence of the baffles. These baffles cause obstructions to the

318

CHAPTER 2.5 CFD ANALYSIS OF A SOLAR-GEOTHERMAL SHELL AND TUBE HEAT

FIGURE 8 The effect of mass flow rate of shell-side fluid on the heat transfer and shell-side pressure drop.

FIGURE 9 The effect of mass flow rate of shell-side fluid on the exergetic efficiency (left y-axis) and the heat exchanger effectiveness (right y-axis).

NOMENCLATURE

319

flow, forcing the fluid to turn around and to recirculate behind the baffles. Additional pumping power is required to maintain such mass flow rates. As shown in Fig. 9, the effect of the shell-side mass flow rate on the heat exchanger effectiveness is given. Increasing the shell-side mass flow rate decreases the effectiveness of the heat exchanger. This trend is due to increasing the outlet temperature of the shelland tube-side fluids, and the maximum amount of the heat transfer increases. Thus, the heat exchanger effectiveness decreases. For these trends in Fig. 9, when the shell-side mass flow rate is selected as approximately 90 kg/s, the exergetic efficiency and the effectiveness of the heat exchanger of 35% and 76%, respectively, are obtained.

4. CONCLUSIONS A 3D numerical model for shell and tube heat exchanger was formed using the COMSOL Multiphysics environment. Using this model, the temperature distributions of the symmetry plane and along the tube-side flow, and the velocity distributions of the symmetry plane, were given comparatively according to different shell-side mass flow rates. In addition, a computer code was written in EES environment, for the effect of changing the shell-side mass flow rate on the heat transfer between the shell- and tube-side fluids, exergetic efficiency, and the effectiveness of the heat exchanger were examined. The main results of this study include: •

•

• • •

When the shell-side mass flow rate increases by 28 to 138 kg/s, the temperature difference along the heat exchanger decreases. On the other hand, it has also been observed that the fluid velocity increases. When the velocity distribution of the shell-side fluid flow is investigated, it has been determined that there are dead zones on the baffle. To reduce dead zone, and to improve performance of the heat exchanger, the performance improvement studies should be carried out by designing different baffle types. When the shell-side mass flow rate increases 28 to 138 kg/s, the rate of heat transfer increases by 7.61e29.8 MW, and the shell-side pressure drop increases by 2.00e49.4 MPa. When the shell-side mass flow rate increases 28e138 kg/s, the exergetic efficiency increases 8.50%e57.2%, and the heat exchanger effectiveness decreases from 92.0% to 71.4%. When the shell-side mass flow rate is selected as approximately 90 kg/s, the exergetic efficiency and the effectiveness of the heat exchanger are found as 35% and 76%, respectively.

NOMENCLATURE Variables

C_ cp h I IT k lmix

Heat capacity (kW/K) Specific heat at constant pressure (kJ/kg$K) Specific enthalpy (kJ/kg) Identity matrix Turbulence intensity Turbulent kinetic energy (m2/s2) Mixing length (m)

320

CHAPTER 2.5 CFD ANALYSIS OF A SOLAR-GEOTHERMAL SHELL AND TUBE HEAT

LT m_ n p Pk Pr Q_ S s T u ut x

Turbulence length scale (m) Mass flow rate (kg/s) Normal vector Pressure (Pa) Source term Prandtl number Rate of heat transfer (W) Strain rate vector (1/s) Specific entropy (kJ/kg$K) Temperature (K) Velocity (m/s) Friction velocity (m/s) Position (m)

Greek Letters dD w DT ε h kV l m r sK sε f

Nondimensional position normal to the wall’s surface (m) Temperature difference (K) Kinetic energy dissipation (m2/s3), heat exchanger effectiveness () Exergetic efficiency () Von Karman constant Thermal conductivity (W/m K) Kinematic viscosity (Pa s) Density (kg/m3) Turbulent Prandtl number for turbulent kinetic energy Turbulent Prandtl number for turbulent kinetic energy dissipation Arbitrary variable

Subscript 0 eff i Inlet j l max min o s T t

Dead state Effective Fluid types, inlet Inlet value Fluid type Laminar Maximum Minimum Outlet Shell Matrix transpose Turbulent/tube

REFERENCES [1] Zhang J, He Y, Tao W. 3D numerical simulation on shell-and-tube heat exchangers with middle-overlapped helical baffles and continuous baffles e Part I : numerical model and results of whole heat exchanger with middle-overlapped helical baffles. International Journal of Heat and Mass Transfer 2009;52:5371e80. http:// dx.doi.org/10.1016/j.ijheatmasstransfer.2009.07.006.

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[2] You Y, Chen Y, Xie M, Luo X, Jiao L, Huang S. Numerical simulation and performance improvement for a small size shell-and-tube heat exchanger with trefoil-hole baffles. Applied Thermal Engineering 2015;89: 220e8. http://dx.doi.org/10.1016/j.applthermaleng.2015.06.012. [3] Ozden E, Tari I. Shell side CFD analysis of a small shell-and-tube heat exchanger. Energy Conversion and Management 2010;51:1004e14. http://dx.doi.org/10.1016/j.enconman.2009.12.003. [4] Wang X, Zheng N, Liu P, Liu Z, Liu W. Numerical investigation of shell side performance of a double shell side rod baffle heat exchanger. International Journal of Heat and Mass Transfer 2017;108:2029e39. http:// dx.doi.org/10.1016/j.ijheatmasstransfer.2017.01.055. [5] Aslam Bhutta MM, Hayat N, Bashir MH, Khan AR, Ahmad KN, Khan S. CFD applications in various heat exchangers design: a review. Applied Thermal Engineering 2012;32:1e12. http://dx.doi.org/10.1016/ j.applthermaleng.2011.09.001. [6] Zhang J, He Y, Tao W. 3D numerical simulation on shell-and-tube heat exchangers with middle-overlapped helical baffles and continuous baffles e Part II : simulation results of periodic model and comparison between continuous and noncontinuous helical baffles. International Journal of Heat and Mass Transfer 2009; 52:5381e9. http://dx.doi.org/10.1016/j.ijheatmasstransfer.2009.07.007. [7] El Maakoul A, Laknizi A, Saadeddine S, Ben Abdellah A, Meziane M, El Metoui M. Numerical design and investigation of heat transfer enhancement and performance for an annulus with continuous helical baffles in a double-pipe heat exchanger. Energy Conversion and Management 2017;133:76e86. http://dx.doi.org/ 10.1016/j.enconman.2016.12.002. [8] Shahril SM, Quadir GA, Amin NAM, Badruddin IA. Thermo hydraulic performance analysis of a shell-anddouble concentric tube heat exchanger using CFD. International Journal of Heat and Mass Transfer 2017; 105:781e98. http://dx.doi.org/10.1016/j.ijheatmasstransfer.2016.10.021. [9] Jayakumar JS, Mahajani SM, Mandal JC, Vijayan PK, Bhoi R. Experimental and CFD estimation of heat transfer in helically coiled heat exchangers. Chemical Engineering Research and Design 2008;86:221e32. http://dx.doi.org/10.1016/j.cherd.2007.10.021. [10] Lei Y, He Y, Chu P, Li R. Design and optimization of heat exchangers with helical baffles. Chemical Engineering Science 2008;63:4386e95. http://dx.doi.org/10.1016/j.ces.2008.05.044. [11] Nakaso K, Mitani H, Fukai J. Convection heat transfer in a shell-and-tube heat exchanger using sheet fins for effective utilization of energy. International Journal of Heat and Mass Transfer 2015;82:581e7. http:// dx.doi.org/10.1016/j.ijheatmasstransfer.2014.11.033. [12] Nemati Taher F, Zeyninejad Movassag S, Razmi K, Tasouji Azar R. Baffle space impact on the performance of helical baffle shell and tube heat exchangers. Applied Thermal Engineering 2012;44:143e9. http:// dx.doi.org/10.1016/j.applthermaleng.2012.03.042. [13] Hosseini MJ, Rahimi M, Bahrampoury R. Experimental and computational evolution of a shell and tube heat exchanger as a PCM thermal storage system. International Communications in Heat and Mass Transfer 2014; 50:128e36. http://dx.doi.org/10.1016/j.icheatmasstransfer.2013.11.008. [14] Tan X, Zhu D, Zhou G, Yang L. 3D numerical simulation on the shell side heat transfer and pressure drop performances of twisted oval tube heat exchanger. International Journal of Heat and Mass Transfer 2013;65: 244e53. http://dx.doi.org/10.1016/j.ijheatmasstransfer.2013.06.011. [15] Singh G, Kumar H. Computational fluid dynamics analysis of shell and tube heat exchanger. Journal of Civil Engineering and Environmental Technology 2014;1:66e70. [16] Tempesti D, Fiaschi D. Thermo-economic assessment of a micro CHP system fuelled by geothermal and solar energy. Energy 2013;58:45e51. http://dx.doi.org/10.1016/j.energy.2013.01.058. [17] Cakici DM, Erdogan A, Colpan CO. Thermodynamic performance assessment of an integrated geothermal powered supercritical regenerative organic Rankine cycle and parabolic trough solar collectors. Energy 2016;120. http://dx.doi.org/10.1016/j.energy.2016.11.083. [18] Patankar SV. Numerical heat transfer and fluid flow. 1st ed. USA: Taylor & Francis; 1980.

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[19] COMSOL user’s guide. 2015. [20] Erdogan A, Cakici DM, Colpan CO. Effect of solar e geothermal heat exchanger design and fluid type on the thermodynamic performance of a power plant. In: Int. exergy, energy environ. symp., Antalya, Turkey; 2016. [21] Wilcox DC. Turbulence modeling for CFD. DCW Industries; 1998.

CHAPTER

NUMERICAL INVESTIGATION OF FIXED-BED DOWNDRAFT WOODY BIOMASS GASIFICATION

2.6

Ebubekir S. Aydin1, Ozgun Yucel1, Hasan Sadikoglu1, 2 _ Gebze Technical University, Kocaeli, Turkey1; Yildiz Technical University, Istanbul, Turkey2

1. INTRODUCTION Biomass is the general name of all nonfossilized biological material obtained from living or recently living creatures. It refers to animal and vegetable-based products commonly used to produce biofuels and biochemicals. Biomass is a term consisting of bios, which means “life” in Greek, and “mass.” Biomass is defined as all of the materials that can be renewed in a shorter period than a century-long process, including land and water-related plants, animal residues, food industry wastes, forest byproducts, and urban wastes [1]. Biomass is a continuous source of renewable and sustainable energy in nature; every kind of energy such as electricity, heat, and work obtained from biomass is called bioenergy. Biomass is considered to be a strategic energy source not only because it is renewable but because it can be grown or raised everywhere. Biomass can be used safely to generate electricity, chemicals, and fuel especially for vehicles by enhancing socioeconomic development and contributing to environmental protection. Owing to the limited availability and fluctuating high prices of fossil energy resources such as petroleum, coal, and natural gas in the world, as well as problems of environmental pollution based on fossil energy resources, biomass is increasingly becoming an alternative to solve energy problems. The storage of energy, one of the main problems, can be eliminated by using biomass for electricity and heat energy. Fossil-based energy resources such as coal, petroleum, and natural gas are being consumed at an accelerated rate and can face depletion in the near future. As a result of increasing energy demands and environmental awareness, developed countries use both biomass and nonrecoverable parts to produce electric energy and heat energy by gasification. Today, the world’s renewable energy needs to have a key role in revitalizing gasification systems, with the decline of petroleum. To solve the demand for energy and reduce the level of air pollution, clean energy resources and technologies are crucial and gaining in importance. One promising technology, gasification, is highly efficient and environmentally friendly and has received significant attention [2]. Gasification is a thermochemical process that deals with the conversion of carbonaceous materials including biomass, fossil fuels,

Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00018-4 Copyright © 2018 Elsevier Inc. All rights reserved.

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CHAPTER 2.6 NUMERICAL INVESTIGATION OF FIXED-BED DOWNDRAFT

plastics, and coal into syngas through partial oxidation in a gasifier. It is also a successful option for waste management, energy production from unconventional feeds such as forest waste, agricultural waste, poultry waste, and municipal solid waste, and the production of valuable chemicals. Gasification adds value to low-value feedstocks by converting them into marketable fuels and products. During the gasification process, a combustible gaseous fuel consisting of CO, H2, CH4, and some saturated hydrocarbons is produced by the partial oxidation of feedstocks. By means of gasification, harmful substances contained in the fuel are removed from the fuel and SO2 and NOx emissions resulting from gasification are extremely low in the gaseous mixtures. For this reason, gasification is widely accepted as an environmentally friendly method. Typically, 15% to 20% of the mass of burned solid waste results in ash, but the bottom ash yield of solid waste gasification is about 7%. Gasification process reduces volume (up to 90%) and weight (up to 75%) and breaks down hazardous substances such as dioxin or furans. Nevertheless, in gasification, sulfur dioxide and nitrogen oxide do not form owing to high temperatures and low oxygen levels. In addition, all of the thermal efficiency of the gasification process is greater than the direct combustion process. One disadvantage of small-scale energy production from gasification is the need for regular control of the gas cleaning system. Otherwise, internal combustion engines are damaged. The product gas obtained by partial oxidation of biomass can be supplied to the internal combustion engine, the gas turbine, or the boilers to produce energy [3]. When they burn in internal combustion engines, gas fuels have lower emissions than petrol. Producer gas can be used in diesel engines by introducing a spark ignition system with a reduced compression ratio [4]. Generally, the quality of syngas varies with the adopted oxidizing agent, such as air, steam, steam-oxygen, air-steam, and oxygen-enriched air [4]. Because of its availability and simplicity, air is the most widely used oxidizing agent in the laboratory and industrial applications. Syngas, which is a mixture of hydrogen, methane, carbon monoxide, and carbon dioxide, has a calorific value of 3e5 MJ/m3 in the case of air and air/steam, and 10e18 MJ/m3 in the case of oxygen and steam [5,6]. The produced syngas can be used directly as a gaseous fuel or further processed to produce electricity and heat. In addition to energy production, syngas can be considered a key intermediary product in the chemical industry to produce some crucial end products such as methanol, dimethyl ether, and methyl tert-butyl ether [7e9]. Gasifiers are divided into three principal types: fixed beds, fluidized, and entrained suspension gasifiers. Among these, fixed-bed gasifiers are the oldest and most common reactors used to produce syngas. Easy construction and simple operation made fixed-bed gasifiers preferable and they are widely used and studied. Gasifiers are also classified as updraft, downdraft, and cross-draft, depending on the direction and entry of the oxidizing agent flow. In a downdraft gasifier, solid fuels and air move in the downward direction in the lower section of the gasifier. A series of temperature-dependent thermochemical conversions of carbonaceous material occur inside the gasifier. The carbonaceous material undergoes several different processes in passing through four different zones based on the operation: drying, pyrolysis, combustion, and reduction. Each stage occurs in a specific temperature region. These temperature zones vary according to the type of gasifier. Fig. 1 shows the different zones in the process of gasification in a downdraft gasifier. These type of gasifier are suitable to handle solid fuels with an ash and moisture content less than 5% and 20%, respectively [10]. Syngas from a downdraft gasifier has a lesser tar content ( Case B. The highest total exergy efficiency is displayed in Case A. The total energy input rates of subsystem in all cases is illustrated in Fig. 4. As seen from this figure, when the greenhouse indoor temperature increases from 20 to 34 C, the total energy input envelope of all cases increases. When the greenhouse indoor temperature is taken as stable at 30 C, the total energy input rates of Case A, B, and C are calculated as 19,463.4, 7119.9, and 14,949.4 W, respectively. The highest energy input rate occurs in Case A.

FIGURE 3 The changing of exergy efficiency with different indoor temperatures for three cases.

428

CHAPTER 2.12 PERFORMANCE ASSESSMENT OF VARIOUS GREENHOUSE

FIGURE 4 The effect of indoor temperature on the total energy input envelope.

FIGURE 5 The effect of reference temperature on the exergy efficiency of three cases.

Fig. 5 shows the changing of exergy efficiency of all cases at different reference temperatures. As the reference temperature increases from 10 to 25 C, exergy efficiency of all cases decreases. The maximum exergy efficiency of all cases is demonstrated in Case A, as 34.37%, and indoor temperature of greenhouse is constant at 30 C. It is also noted that these cases tend to demonstrate lower exergy efficiency with higher reference temperature. In this study, the sustainability index is compared for the three cases. The sustainability index of all three cases is calculated and illustrated in Fig. 6. For the three cases (A, B, and C), the sustainability index, at 20 C reference temperature, is found as 1.16, 1.009, and 1.05, respectively. It is

4. RESULTS AND DISCUSSION

429

FIGURE 6 The changing of sustainably index of three cases with reference temperature.

observed that the sustainability index for all cases decreases with reference temperature increase from 10 to 25 C. Moreover, the changing sustainability index is directly proportional to exergy efficiency. The variation of energy and exergy loss rates of components for the three cases is illustrated in Figs. 7 and 8. As expected, the highest energy and exergy loss rates occur in the primary energy transformation and generation sections. In addition, the highest exergy loss rate takes place in Case B. Overall exergy efficiency of the three cases is demonstrated in Fig. 9; reference and greenhouse indoor temperature are constant at 10 and 34 C. Whereas the highest exergy efficiency is seen in Case A, the lowest exergy efficiency occurs in Case B. It can be concluded from this study that the most effective system for heating application is Case A.

FIGURE 7 Variation of energy loss rates of components.

430

CHAPTER 2.12 PERFORMANCE ASSESSMENT OF VARIOUS GREENHOUSE

FIGURE 8 Variation of exergy loss rates of components.

FIGURE 9 Overall exergy efficiency of three cases.

NOMENCLATURE

431

5. CONCLUSIONS In this study, the energy, exergy analyses and sustainability index of three cases are discussed. The heating system consists of a solar collector vacuum tube (1), a heat pump (2), and a wood biomass (3). These cases as driven solar energy and fossil fuels for the heating greenhouse with a net area 1000 m2 are compared to their exergy efficiency and sustainability index. Some conclusions are drawn from results of this study: • • • • • •

The total energy demand of the greenhouse was calculated as 4309.95 W. The exergy efficiency of Case A, Case B, and Case C for heating systems was found to be 33.11%, 2.14%, and 15.32%, respectively, at 34 C indoor greenhouse temperature. The sustainability index for three cases with a solar collector, a heat pump, and a wood biomass boiler for heating systems are calculated as 1.38, 1.01, and 1.14, respectively. The highest and lowest exergy input rates of heating systems for Cases B and Case A were computed as 15,732.17 and 1017.05 W. As the greenhouse indoor temperature increases from 20 to 34 C, the total exergy efficiency rates of all of the cases increase. It was concluded that for the Mediterranean climate the performance of greenhouse was improved with the use of a solar collector.

NOMENCLATURE A cp DHW E_ _ Ex F f g I N nd n0 Q_ R RR SI T U E_ N q p s

Area (m2) Specific heat capacity (kJ/kg K) Domestic hot water (
) Energy (W) Exergy (W) Factor Approximation factor Transmission Solar irradiation (W/m2) Percentage of equipment resistance Rate of air changing (1/h) Number Rate of heat transfer (kW) Pressure drop of the pipe (Pa/m) Renewability ratio Sustainability index Temperature (K) Thermal transmittance (W/m2 K) Rate of volumetric flow Net Quality Primary energy Source

432

CHAPTER 2.12 PERFORMANCE ASSESSMENT OF VARIOUS GREENHOUSE

Subscripts aux dis Ge HS in out

auxiliary energy demand distribution Generation Heating system Inlet Outlet

Greek Letters h j

Efficiency of energy Efficiency of exergy

REFERENCES [1] Annex 49. Energy conservation in buildings and community systems low exergy systems for high performance buildings and communities. 2007. Homepage: http://www.annex49.com. [2] Omer AM. Renewable building energy systems and passive human comfort solutions. Renewable and Sustainable Energy Reviews 2008;12:1562e87. [3] Schmidt D, Juusela MA. Low-exergy systems for heating and cooling of buildings. In: Proceedings of the 21st Conference on Passive and Low Energy Architecture, Eindhoven, The Netherlands; 2004. [4] Schmidt D. Low exergy systems for high-performance buildings and communities. Energy and Buildings 2009;41:331e6. [5] Annex 37. Energy conservation in buildings and community systems e low exergy systems for heating and cooling of buildings. 2016. http://virtual.vtt.fi/annex37/. [6] Mohammadi A, Omid M. Economical analysis and relation between energy inputs and yield of greenhouse cucumber production in Iran. Applied Energy 2010;87:191e6. [7] Chou SK, Chua KJ, Ho JC, Ooi CL. On the study of an energy-efficient greenhouse for heating, cooling and dehumidification applications. Applied Energy 2004;77:355e73. [8] Ozgener O, Hepbasli A. Experimental investigation of the performance of a solar assisted ground-source heat pump system for greenhouse heating. International Journal of Energy Research 2005;29(2):217e31. [9] Balta MT, Dincer I, Hepbasli A. Performance and sustainability assessment of energy options for building HVAC applications. Energy and Buildings 2010;42(8):1320e8. [10] Lohani SP, Schmidt D. Comparison of energy and exergy analysis of fossil plant, ground and air source heat pump building heating system. Renewable Energy 2010;35:1275e82. [11] Ozgener O, Hepbasli A. Performance analysis of a solar assisted ground-source heat pump system for greenhouse heating: an experimental study. Building and Environment 2005;40(8):1040e50. [12] Tong Y, Kozai T, Nishioka N, Ohyama K. Greenhouse heating using heat pumps with a high coefficient of performance (COP). Biosystems Engineering 2010;106:405e11. [13] Hepbaslı A. Low exergy (LowEx) heating and cooling systems for sustainable buildings and societies. Renewable and Sustainable Energy Reviews 2012;16:73e104. [14] Yucer CT, Hepbasli A. Thermodynamic analysis of a building using exergy analysis method. Energy and Buildings 2011;43(2e3):536e42. [15] Shukuya M, Hammache A. Introduction to the concept of exergyeefor a better understanding of lowtemperature-heating and high-temperature-cooling systems. Espoo, Finland: VTT Research Notes 2158; 2002. [16] Shukuya M. Exergy concept and its application to the built environment. Building and Environment 2009; 44(7):1545e50.

REFERENCES

433

[17] Balta MT, Kalinci Y, Hepbasli A. Evaluating a low exergy heating system from the power plant through the heat pump to the building envelope. Energy and Buildings 2008;40(10):1799e804. [18] LowEx., LowEx.Net, Network of International Society for Low Exergy Systems in Buildings. http://www. lowex.org. [19] Hepbaslı A. A comparative investigation of various greenhouse heating options using exergy analysis method. Applied Energy 2011;88:4411e23. [20] Balta MT, Dincer I, Hepbasli A. Development of sustainable energy options for buildings in a sustainable society. Sustainable Cities and Society 2011;1:72e80.

CHAPTER

ENERGY, EXERGY, AND EXERGOENVIRONMENTAL ASSESSMENTS OF SOLAR-ASSISTED ABSORPTION COOLING SYSTEMS AND CONVENTIONAL AIRCONDITIONING SYSTEM: A COMPARATIVE STUDY

2.13

Hamed Alimoradiyan1, Tahir A.H. Ratlamwala2 Eastern Mediterranean University, Famagusta, Turkey1; Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Karachi, Pakistan2

1. INTRODUCTION Because of the spread in the size of cities and the growth in the world’s population, energy consumption has become a vital concern for countries globally. Rapid developments in industry has increased demands for energy more than ever. To supply energy needs, most power plants use highefficiency fossil fuels, but they are facing fuels’ typical drawbacks such as that they release dangerous gases including CO2, NOx, which causes global warming, air pollution, and ozone depletion. Greenhouse gases in the atmosphere can absorb solar radiation and release it as infrared waves [1]. It has become increasingly important to come up with alternative energy sources that are energy efficient and environmentally compatible, and that are not harmful to nature and its creatures [2]. One of the most accessible renewable energy sources is the sun. Solar radiation coming to the earth’s surface brings with it an enormous quantity of energy that can be used to generate power, heat, or both, depending on the solar technology selected. In this way, solar thermal technology, including solar dishes, parabolic troughs, and heliostat fields, help achieve high-temperature heat and power [2,3]. Many researchers have performed comprehensive energetic and exergetic analyses for integrated energy systems. M. Rabani et al. [4] analyzed an organic Rankine cycle (ORC) system, gas-turbine cycle, and integrated heliostat solar field in terms of their energy and exergy. Several combined cycle power plants were analyzed in terms of exergy and exergoeconomic and environmental impacts Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00025-1 Copyright © 2018 Elsevier Inc. All rights reserved.

435

436

CHAPTER 2.13 SOLAR-ASSISTED ABSORPTION COOLING SYSTEMS AND CAS

by Ahmadi et al. [5]. The environmental impacts of energy systems were checked by exergoenvironmental evaluation by Mayer et al. [6]. Exergetic and energetic assessments of an integrated triple-effect absorption system were presented by Gadalla et al. [7]. Integrated, solar-based, quadruple-effect absorption desalination for cooling and pure water production was analyzed in terms of an energetic and energetic analysis by Ratlamwala et al. [8]. A. Kribus et al. [9] presented the performance feasibility of a combined cycle electricity generation plant that was driven by a high-temperature central receiver and concentered solar energy system. Wu et al. [10] conducted a thermal and electrical transformation performance assessment for a parabolic dish solar thermal power system. Alkhamis et al. [11] presented a performance feasibility study for a proposed solar-powered heating and cooling system in a tropical location for a swimming pool and space heating system. An integrated system, including a heliostat field, a steam cycle, an ORC, and an electrolyzer for hydrogen production was analyzed in terms of energy and exergy by Ratlamwala et al. [12]. Xu et al. [13] presented an energetic and exergetic analysis of a solar power tower system using molten salt as the heat transfer fluid. Garcı´a et al. [14] presented a simulation to analyze the performance quality of a parabolic trough solar thermal power plant with a thermal storage system. To select the best suitable system, Kalogirou [15] offered the best working temperature range for three types of solar energy systems, including a parabolic trough collector (60 to 500
C), a solar dish (100 to 700
C), and a heliostat field solar system (150 to 1500
C). High-temperature solar thermal collectors were useful from both the heat-creating and efficiency standpoints based on studies by some researchers [16e19]. The heat produced from both combustion and the solar-based system was then used to drive a Rankin cycle to generate power and hot water or any other desired output [2]. The current study presents a comparative energy, exergy, and exergoenvironment assessment of four integrated systems. The systems considered are (1) an integrated solar heliostat, single-effect LiBr-water absorption system (System 1), (2) an integrated solar heliostat, double-effect LiBr-water absorption system (System 2), (3) an integrated solar heliostat, triple-effect LiBrewater absorption system (System 3), and (4) a combined combustioneRankin cycle, conventional air-conditioning system (System 4). This study was unique in how it compared solar cooling technologies with a conventional cooling system to show that when the overall system was considered, the most advanced solar cooling technologies were the clear winners in terms of energy, exergy, and exergoenvironment. A parametric study was also performed to investigate the effects of several operating parameters such as the evaporator temperature and ambient temperature on energy, exergy, and exergoenvironmental performances of the four systems considered.

2. DESCRIPTION OF THE SYSTEM Block diagrams of the integrated systems reported in this chapter are presented in Fig. 1. Figs. 2e4 display the schematics of Systems 1, 2, and 3 using a LiBrewater absorption cooling system coupled with a heliostat field. In a heliostat solar field, solar radiation is reflected onto the receiver, which transfers molten salt. In the current assessment, a combination of LiCl (59.5%) and KCl (49.5%) was used as the working molten salt. The molten salt boiled at 1400
C and melted at 354
C. After gaining heat from receivers, this high-temperature molten salt passed through the high-temperature generator to add heat to the LiBrewater mixture entering the high-temperature generator. In the refrigeration cycle, LiBrewater left the absorber at state 1 and entered the heat exchanger, taking heat from a weak

2. DESCRIPTION OF THE SYSTEM

437

Hot Molten Salt Fuel(CH4)

Air Cooling Solar Heliostat field

SEAS Heating

CC

cold Molten Salt Hot Molten Salt

Cooling Solar Heliostat field

Cooling

DEAS

ORC

Heating

power

CAS Heating

cold Molten Salt Hot Molten Salt Exhaust

Cooling Solar Heliostat field

TEAS

Heating

cold Molten Salt

FIGURE 1 Flow diagram of integrated systems. CAS, conventional air-conditioning system; CC, combustion chamber; DEAS, double-effect absorption system; ORC, organic Rankine cycle; SEAS, simple-effect absorption system; TEAS, triple-effect absorption system. Solar radiation

7 Condenser

receiver

8

9

Eva.

Molten salt inlet

Molten salt return

Generator

11

10

4 3

5

6

Heat Exchanger Heliostat field

Absorber 2

1

FIGURE 2 Schematic of integrated solar heliostat, single-effect absorption cooling system (System 1). Eva., evaporation.

7

Condenser

12 13

Solar radiation

6

5

receiver

Molten salt inlet

14 V.H.T. G

H.T.G Evaporator

12

Molten salt return

C.H.E.

18 17

4

22

19

8 3

9

10

V.H.E.

Heliostat field

15

16 21

11

2

1

H.H.E.

20

3

Abs.

FIGURE 3 Schematic of integrated solar heliostat, double-effect absorption cooling system (System 2). Abs, absorber; CHE, condenser heat exchanger; HHE, high temperature heat exchanger; HTG, high temperature generator. Solar radiation

receiver

Molten salt inlet H.T.G

Molten salt return

14

15

21

H.T.C. 22

H.H.E 16 13

23

17

18

M.T.G

Heliostat field

M.T.C. 12

24 25

M.H.E 19 26

11 20 L.T.G

L.T.C. 3

4

7 8

L.H.E 5

2

6

1

9 Abso.

10

Eva.

FIGURE 4 Schematic of integrated solar heliostat, triple-effect absorption cooling system (System 3). Abso, absorber; EVA, evaporator; HHE, high temperature heat exchanger; HTC, high temperature condenser; HTG, high temperature generator; LHE, low temperature heat exchanger; LTC, low temperature condenser; LTG, low temperature generator; MHE, medium temperature heat exchanger; MTC, medium temperature condenser; MTG, medium temperature generator.

3. ENERGETIC AND EXERGETIC ANALYSES

3

2 Cond.

Power

Eva.

1

Turbine

3

C

4

439

boiler

Air

(Q) C.C.

CH4

4

Cond.

1

2

FIGURE 5 Schematic of integrated conventional air-conditioning system (System 4). C, cold; C.C., combustion chamber; Cond., condenser.

LiBrewater solution coming back from the generator. Then it went into the generator at state 3 and gained heat from high-temperature molten salt passing through the generator. Next, water left the generator as superheated steam at state 7 and a weak solution left the generator at state 4 and returned to the absorber by passing through the heat exchanger. The water steam at state 7 entered the condenser and supplied heat. Then it entered the evaporator at state 8 to provide cooling. Water from the evaporator then entered the absorber to mix with a weak solution from the generator, and the same scenario repeated for Systems 2 and 3. For example, a conventional air conditioning system was integrated into the Rankin cycle to supply its compressor power (System 4). Also, the combustion chamber was chosen to run the Rankin cycle and methane (CH4) was used as fuel. The fuel was mixed with air at an ambient temperature (25
C) and combustion built up to provide heat to the Rankin cycle boiler to produce power that was then supplied to the compressor of the conventional system, as illustrated in Fig. 5.

3. ENERGETIC AND EXERGETIC ANALYSES Initial assumptions are needed to reach a precise energetic and exergetic evaluation. For this purpose, the ambient temperature (T0), surrounding pressure (p0), and air-specific humidity (u) were considered to be 298K, 101 kPa, and 40%, respectively. In addition, the isentropic efficiencies of the pumps and turbine (hpump and hturbine) were assumed to be 80%, whereas the parasitic losses were assumed to be 20%.

3.1 HELIOSTAT SOLAR FIELD SYSTEM Xu et al. [13] proposed a heliostat solar field, which was used in the current study to come up with a base model. The amount of heat received by the receivers from the sunlight intensity is calculated as: Q_s ¼ I  Afield

(1)

440

CHAPTER 2.13 SOLAR-ASSISTED ABSORPTION COOLING SYSTEMS AND CAS

where I and Afield represent the solar intensity and solar area field, respectively. The rate of heat received by the central receiver is defined as: hH ¼

Q_rec Q_s

where Q_rec represents the rate of solar heat absorption. The average central receiver emissivity is calculated as: εw εavg ¼ εwþð1εw ÞFr

(2)

(3)

where εw and Fr represent the receiver surface emissivity and view factor, respectively. The inner-side temperature of the central receiver is defined as: Tinsi ¼

Trec;surf þ T0 2

(4)

where Trec,surf and T0 define the surface receiver and ambient temperature, respectively. The central receiver surface area is calculated as: Arec;surf ¼

Afield C  Fr

where C is the concentration ratio. The rate of heat lost owing to emissivity in the central receiver is defined as:
 4 εavg  s Trec;surf  T04 Afield Q_rec;em ¼ C

(5)

(6)

where s represents the StefaneBoltzmann constant. The rate of heat lost owing to reflection in the central receiver is calculated as: Fr Q_rec;ref ¼ Q_rec  r  Afield In this formula, r represents density. The rate of heat loss owing to convection in the central receiver is found using:      hair;fc;insi  Trec;surf  T0 hair;nc;inis  Trec;surm  T0 Afield Q_rec;conv ¼ C  Fr The rate of heat loss owing to conduction in the central receiver is calculated as:   T A  T 0 rec;surf  field Q_rec;cond ¼  vinsu 1 þ C  Fr linsu hair;o

(7)

(8)

(9)

The rate of heat absorbed by the molten salt passing through the central receiver is found using:   (10) Q_rec;abs ¼ m_ ms Cp Tms;in  Tms;out

3. ENERGETIC AND EXERGETIC ANALYSES

441

The total rate of heat received by the central receiver is calculated as: Q_rec ¼ Q_rec;abs þ Q_rec;em þ Q_rec;ref þ Q_rec;conv þ Q_rec;cond

(11)

The central receiver surface temperature is found using: Trec;surf  Tms Q_rec ¼ _ AfieldFr c ln ddoi do d0 di hms 2kw

(12)

where Trec,surf represents the receiver surface temperature (K), Tms the average temperature of the molten salt (K), do the outer diameter of the tubes in the central receiver (m), di the inner diameter of the tubes in the central receiver (m), hms the heat transfer coefficient of the molten salt (W/m2 K), and kw the conductivity of the tube material (W/m K). The exergy rate carried by the solar light intensity is calculated as:   _ s ¼ 1  T0 Q_s Ex (13) Tsun

3.1.1 Rankin Cycle In general, the efficiency of a simple Rankin cycle can be defined as: htherm ¼

W_ net Q_in

(14)

where htherm defines the thermodynamic efficiency of the cycle as the ratio of net power output to heat input. Each of the next four equations is derived from the energy and mass balance for a control volume: _ 3  h2 Þ Q_in ¼ mðh

(15)

_ 2  h1 Þ W_ pump ¼ mðh

(16)

_ 3  h4 Þ W_ thermal ¼ mðh

(17)

where m_ represents the mass flow rate for the Rankin cycle. When dealing with the efficiencies of turbines and pumps, an adjustment must be made to the work terms: _ 3  h4 Þ y mðh _ 3  h4 Þhthermal W_ turbine ¼ mðh

(18)

3.1.1.1 Conventional System The ratio of air to fuel is an illustration: AF ¼

m_ air m_ fuel

(19)

442

CHAPTER 2.13 SOLAR-ASSISTED ABSORPTION COOLING SYSTEMS AND CAS

The coefficient of performance (COP) of the conventional system with respect to energy and exergy is: Q_cooling m_ fuel  HHVfuel

(20)

_ th Ex m_ fuel  ðexph þ exch Þ

(21)

COPen ¼ COPex ¼

where m_ fuel , exph, and exch represent the mass flow rate of fuel (CH4), physical exergy, and chemical exergy, respectively.

3.1.2 Absorption Systems The exergy rate carried by the molten into the generator salt is calculated as:   T0 _ Q_rec;abs Exrec;abs ¼ 1  Tms;o

(22)

The specific enthalpy at any given state in Systems 1e3 is calculated as: hi ¼

k X

mfm hm

(23)

m¼1

The specific entropy at any given state in Systems 1e3 is calculated as: si ¼

k X

mfm sm

(24)

Mm Mi

(25)

m¼1

The mass fraction of a substance is found by: mfm ¼ ym

The exergy rate at any given state in Systems 1e3 is: _ i ¼ m_ i ððhi  h0 Þ  T0 Þ  T0 ðsi  s0 Þ Ex The thermal exergy rate in each heat exchanger is defined as:   _ thi ¼ 1  T0 Q_i Ex Ti

(26)

(27)

The power required by any pump in Systems 1e3 is written as: W_ pi ¼ m_ i ðhi  hi1 Þ

(28)

The COP for Systems 1e3 is: COPen ¼

Q_eva W_ pump þ Q_solar

(29)

3. ENERGETIC AND EXERGETIC ANALYSES

COPex ¼

_ eav Ex _ solar W_ pump þ Ex

_ dest;tot Ex fei ¼ P _ in Ex

443

(30) (31)

_ dest;tot , and Ex _ in present the exergoenvironmental impact factor, total exergy destruction in where fei, Ex the system, and total exergy supplied to the system, respectively: 1 Cei ¼ h ex 100

(32)

where Cei and hex represent the exergoenvironmental impact coefficient and exergetic efficiency, respectively: qei ¼ fei  Cei

(33)

where qei represents the exergoenvironmental impact index: qeii ¼

1 qei

(34)

where qeii represents the exergoenvironmental impact improvement: fes ¼

_ tot;out Ex _ _ des;tot þ Ex _ uu Extot;out þ Ex

(35)

_ uu represent the exergetic stability factor and exergy carried by the unused fuel: where fes and Ex qest ¼ fes  qeii where qest represents the exergetic sustainability index. The assumptions made to analyze the heliostat field system are listed in Table 1.

Table 1 Assumptions for Solar Heliostat Field Constant

Values

Sun’s temperature (Tsun) Efficiency (hh) Area (Afield) View factor (Fr) Receiver surface emissivity (εw) Thickness (vinsu) Concentration ratio (C)

4500K 75% [3] 2915 m2 0.8 [3] 0.8 [3] 0.07 m [3] 1000 [3]

(36)

444

CHAPTER 2.13 SOLAR-ASSISTED ABSORPTION COOLING SYSTEMS AND CAS

4. RESULTS AND DISCUSSIONS This section presents the performance analysis of the integrated systems. The results obtained were compared with each other to see which system performed best from the perspectives of energy, exergy, and the exergoenvironment. The solar heliostat field demonstrated in this study was modeled on the basis of the system presented by Ratlamwala and Dincer [3]. The energy efficiency obtained in the current study for System 1 was 0.5509, compared with the range from 0.37 to 0.81 in Ali et al. [20]. The energetic COP for System 2 obtained in this study was 1.284, compared with the range of 0.9e1.2 [21], and for System 3 it was 1.511, compared with 1.189 [22], which proved that the current study was adequately modeled.

4.1 EFFECTS OF EVAPORATOR TEMPERATURE THE ENERGETIC AND EXERGETIC COEFFICIENTS OF PERFORMANCE By considering COPen and COPex to be the most important parameters in our design, there is another parameter that can have an impact on system performance: evaporator temperature. When varying the evaporator temperature, there was a light downward trend in performance for all three absorption systems and for System 4. As is illustrated in Fig. 6, the changing was slightly less for COPen whereas

1.6

1.4

1.4

1.2

COPen

1

COPen (system 1) COPen (system 2)

COPex (system 1) COPex (system 2)

COPen (system 3)

COPex (system 3) COPex (system 4)

COPen (system 4)

0.8

1 0.8 0.6

COPex

1.2

0.6 0.4

0.4

0.2

0.2 0 274

275

276

277

278

0

Teva(K)

FIGURE 6 Effects of variation in evaporator temperature on energy and exergy coefficients of performance (COPs).

4. RESULTS AND DISCUSSIONS

445

it was more significant for COPex. As the evaporator temperature increased from 274 to 279K, there was a decline in COPen from 0.5556 to 0.5509, 1.288 to 1.284, 1.524 to 1.511, and 1.4 to 1.358 for Systems 1e4, respectively. The decreases in COPen were slight compared with the decreases in COPex: 0.1375 to 0.119, 0.3012 to 0.2608, 0.312 to 0.2701, and 0.4674 to 0.4435 for Systems 1e4, respectively. It is desirable for the system to supply a cool temperature so that the evaporator can reach maximum performance.

4.2 EFFECTS OF EVAPORATOR TEMPERATURE ON EXERGOENVIRONMENTAL IMPACT FACTORS By analyzing the exergoenvironmental impact factor for all four systems that were examined, their affirmative effects on the surrounding environment could be determined. A reduction in irreversibility for the investigated systems could reduce the environmental implications. The best value of this parameter is 0, which shows that system had no irreversibilities. As is shown in Fig. 7, the exergoenvironmental impact factor decreased slightly by increasing the evaporator temperature for Systems 1e3. There was a significantly different trend among Systems 1, 3, and 4 because of the high amount of exergy destruction produced by System 4. System 4 had the highest exergoenvironmental impact factor compared with three absorption systems, which shows that System 4 was not eco-friendly.

4.875

0.025

4.87

0.02

Fei

4.86 0.01

system 1 system 2 system 3 system 4

0.005

0 274

Fei (system 4)

4.865 0.015

4.855

4.85

275

276

277

278

Teva(K)

FIGURE 7 Effects of variation in evaporator temperature on exergoenvironmental impact factor.

4.845 279

446

CHAPTER 2.13 SOLAR-ASSISTED ABSORPTION COOLING SYSTEMS AND CAS

4.3 EFFECTS OF EVAPORATOR TEMPERATURE ON EXERGOENVIRONMENTAL IMPACT COEFFICIENTS The exergoenvironmental impact coefficient refers to the exergetic efficiency of the system. The exergy efficiency has an important role in the exergoenvironmental assessment of the system. Fig. 8 shows that by varying the evaporator temperature from 274K to 279K, there was an upward trend in Cei for Systems 1e3 and System. Because of lower exergy efficiency, Systems 1e3 had higher Cei compared with System 4, which used fossil fuel. In this section, we sought to obtain the optimum amount of Cei, which was more accessible for Systems 1e3. It was obtained by evaluating the systems, using solar energy systems cause higher exergoenvironmental impact coefficients that encourage the engineers to work more on solar energy systems to protect the environment from the hazardous impact of fossil fuels.

4.4 EFFECTS OF EVAPORATOR TEMPERATURE ON THE EXERGOENVIRONMENTAL IMPACT INDEXES One of the most important factors showing whether the system under analysis harms the environment is the exergoenvironmental impact index. It considers the exergy destruction and waste exergy output of the system, which should be as small as possible. The exergoenvironmental impact index is defined by multiplying the exergoenvironmental impact factor by the exergoenvironmental impact coefficient. By varying the evaporator temperature, the qei for all of the systems increased. As shown in Fig. 9, Systems 1e3 had the lowest amounts of exergoenvironmental impact whereas System 4 had the highest qei, so it is crucial to keep this parameter near 0 to reach an acceptable result. 10

8 system 1 system 2 system 3 system 4

Cei

6

4

2

0 274

275

276

277

278

279

Teva(K)

FIGURE 8 Effects of variation in evaporator temperature effect on exergoenvironmental impact coefficient.

4. RESULTS AND DISCUSSIONS

447

11

0.09 0.08

θei

0.06

10.9 system 1 system 2 system 3 system 4

10.8

0.05 0.04

θei (system 4)

0.07

10.7

0.03 0.02 274

275

276

Teva(K)

277

278

10.6 279

FIGURE 9 Effects of variation in evaporator temperature on exergoenvironmental impact index.

4.5 EFFECTS OF EVAPORATOR TEMPERATURE ON IMPROVING EXERGOENVIRONMENTAL IMPACT The exergoenvironmental impact improvement parameter is considered as a parameter to check systems in terms of their environmental suitability. The exergoenvironmental impact index should be as small as possible to reach the highest and the most suitable environmental appropriateness for all systems. This parameter depends significantly on the total rate of exergy for the stream outlet and the total exergy destruction of the system. A high value of exergoenvironmental impact improvement means the system is very compatible with the environment. By varying the evaporator temperature the qeii for Systems 1e3 decreased but System 4 remained constant trend. The lowest amount was for System 4 compared with Systems 1e3, as shown in in Fig. 10.

4.6 EFFECTS OF EVAPORATOR TEMPERATURE ON EXERGETIC STABILITIES The exergetic stability factor as shown in Fig. 11 is a utility of the desired output exergy, total exergy destruction, and exergy released by waste fuel. It is used to reach a value of this parameter as close to 1 as possible. In this study, the evaluations showed that, owing to their lower exergy destruction and its effect on exergetic stability, Systems 1e3 were close to 1 compared with System 4. System 4 burned fossil fuels to run the system, and the high rate of exergy destruction (exergetic losses) caused a great deal of emissions into the environment and endangered the surrounding area. It is recommended to use filters to reduce emissions, but they cannot decrease exergy destruction. Fig. 11 proves all of the results obtained by the system assessments.

CHAPTER 2.13 SOLAR-ASSISTED ABSORPTION COOLING SYSTEMS AND CAS

0.095

40

θeii

30

system 1 system 2 system 3 system 4

0.094

0.093

20 0.092 10

θeii (system 4)

448

0.091

0 274

275

276

277

278

0.09 279

Teva(K)

FIGURE 10

0.00003635

0.995

0.00003632

0.99

0.00003629

Fes

1

0.985

0.98

0.975 274

0.00003625

system 1 system 2 system 3 system 4

275

0.00003622

276

Teva(K)

277

278

FIGURE 11 Effects of variation in evaporator temperature on exergetic stability factor.

0.00003619 279

Fes (system 4)

Effects of variation in evaporator temperature on exergoenvironmental impact improvement.

4. RESULTS AND DISCUSSIONS

449

4.7 EFFECTS OF EVAPORATOR TEMPERATURE ON THE EXERGETIC SUSTAINABILITY INDEXES The exergetic sustainability index shown in Fig. 12 is the result of multiplying the exergetic stability factor and the exergoenvironmental impact improvement of the integrated systems. It is best to gain the highest possible value of the exergetic sustainability index. For this evaluation, System 1 had the highest exergetic sustainability index; next were Systems 2 and 3. As illustrated in Fig. 12, all systems had the same trends (decreasing) but System 4 was the lowest among the 4 systems. In this evaluation, the trends shown in Fig. 12 prove the assessment results and show that solar energy systems (Systems 1e3) are recommended compared with conventional system (System 4).

4.8 EFFECTS OF AMBIENT TEMPERATURE ON ENERGETIC AND EXERGETIC COEFFICIENTS OF PERFORMANCE Ambient temperature has a crucial role in heat-dependent integrated systems. Fig. 13 presents the effect of increasing ambient temperature on the energetic and exergetic COPs for Systemse4. As shown in Fig. 13, variations in ambient temperature had no effect on COPen for all of the systems because the energetic analysis did not account for irreversibilities or heat losses when it varied in ambient temperature. Despite having an abortive role in the energetic COP, ambient temperature has a significant role in exergetic COP because all of the exergy rates and exergy destruction depended on ambient temperature, so Fig. 13 shows that there was an increasing trend for Systems 1e3 whereas

40

0.095

30 θest

system 1 system 2 system 3 system 4

0.093

0.092 20 0.091

10 274

275

276

277

278

Teva(K)

FIGURE 12 Effects of variation in evaporator temperature on the exergetic sustainability index.

0.09 279

θeii (system 4)

0.094

450

CHAPTER 2.13 SOLAR-ASSISTED ABSORPTION COOLING SYSTEMS AND CAS

1.68 1.5

1.4

1

0.84

COPex

COPen

1.12 COPex (system 1) COPex (system 2) COPex (system 3) COPex (system 4)

COPen (system 1) COPen (system 2) COPen (system 3) COPen (system 4)

0.56

0.5

0.28 0 295

300

305

310

315

0 320

T0(K) FIGURE 13 Effects of variation in ambient temperature on energy and exergy coefficients of performance (COPs).

System 4 had a downward trend. By varying the ambient temperature from 295K to 320K, the COPex rose from 0.09,751 to 0.3129, 0.1882 to 0.6087, and 0.2225 to 0.6762 for Systems 1e3, respectively. In comparison, the COPex of System 4 fell from 0.4887 to 0.3846.

4.9 EFFECTS OF VARIATION IN AMBIENT TEMPERATURE ON EXERGY DESTRUCTION RATES The exergy destruction rate was evaluated for each component as the most important environmental parameter (Fig. 14). Chemical exergy caused by the combustion procedure was the principal source of exergy destruction (irreversibility) for System 4. In addition, heat losses in heat exchangers caused by passing cold and hot fluid and temperature differences between systems and environments could have caused the exergy destruction rate for all of the systems. Also, for the ORC, the boiler was the most significant reason for exergy destruction, because high-temperature fluid passed through the boiler. Irreversibility (exergy destruction) is the most crucial parameter to consider when designing an eco-friendly system. The lowest amount of exergy destruction is the most suitable system for design. System 4 and systems that use fossil fuels because of their high chemical exergy, high heat losses, and high rate of greenhouse emissions are not suggested, although inevitably they have the highest energy and exergy efficiencies compared with renewable systems.

5. CONCLUSIONS

451

1400

Rate of Exergy Destruction

1200

system 1

1000 system 2 800 600

system 3

400 system 4 200 0 295

300

305

310

315

320

T0(k)

FIGURE 14 Effects of variation in ambient temperature on exergy destruction rate for each integrated system.

5. CONCLUSIONS This study dealt with comparative energy and exergy analyses for (1) an integrated solar heliostat, single-effect LiBrewater absorption system (System 1), (2) an integrated solar heliostat, double-effect LiBrewater absorption system (System 2), (3) an integrated solar heliostat, triple-effect LiBrewater absorption system (System 3), and (4) a combustioneRankin integrated conventional air-conditioning system (System 4). A comparative study was been conducted to analyze the effect of varying the ambient and evaporator temperature on the COPen, COPex, and exergoenvironmental parameters to evaluate their environmental impacts. The result showed by changing the evaporator temperature from 274K to 279K, the COPen decreased from 0.5556 to 0.5509 for System 1, 1.288 to 1.284 for System 2, 1.524 to 1.511 for System 3, and 1.4 to 1.358 for System 4. Also, there was a downward trend for COPex from 0.1375 to 0.119 for System 1, 0.2642 to 0.2299 for System 2, 0.312 to 0.2701 for System 3, and 0.4887 to 3846 for System 4. By increasing the evaporator temperature, the COPen and COPex decreased, but by raising the ambient temperature, the COPen was constant for all four systems. However, the COPex increased for Systems 1e3 whereas it decreased for System 4, as shown in Fig. 13. Furthermore, by varying the evaporator temperature from 274K to 279K, environmental parameters such as the exergoenvironmental impact factor, exergoenvironmental impact coefficient, exergoenvironmental impact index, exergoenvironmental impact improvement, exergetic stability factor, and exergetic sustainability index varied, depending on their characteristics, but the promising outcome of the study is that all of the systems were eco-friendlier at a lower evaporator temperature. The most vital parameter for examining the environmental aspect of systems is their irreversibility (exergy destruction) or their losses into the environment. System 4 had the highest rate of

452

CHAPTER 2.13 SOLAR-ASSISTED ABSORPTION COOLING SYSTEMS AND CAS

irreversibility (exergy destruction) because of chemical reactions that occurred during combustion with CH4 as the fossil fuel, compared with Systems 1e3. The results showed that it was more useful for the environment to operate all systems at a lower evaporator temperature because of the lower exergy destruction owing to the lower difference between the evaporator and the ambient temperature. Thus, as illustrated in figures and mentioned in the results, System 4 is not recommended as an environmental solution although it had high COPen and COPex.

NOMENCLATURE A c d _ di Ex Fr h HW HHV I m_ M mf P Q_ s S T W_ y

Area Concentration ratio Diameter, m Exergy destruction rate, kW View factor Specific enthalpy, kJ/kg; heat transfer coefficient, W/m2 K Hot water Higher heating value Solar light intensity, W/m2 Mass flow rate, kg/s Molecular weight, kg/mol Mass fraction Pressure, kPa Heat flow rate, kW Specific entropy, kJ/kg K Separator Temperature, K Work rate, kW Mole fraction

Greek Letters h ε s r v l

Efficiency Receiver surface emissivity StefaneBoltzmann constant, W/m2 K4 Density, kg/m3 Thickness, m Thermal conductivity, W/m K

Subscripts Abs avg ch CAS CC DEAS ORC SEAS

Absorbed, absorber Average Chemical Conventional air-conditioning system Combustion chamber Double-effect absorption system Organic Rankine cycle Simple-effect absorption system

NOMENCLATURE

TEAS cond conv convr COP em en ex fc H i insi insu i k m ms nc o p ph surf sys th turb w

Triple-effect absorption system Conduction, condenser Convection Conversion Coefficient of performance Emissive Energy Exergy Forced convection Heliostat Inner Inner side of receiver Insulation ith state kth state mth state Molten salt Natural convection Outer Pump Physical Surface System Thermal Turbine Wall surface

Acronyms Abs C CHE CH4 CO2 EVA H HE HHE HTC HTG KCl LHE LiCl LTC LTG MHE MTC MTG

Absorber Cold Condenser heat exchanger Methane Carbon dioxide Evaporator Hot Heat exchanger High temperature heat exchanger High temperature condenser High temperature generator Potassium chloride Low temperature heat exchanger Lithium chloride Low temperature condenser Low temperature generator Medium temperature heat exchanger Medium temperature condenser Medium temperature generator

453

454

CHAPTER 2.13 SOLAR-ASSISTED ABSORPTION COOLING SYSTEMS AND CAS

REFERENCES [1] Ozgur Colpan C, Dincer I, Hamdullahpur F. The reduction of greenhouse gas emissions using various thermal systems in a landfill site. International Journal of Global Warming 2009;1(1e3):89e105. [2] Ratlamwala TAH, El-Sinawi AH, Gadalla MA, Aidan A. Performance analysis of a new designed PEM fuel cell. International Journal of Energy Research 2012;36(11):1121e32. [3] Ratlamwala TAH, Dincer I. Performance assessment of solar-based integrated CueCl systems for hydrogen production. Solar Energy 2013;95:345e56. [4] Rabbani M, Ratlamwala TAH, Dincer I. Transient energy and exergy analyses of a solar based integrated system. Journal of Solar Energy Engineering 2015;137(1):011010. [5] Ahmadi P, Dincer I, Rosen MA. Exergy, exergoeconomic and environmental analyses and evolutionary algorithm based multi-objective optimization of combined cycle power plants. Energy 2011;36(10): 5886e98. [6] Meyer L, Tsatsaronis G, Buchgeister J, Schebek L. Exergoenvironmental analysis for evaluation of the environmental impact of energy conversion systems. Energy 2009;34(1):75e89. [7] Gadalla M, Ratlamwala TAH, Dincer I. Evaluation of a triple effect absorption air conditioning system integrated with PEM fuel cell. In: ASME 2010 8th International Conference on Fuel Cell Science, Engineering and Technology. American Society of Mechanical Engineers; January 2010. p. 707e17. [8] Ratlamwala TAH, Dincer I, Gadalla MA. Energy and exergy analyses of an integrated solar-based desalination quadruple effect absorption system for freshwater and cooling production. International Journal of Energy Research 2013;37(13):1569e79. [9] Kribus A, Zaibel R, Carey D, Segal A, Karni J. A solar-driven combined cycle power plant. Solar energy 1998;62(2):121e9. [10] Wu SY, Xiao L, Cao Y, Li YR. A parabolic dish/AMTEC solar thermal power system and its performance evaluation. Applied Energy 2010;87(2):452e62. [11] Alkhamis AI, Sherif SA. Feasibility study of a solar-assisted heating/cooling system for an aquatic centre in hot and humid climates. International Journal of Energy Research 1997;21(9):823e39. [12] Ratlamwala TAH, Dincer I, Aydin M. Energy and exergy analyses and optimization study of an integrated solar heliostat field system for hydrogen production. International Journal of Hydrogen Energy 2012;37(24): 18704e12. [13] Xu C, Wang Z, Li X, Sun F. Energy and exergy analysis of solar power tower plants. Applied Thermal Engineering 2011;31(17):3904e13. ´ lvarez JL, Blanco D. Performance model for parabolic trough solar thermal power plants with [14] Garcı´a IL, A thermal storage: comparison to operating plant data. Solar Energy 2011;85(10):2443e60. [15] Kalogirou SA. Solar thermal collectors and applications. Progress in Energy and Combustion Science 2004; 30(3):231e95. [16] Liu JG, Zhao TS, Liang ZX, Chen R. Effect of membrane thickness on the performance and efficiency of passive direct methanol fuel cells. Journal of Power Sources 2006;153(1):61e7. [17] Baldauf M, Preidel W. Status of the development of a direct methanol fuel cell. Journal of Power Sources 1999;84(2):161e6. [18] Song C. Fuel processing for low-temperature and high-temperature fuel cells: challenges, and opportunities for sustainable development in the 21st century. Catalysis Today 2002;77(1):17e49. [19] Wasmus S, Ku¨ver A. Methanol oxidation and direct methanol fuel cells: a selective review. Journal of Electroanalytical Chemistry 1999;461(1):14e31.

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[20] Ali AHH, Noeres P, Pollerberg C. Performance assessment of an integrated free cooling and solar powered single-effect lithium bromide-water absorption chiller. Solar Energy 2008;82(11):1021e30. [21] Riffat SB, Qiu G. Comparative investigation of thermoelectric air-conditioners versus vapour compression and absorption air-conditioners. Applied Thermal Engineering 2004;24(14):1979e93. [22] Gomri R, Hakimi R. Second law analysis of double effect vapour absorption cooler system. Energy conversion and management 2008;49(11):3343e8.

CHAPTER

COMPARATIVE STUDY OF TWO SOLAR CASCADE ABSORPTIONCOMPRESSION REFRIGERATION SYSTEMS BASED ON ENERGY AND EXERGY METHODS

2.14

Fateme A. Boyaghchi, Motahare Mahmoodnezhad Alzahra University, Tehran, Iran

1. INTRODUCTION Vapor compression-absorption cascade refrigeration systems (CACRSs) are novel cycles that can be used instead of vapor compression refrigeration systems (CRSs) or vapor absorption refrigeration systems (ARSs) in order to save energy. The required electricity in these cycles is less than that of CRSs and cooling load can be provided by using low-temperature energy sources such as solar energy. Recently, many researchers have focused on reducing energy consumption on refrigeration cycles by studying CACRSs. Chinnappa et al. [1] studied the solar-assisted CACRS integrated with a flat-plate solar collector for air conditioning applications in tropical areas. The desired system contained an R22 compression stage and an NH3eH2O fluid pair single-effect absorption section. Results showed a considerable saving in energy in comparison with the individual CRS. Kairouani and Nehdi [2] developed and evaluated a CACRS using geothermal energy. R717, R22, and R134a were selected as refrigerants inside CRS and the ammoniaewater (NH3eH2O) pair for ARS. Results indicated a significant increment in the coefficient of performance (COP) as well as lower electricity consumption for CACRS in comparison with individual refrigeration system under the same operating conditions. Fernandez-Seara et al. [3] evaluated a CACRS integrated with a cogeneration system to produce cooling effects at low temperature. NH3eH2O pair was considered in the absorption stage and CO2 and NH3 in the compression stage. The impacts of the major parameters were evaluated on the thermal COP and the global refrigeration-cogeneration performance was calculated to assess the adaptability between the refrigeration and the cogeneration system. Garimella et al. [4] presented and analyzed a high-temperature lift CACRS for the naval ship application to produce low- and medium-temperature refrigerants, respectively, for high-heat flux Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00026-3 Copyright © 2018 Elsevier Inc. All rights reserved.

457

458

CHAPTER 2.14 COMPARATIVE STUDY OF TWO SOLAR CACRS

electronics applications and space conditioning. LiBreH2O was selected for the single-effect absorption stage, while CO2 was used in the compression stage. Sensitivity study showed very high COPs and low electricity demand relative to CRS. Seyfouri and Ameri [5] developed and analyzed the various layouts of CACRS to produce a low temperature. The R22 compression stage was operated by the microturbine, and the LiBreH2O absorption stage was driven by the microturbine waste heat. Results implied that these configurations had high COPs and less energy consumption than CRS, and the best layout for energy savings belonged to a system with two-stage compression refrigeration equipped with an intercooler between the compressors and a subcooler at the condenser outlet. Cimsit and Ozturk [6] compared the performances of CACRS considering LiBreH2O and NH3eH2O fluid couple in the absorption stage, and various refrigerants (e.g., R134a, R410A, and NH3) in the vapor compression stage. Outcomes indicated that the electrical energy consumption in VCACRS was 48%e51% lower than the equivalent CRS, and applying H2OeLiBr instead of NH3eH2O pair in the absorption stage caused 35% reduction and 33% increment, respectively, in the heat energy requirement in the generator and the overall COP of the system. Jain et al. [7] showed that the power consumption in CACRS was reduced by 61% and COP of the compression stage was improved by 155% as compared with common CRS. They also found that R410a, R407C, and R134a, the environment friendly refrigerants, had the potential to replace R22. Moreover, they estimated the size and the cost of CACRS with LiBreH2O pair and R410a in the absorption and compression stages, respectively. Results showed that increasing the period of operation and the rate of interest improved the investment and the total annual costs of the system [8]. Cimsit et al. [9] modeled and optimized the CACRS from the exergoeconomic perspective. LiBreH2O and R134a were considered for each stage, and nonlinear simplex direct search method was used to maximize the exergetic COP and minimize the cost. Boyaghchi et al. [10] proposed and optimized a novel CACRS integrated with a flat-plate solar collector with copper oxide (CuO)-water nanofluid heat transfer medium due to its high effectiveness [11e13]. The proposed system consisted of a single-effect LiBreH2O ARS and an ejector-enhanced dual evaporator DECRS with R134a, R407C, R22, R1234ze, and R1234yf as refrigerants. They concluded that R134a was the best fluid from the thermodynamic viewpoint, and R1234ze was identified as the best refrigerant from the exergoeconomic viewpoint. Moreover, the thermodynamic and the economic performances of the system were optimized using an evolutionary algorithm. This chapter is an attempt to propose and compare the performances of the system mentioned in Ref. [10] by adding an ejector between condenser 2 and vapor generator in the absorption stage. The thermodynamic performances of both systems are evaluated by changing the various design parameters, namely, nanoparticles volume fraction, low pressure in the absorption stage, collector area, and tilt angle. The LiBreH2O is applied as a fluid pair in absorption and four working fluids, including R134a, R507A, R1234yf, and R1234ze, are applied in DECRS as a fluid pair in ARS section due to their thermophysical properties, low ozone depletion potential, and greenhouse warming potential [14e16].

2. SYSTEM DESCRIPTION Fig. 1A illustrates the general flow sheet of vapor compression-absorption cascade refrigeration system (system 1) proposed in Ref. [10] where a single-effect ARS [6,17] and an alternate two-phase ejector cycle [18] are coupled together with a cascade condenser at which the refrigerant vapor in

2. SYSTEM DESCRIPTION

FIGURE 1 The cascaded vapor compression-absorption system (A) system 1 and (B) system 2.

459

460

CHAPTER 2.14 COMPARATIVE STUDY OF TWO SOLAR CACRS

DECRS is condensed by rejecting heat to water in ARS; Fig. 1B shows the ejector-enhanced cascade cycle (system 2), which is equipped with an ejector in ARS. In system 1, water, as the refrigerant in vapor phase leaves evaporator 3, is captured in the absorber by the low-pressure strong solution coming from the pressure-reduction valve, rejecting heat to air. The weak solution exits the absorber and is pressurized up to the generator pressure by means of pump 1. Then it is preheated by receiving the heat from the strong solution leaving the generator when passing through the solution heat exchanger. In the generator, the solution boils by receiving the heat from the nanofluid circulating inside the solar collector subsystem and is separated into vapor and strong solution streams. The vapor phase condenses through condenser 2, rejecting heat to air. Then it is throttled by means of expansion valve 1. The difference between systems 1 and 2 is that an ejector is located at the entrance of condenser 2 to provide the lower operating pressure and temperature in condenser 2. The ejector motive fluid is the water vapor coming from the generator. On the other hand, the refrigerant pressure is increased by the compressor in the vapor compression stage, and it is led to condenser 1. After condensing, some portion of refrigerant pressure is dropped as it passes through the expansion valve and enters evaporator 2 to produce cooling effect by removing heat from the air of the refrigerator compartment, and the remaining refrigerant enters the ejector as the primary flow and is mixed with the stream leaving evaporator 2. Then the refrigerant is directed to evaporator 1 to produce the cooling effect in the second refrigerator compartment.

3. MODEL SIMULATION The governing equations and thermodynamic properties of solutions are implemented by applying the Engineering Equation Solver (EES) software. To simplify the models, some thermodynamic assumptions are made as follows: 1. 2. 3. 4.

All components are considered to operate under steady-state conditions. Pressure losses through the pipelines and heat losses in and to the surrounding areas are neglected. Refrigerants at the exit of evaporators, cascade condenser, and condenser are saturated. The compression process in the compressor is irreversible, and isentropic efficiency is assumed constant. 5. The strong and weak solutions coming from the generator and absorber, respectively, are saturated. 6. The isenthalpic process is considered within the expansion valves. The basic models for all components during the steady-state process including mass, energy and LiBr mass balance equations are expressed as [7]: •

Mass balance:

X

_ ¼ m

in

_ m

(1)

_ mx

(2)

out

in

X

X

_ ¼ mx

X out

3. MODEL SIMULATION

461

_ refers to the mass flow rate and x indicates the LiBr concentration. The subscripts In Eqs. (1) and (2), m “in” and “out” are inlet and outlet streams, respectively. • Energy balance: X X _ ¼ _  _ Q_  W mh mh (3) out

in

_ are heat transfer rate and power, respectively, and h is the specific enthalpy. Here, Q_ and W

3.1 THE FLAT-PLATE COLLECTOR SIMULATION The flat-plate solar collector is selected to provide the required heating load for both systems. The useful heat gained by the collectors, Q_ u , can be estimated by [19]:    Q_ u ¼ AColl FR Gt ðsaÞav  UL Tnf;in  Tamb (4) In Eq. (4), AColl and ðsaÞav are, respectively, the average transmissivityeabsorptivity product falling on the collector, and collector area, Gt , is the total irradiation on a tilted collector, UL refers to the overall heat transfer coefficient, and FR represents the collector heat removal factor, given by: " !# _ 23 cp;nf m UL F0 AColl FR ¼ 1  exp  (5) _ 23 cp;nf AColl UL m Here, cp,nf represents the specific heat of nanofluid, and F0 is the collector efficiency factor, given by [19]: F0 ¼

 WColl

1 UL 1 1 þ UL ½Do þ ðWColl  Do ÞF pDi lnf



(6)

In Eq. (6), W is the collector width, D and l are tube diameter and heat transfer coefficient inside the tubes, and factor F is defined as [19]: F¼

tanh½mðWColl  Do Þ=2 mðWColl  Do Þ=2 rffiffiffiffiffiffi UL m¼ kd

(7) (8)

where k and d are thermal conductivity and plate thickness, respectively.

3.2 THE THERMAL STORAGE TANK SIMULATION A thermal storage tank operates as a buffer between the solar collector and refrigeration subsystems. It is assumed that the thermal storage tank is completely insulated and the nanofluid is well mixed so that its temperature Tnf is only the function of time and obtained by the energy balance as follows [19]: _ 23 cP ÞTST ðm

dTTST ¼ Q_ Coll  Q_ load  ðUAÞTST ðTTST  Tamb Þ dt

(9)

462

CHAPTER 2.14 COMPARATIVE STUDY OF TWO SOLAR CACRS

Here, Q_ load is the energy discharged to refrigeration system and can be estimated as:   _ nf cp;nf Tnf  Tnf;in Q_ load ¼ m

(10)

The thermophysical properties of nanoparticles, i.e., density, viscosity, specific heat, and thermal conductivity [11,13,20], can be calculated by Eqs. (11)e(13), respectively: rnf ¼ ð1  4Þrbf þ rnp

(11)

where 4 refers to the nanoparticle volume fraction, rnp is the nanoparticle density set to be 6000 kg/m3 for CuO, and rnf is the density of the base fluid, considered water in this work. mnf ¼ ð1 þ 2:54Þmbf cp;nf ¼

ð1  4Þðrcp Þbf þ 4ðrcp Þnf rnf

(12) (13)

In Eq. (13), cp,np is the specific heat of nanoparticles given to be 0.551 kJ/kg K for CuO, and cp,bf indicates the specific heat of the base fluid. knf knp þ ðSH  1Þkbf  ðSH  1Þ4ðkbf  knp Þ ¼ knp þ ðSH  1Þkbf  4ðkbf  knp Þ kbf

(14)

The shape factor, SH, is considered to be 3 for the spherical shape of nanoparticle, knp is the thermal conductivity of nanoparticle, given to be 33 W/m K [11], and kbf is the thermal conductivity of base fluid.

3.3 THE EJECTOR SIMULATION An ejector is a simple structure equipment with no moving parts, low capital investment and maintenance cost, as well as long lifetime. Moreover, using an ejector in refrigeration cycles provides better performance and vast selection for environmentally friendly refrigerants in the compression stage [21]. Ejectors are classified into two types: constant-pressure and constant-area. In this work, the constantpressure-type ejector is selected owing to its better performance than the constant-area one [22]. The ejector simulation is implemented based on the one-dimensional constant-pressure flow model. In this model, the pressure of stream at the exit of nozzle remains fixed along the mixing chamber, and its value is gained by adding the given pressure drop, assuming the value for entrainment ratio and the efficiencies values of 90%, 80%, 75%, and 85% for the motive nozzle (hmn), suction nozzle (hsn), mixing section (hms), and diffuser (hd), respectively, and applying the energy equations for each section. By this procedure, the entrainment ratio of the ejector related to state parameters can be estimated by iteration. The detailed relations can be obtained from Ref. [22].

3.4 EXERGY ANALYSIS By neglecting the kinetic and potential exergies, the total exergy of the stream is defined as [23]: _ ¼ Ex _ Ph þ Ex _ Ch Ex

(15)

5. RESULTS AND DISCUSSION

463

_ Ph , can be calculated using Eq. (16): The physical exergy, Ex _ Ph ¼ m½ðh _ Ex  h0 Þ  T0 ðs  s0 Þ (16) _ To calculate the chemical exergy, ExCh , of LiBr-water solution in the absorption stage, the following relation is used [24e26]:

  x 1x _ ExCh ¼ m ex0Ch;LiBr þ ex0Ch;H2 O (17) MLiBr MH2 O In Eq. (17), ex0Ch;LiBr is the standard chemical exergy of LiBr and ex0Ch;H2 O is the standard chemical exergy of water [25]. To assess the performance of a system from the second law perspective, the product and the fuel _ P , indicates the exergies are identified for each component of the system. The product exergy, Ex _ F , indicates the source desired result produced by the component or the system, and the fuel exergy, Ex _ D , is calculated from that is consumed in generating the product exergy. The exergy destruction rate, Ex the exergy rate balance as follows: _ F;k  Ex _ P;k  Ex _ L;k _ D;k ¼ Ex Ex

(18)

_ L is the exergy loss rate occurring within each component. Here, Ex

4. THERMODYNAMIC PERFORMANCE The daily thermal coefficient of performance of both systems is calculated as [27]:  R _ Evap1 þ Q_ Evap2 dt Q t  COPth ¼ R  _ Comp þ W _ Pump1;2 þ ðGt AFPC Þ dt W t The daily exergetic coefficient of performance of each system can be expressed as: R _ t ExP;tot dt  COPex ¼ R  _ Comp þ Ex _ Pump1;2 þ Ex _ sun dt Ex

(19)

(20)

t

_ sun is the exergy of the sun as follows [28]: where Ex



4 ! 1 T 4 T 0 0 _ sun ¼ Gt AColl 1 þ Ex  3 Tsun 3 Tsun

(21)

Here, Tsun is the sun temperature set to be 6000K.

5. RESULTS AND DISCUSSION Table 1 lists the input data to simulate the proposed systems, and Table 2 indicates the results of modeling for both systems. From the results obtained, adding an ejector has several advantages as follows: condenser 2 inlet pressure drops from 8.931 to 2.416 kPa leading to the decrement in its temperature from 364 to

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CHAPTER 2.14 COMPARATIVE STUDY OF TWO SOLAR CACRS

Table 1 Value of Inputs at Design Point Parameter

Value

Simulation date Dead temperature, To ( C) Dead pressure, Po (kPa) Nanoparticles volume fraction, 4 _ 16 (kg/s) Mass flow rate of strong solution, m Solar collector tilt angle, b (degrees) Solar collector area, AColl (m2) Pressure drop of ejector 1, DPEjc1 (kPa) Pressure drop of ejector 2, DPEjc2 (kPa) Area ratio of ejector 1, AREjc1 Area ratio of ejector 2, AREjc2 Coolant inlet temperature of absorber, T29 ( C) Coolant outlet temperature of absorber, T30 ( C) Temperature of absorber, TAbs ( C) Low pressure of absorption cycle, Plow (kPa) High pressure of absorption cycle, Phigh (kPa) Thermal storage tank number Density of steel, rsteel (kg/m3) Conductivity of steel, ksteel (kW/m K)

June 29 st 20 101.3 0.01 0.334 30 696 5 0.5 7 2 35 38 40 1.2 8.931 10 8050 0.42

339.4K. Moreover, its mass flow rate rises from 0.026 to 0.037 kg/s, and consequently the heat transfer through the cascade grows from 60 to 89.39 kJ/kg, leading to increment in cooling loads inside evaporators 1 and 2 due to the increase of mass flow rate of refrigerant in the compression stage. According to Table 2, the total input energy and exergy rates are almost constant for all refrigerants. For each system, R507A has the highest daily thermal coefficient of performance followed by R134a, R1234ze, and R1234yf, respectively. In systems 1 and 2, the maximum thermal performances are obtained within 9.128% and 13.540%, respectively, due to the high cooling effects produced within 55.02 and 81.97 kW, respectively. Applying system 2 improves the thermal performance within 48.33% averagely. On the other hand, R1234ze produces the maximum exergetic performances for both systems, and R1234yf, R134a, and R507A are in the next ranking. In systems 1 and 2, the maximum daily exergetic performance belongs to R1234ze with the values of 0.3957% and 0.6463%, respectively. Obviously, in system 2, the exergetic performance is improved within 63.33% relative to system 1.

6. PARAMETRIC STUDY This section presents the effects of major design input parameters such as nanoparticles volume fraction (4), collector tilt angle (b), collector area (AColl), and low pressure (Plow) on the daily thermal coefficient of performance (COPth) and exergetic coefficient of performance (COPex) for both desired systems.

Table 2 The Thermodynamic Performance Simulation for the Desired System System 1

System 2

R134a

R507A

R1234yf

R1234ze

R134a

R507A

R1234yf

R1234ze

Total inlet energy rate, E_ in (kW) Total inlet exergy rate, _ in (kW) Ex Total product exergy _ P;tot (kW) rate, Ex Daily thermal coefficient of performance, COPth (%) Daily exergy coefficient of performance, COPexe (%) Cooling load, Q_ Evap1 þ Q_ Evap2 (kW) Total exergy destruction, _ D;tot (kW) Ex

603

602.8

603

605.6

605.5

605.2

605.6

603

564

563.8

564.1

564.1

566.6

566.3

566.7

566.6

2.148

2.032

2.190

2.232

3.547

3.403

3.603

3.662

9.093

9.128

9.076

9.085

13.490

13.540

13.460

13.480

0.3809

0.3604

0.3883

0.3957

0.6260

0.6009

0.6357

0.6463

54.83

55.02

54.73

54.78

81.68

81.97

81.54

81.61

556.8

556.8

556.9

556.8

556.9

556.9

557

556.9

6. PARAMETRIC STUDY

Term

465

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CHAPTER 2.14 COMPARATIVE STUDY OF TWO SOLAR CACRS

6.1 NANOPARTICLES VOLUME FRACTION INFLUENCE Fig. 2 illustrates the effects of volume fraction of nanoparticles on COPsth of both systems for all studied refrigerants. Referring to results, the growth of nanoparticles from 0 to 0.015 leads to a rise in the mass flow rate of nanofluid passing through the solar subsystem and consequently the mass flow rate of vapor generator in both systems. Installing an ejector adds the mass flow rate along branch 36 to the mass flow rate exiting the generator (point 19), causing the increment of the heat transfer within the cascade heat exchanger in system 2 related to system 1. Therefore, the mass flow rate of the refrigerant circulating through the compression cycle grows and increases the cooling loads by means of evaporators 1 and 2. From the results, it may be concluded that R507A is the best refrigerant in both systems from the first law perspective so that the average COPsth calculated for systems 1 and 2 are 9.044% and 13.42%, respectively. In this case, the average cooling loads are obtained, respectively, of about 54.51 and 81.21 kW. Moreover, the increases of the nanoparticles volume fraction show a positive impact on COPsth as well as cooling loads, respectively, within 5.57% and 5.62% for system 1. They are also calculated, respectively, at 5.51% and 5.62% for system 2. The effects of nanoparticles volume fraction on COPex of both systems are illustrated in Fig. 3. In this case, as nanoparticles increase, the consumed power of pumps 1 and 2 remains almost constant while the input power of compressor rises, and according to the mentioned reasons in Fig. 2, the total inlet power of the overall system grows leading to the increment in the total input fuel of the systems for all refrigerants. Due to the high value of the mass flow rate in system 2, the required power is higher than that of system 1. This reason leads to higher COPex of system 2 relative to system 1. According to the results obtained, R1234ze has the maximum COPex (due to the high total product exergy) in both systems. In this case, COPex increases from 0.375% to 0.4041% and from 0.6167% to 0.6609% for systems 1 and 2, respectively, while the highest increments are observed within 7% and 7.5%, respectively, for systems 1 and 2 when R507A is applied as a refrigerant.

FIGURE 2 The effects of nanoparticles on the thermal coefficient of performance of both systems.

6. PARAMETRIC STUDY

467

FIGURE 3 The effects of nanoparticles on the exergetic coefficient of performance of both systems.

6.2 COLLECTOR TILT ANGLE INFLUENCE Fig. 4 implies the effects of the collector tilt angle from 10 to 32 degrees on COPsth of the proposed systems. At the range of 10 to 32 degrees, the outlet temperature of the heat transfer medium at the exit of the solar collector increases and then reduces, leading to variations of the generator inlet temperature. Indeed, there is an optimum tilt angle (about 21 degrees) at which COPth has a drastic increment. Due to the constant values of mass flow rate and specific heat of nanofluid inside the solar subsystem, the value of heat transfer in the generator first increases and then decreases. Results show that at the range of 10 to 22 degrees, the increment of the generator outlet mass flow rate and its influence on the bottom cycle, the cascade heat transfer grows, causing the increment in the mass flow rate of the compression stage. Therefore, cooling produced via evaporators 1 and 2 increases and improves the COPth. Reverse behavior is observed for the range of 21 to 32 degrees. These variations are valid for both systems, but adding an ejector and increment of cascade mass flow rate (due to the mass flow rate of branch 36) in system 2 causes the higher heat transfer in the cascade in system 2 relative to system 1. On the other hand, according to the equal value of absorbed solar irradiation for both systems and slight variations of power consumed, the changes of COPsth depend on the cooling effect produced. Since cooling effect lessens in all cases, COPth reduces. From Fig. 4, the maximum COPsth belonged to R407A and is calculated within 9.678% and 14.36%, respectively, for systems 1 and 2, at which the cooling effects increase up to 60.88 and 90.69 kW, respectively. Fig. 5 shows the effects of the collector tilt angle on COPsex of the both systems. The received irradiation reduces from 635.9 to 590 kW as tilt angle increases from 10 to 32 degrees for all refrigerants. As a result, the solar exergy decreases drastically so that the increase of input power does not affect the total fuel exergy of the systems. Therefore, it lessens with the same slope for all refrigerants. As mentioned in the previous section, at the range of 10 to 21 degrees, with an increase in the generator mass flow rate and its influence on the compression stage, the heat transfer inside the

468

CHAPTER 2.14 COMPARATIVE STUDY OF TWO SOLAR CACRS

FIGURE 4 The effects of collector tilt angle on the thermal coefficient of performance of both systems.

FIGURE 5 The effect of collector tilt angle on the exergetic coefficient of performance of both systems.

cascade heat exchanger grows, leading to the increment in mass flow rate of the compression section, and, consequently, the total cooling effect produced inside the evaporators 1 and 2 increases while this effect reverses at the range of 21 to 32 degrees. Therefore, the total product exergy of the evaporators first increases and then decreases. Moreover, the total product exergy of the system is reduced for all refrigerants. Since the growth rate of the total product exergy is higher than the total fuel exergy, COPex increases, and then with the decrement of ratio, COPex reduces. From the results, it becomes clear that

6. PARAMETRIC STUDY

469

due to the high mass flow rate in system 2 relative to system 1, COPex in system 2 is greater than that of system 1 for all refrigerants. In these cases, R1234ze with maximum COPsex about 0.4286% and 0.7055% for systems 1 and 2, respectively, is the best refrigerant.

6.3 COLLECTOR AREA INFLUENCE Fig. 6 illustrates the effects of the collector area on COPsth of both systems. As the collector area increases from 670 to 770 m2, the received irradiation increases and slight increments in the collector outlet temperature as well as the generator inlet temperature are observed. Since the mass flow rate and specific heat of nanofluid inside the solar subsystem remain constant, the amount of generator heat transfer rises, and, consequently, the temperature as well as the mass flow rate of point 19 grow. The increase of the generator mass flow rate affects the bottom cycle so that the cascade heat transfer can rise, leading to the increment in the mass flow rate of the compression stage. Therefore, the cooling produced via evaporators 1 and 2 increases. On the other hand, the required power of pumps 1 and 2 as well as the compressor increase because of the mass flow rate growth, but the high solar energy received causes the increment in the collector area and finally COPth is reduced. This trend is similar for both systems, but adding an ejector causes the high mass flow rate passing through the cascade heat exchanger as well as heat transfer related to system 1. As a result, the total consumed power in system 2 is more than that of system 1, while the adsorbed energy increasing is the same for both systems. Thus, COPth reduction in system 2 is higher than that of system 1. As clearly observed from Fig. 6, R507A shows the highest value for COPsth and cooling effects as well as the same reduction behavior for both systems. At the highest amount of collector area, the values of COPsth reduce, respectively, up to 8.78% and 12.17% for systems 1 and 2, while the cooling effects have the highest values within 57.79 and 86.07 kW for systems 1 and 2, respectively, which are higher than the values of other refrigerants.

FIGURE 6 The effects of the collector area on the thermal coefficient of performance of both systems.

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CHAPTER 2.14 COMPARATIVE STUDY OF TWO SOLAR CACRS

FIGURE 7 The effects of the collector area on the exergetic coefficient of performance of both systems.

Fig. 7 illustrates the behaviors of COPsex for both proposed systems when the collector area changes from 670 to 770 m2. By increasing the collector area, the received solar irradiation increases, leading to the increment in solar exergy from 537.8 to 618 kW, and, consequently, the fuel exergy of the overall system for all refrigerants increases within 14.8%. Due to the lower value of the product exergy relative to the fuel exergy for all refrigerants, COPex of both systems decreases, however, COPex of system 2 is higher than that of system 1 (because of high value of mass flow rate). Obviously, R1234ze in both systems with the highest reduction in COPex has the maximum values of COPex and cooling exergies so that the product exergy increases from 2.183 to 2.368 kW (about 8.48% increment) in system 1 and from 3.577 to 3.901 kW (about 9.06% increment) in system 2.

6.4 LOW PRESSURE INFLUENCE Fig. 8 shows the effects of low pressure on COPsth of desired systems. It becomes clear from the results that increasing Plow causes the reduction in the mass flow rate of point 19 for all refrigerants. Therefore, the heat transfer through the cascade heat exchanger drops, leading to the decrement in refrigeration effects inside of evaporators 1 and 2. On the other hand, the variation of the low pressure cannot affect the solar subsystem. Thus, the required power of pump 2 does not change while the power of pump 1 reduces slightly. Moreover, the required power of the compressor rises due to the increments in the pressure and temperature of point 2. As a result, the total consumption power of the systems increases for all refrigerants. Due to the higher decrements of heat transfers inside the evaporators 1 and 2 relative to the inlet power of the systems, COPth of both systems lessens for all refrigerants. This trend occurs in system 2 with higher effect due to the increment of mass flow rate. Outcomes clarify that R134a with 6.99% reduction in cooling effect (from 54.83 to 51 kW) and minimum drop in COPth from 9.093% to 8.435% (about 7.24% decrement) seems to be the convenient refrigerant for high values of Plow.

6. PARAMETRIC STUDY

471

FIGURE 8 The effects of low pressure on the thermal coefficient of performance of both systems.

The effects of exergetic performance of the desired systems versus the variation of the low pressure are plotted in Fig. 9. As mentioned before, the increment of the low pressure does not affect the solar subsystem, and it increases the power of the compressor for all refrigerants. Moreover, the total product exergy system decreases as the low pressure increases for all refrigerants. As previously mentioned, due to the increment of the mass flow rate of system 2, its COPex is higher than that of system 1. According to the results, although R1234ze causes a large COPth in both systems in

FIGURE 9 The effects of low pressure on the exergetic coefficient of performance of both systems.

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CHAPTER 2.14 COMPARATIVE STUDY OF TWO SOLAR CACRS

comparison with other refrigerants, the lowest reduction in COPth occurs for R134a so that COPth can be reduced within 7.24% and 11.27% in systems 1 and 2, respectively. In this case, the cooling load and COPth show the higher values near 2 bars.

7. CONCLUSIONS A modified ejector-enhanced cascade LiBr-water absorption-compression refrigeration cycle (system 2) is proposed and compared with the conventional one (system 1) thermodynamically. The desired systems are powered by solar energy and CuO-water nanofluid is selected as transport medium. The sensitivity analysis is conducted to assess the performances of desired systems for R134a, R507A, R1234yf, and R1234ze in the compression section. The major following conclusions can be drawn about this research: •

• • • •

The thermodynamic simulation of desired systems indicates that the greatest COPth of systems 1 and 2 occurs for R507A within 9.128% and 13.540%, respectively. Moreover, the maximum COPsex in systems 1 and 2 are calculated for R1234ze by about 0.3957% and 0.6463%, respectively. The increment of nanoparticles increases COPth and COPex of desired systems so that COPth and COPex of system 2 can be higher within 58% and 60%, respectively, with those of system 1. In both systems, collector tilt angle of 21 degrees possesses the highest COPth and COPex for all refrigerants. The increment of the low pressure from 1.2 to 2 kPa causes the decrement in COPth and COPex of both systems for all refrigerants. For all cases, R507A shows better COPth and R1234ze indicates more convenient COPsex in both desired systems.

NOMENCLATURE A COP cp D ex ex0 _ Ex F F0 FR Gt h k M _ m Q_ T U W

Area (m2) Coefficient of performance Specific heat (kJ/kg K) Riser diameter (m) Specific exergy (kJ/kg K) Standard molar specific exergy (kJ/kmol K) Exergy flow rate (kW) Fin efficiency Collector efficiency factor Heat removal factor Solar insolation on tilted surface Enthalpy (kJ/kg) Thermal conductivity (kW/m K) Molecular weight (kg/kmol) Mass flow rate (kg/s) Heat flow rate (kW) Temperature ( C) Overall heat transfer coefficient (W/m2 K) Collector width (m)

REFERENCES

_ W x

473

Power of compressor (kW) Concentration of LiBr solution

Greek Symbols m b d l r 4

Viscosity (kg/s m) Collector tilt angle (degrees) Plate thickness (m) Heat transfer coefficient inside the tubes (W/m2 K) Density (kg/m3) Nanoparticles volume fraction (%)

Subscripts 0 1, 2. amb ch Coll Comp D Ejc Evap ex F i in k L load nf np o out ph Pump sun th tot TST u

Environmental state Cycle locations, see Figs. 1 and 2 Ambient Chemical component Collector Compressor Destruction Ejector Evaporator Exergetic Fuel Inner Entering streams The kth component of the system Loss Load Nanofluid Nanoparticles Outter Exiting streams Physical component Pump Sun Thermal Total Thermal storage tank Useful

REFERENCES [1] Chinnappa J, et al. Solar-assisted vapor compression/absorption cascaded air-conditioning systems. Solar Energy 1993;50(5):453e8. [2] Kairouani L, Nehdi E. Cooling performance and energy saving of a compressioneabsorption refrigeration system assisted by geothermal energy. Applied Thermal Engineering 2006;26(2):288e94. [3] Ferna´ndez-Seara J, Sieres J, Va´zquez M. Compressioneabsorption cascade refrigeration system. Applied Thermal Engineering 2006;26(5):502e12.

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CHAPTER 2.14 COMPARATIVE STUDY OF TWO SOLAR CACRS

[4] Garimella S, Brown AM, Nagavarapu AK. Waste heat driven absorption/vapor-compression cascade refrigeration system for megawatt scale, high-flux, low-temperature cooling. International Journal of Refrigeration 2011;34(8):1776e85. [5] Seyfouri Z, Ameri M. Analysis of integrated compressioneabsorption refrigeration systems powered by a microturbine. International Journal of Refrigeration 2012;35(6):1639e46. [6] Cimsit C, Ozturk IT. Analysis of compressioneabsorption cascade refrigeration cycles. Applied Thermal Engineering 2012;40:311e7. [7] Jain V, Kachhwaha S, Sachdeva G. Thermodynamic performance analysis of a vapor compressione absorption cascaded refrigeration system. Energy Conversion and Management 2013;75:685e700. [8] Jain V, Sachdeva G, Kachhwaha S. NLP model based thermoeconomic optimization of vapor compressioneabsorption cascaded refrigeration system. Energy Conversion and Management 2015;93: 49e62. [9] Cimsit C, Ozturk IT, Kincay O. Thermoeconomic optimization of LiBr/H2O-R134a compression-absorption cascade refrigeration cycle. Applied Thermal Engineering 2015;76(0):105e15. [10] Boyaghchi FA, Mahmoodnezhad M, Sabeti V. Exergoeconomic analysis and optimization of a solar driven dual-evaporator vapor compression-absorption cascade refrigeration system using water/CuO nanofluid. Journal of Cleaner Production 2016;139:970e85. [11] Alim M, et al. Analyses of entropy generation and pressure drop for a conventional flat plate solar collector using different types of metal oxide nanofluids. Energy and Buildings 2013;66:289e96. [12] Faizal M, et al. Energy, economic and environmental analysis of metal oxides nanofluid for flat-plate solar collector. Energy Conversion and Management 2013;76:162e8. [13] Khairul M, et al. Heat transfer and thermodynamic analyses of a helically coiled heat exchanger using different types of nanofluids. International Journal of Heat and Mass Transfer 2013;67:398e403. [14] Zhang T, Mohamed S. Conceptual design and analysis of hydrocarbon-based solar thermal power and ejector cooling systems in hot climates. Journal of Solar Energy Engineering 2015;137(2):021001. [15] Rayegan R. Exergoeconomic analysis of solar organic rankine cycle for geothermal air conditioned net zero energy buildings. 2011. [16] Ayub Z. Status of enhanced heat transfer in systems with natural refrigerants. Journal of Thermal Science and Engineering Applications 2010;2(4):044001. [17] Misra R, et al. Thermoeconomic optimization of a single effect water/LiBr vapour absorption refrigeration system. International Journal of Refrigeration 2003;26(2):158e69. [18] Ishizaka N, et al. Ejector type refrigerating cycle. 2009 [Google Patents]. [19] Kalogirou SA. Solar energy engineering: processes and systems. Academic Press; 2013. [20] Said Z, et al. Experimental investigation of the thermophysical properties of Al2O3-nanofluid and its effect on a flat plate solar collector. International Communications in Heat and Mass Transfer 2013;48:99e107. [21] Saleh B. Performance analysis and working fluid selection for ejector refrigeration cycle. Applied Thermal Engineering 2016;107:114e24. [22] Li H, et al. Performance characteristics of R1234yf ejector-expansion refrigeration cycle. Applied Energy 2014;121:96e103. [23] Bejan A, Tsatsaronis G. Thermal design and optimization. John Wiley & Sons; 1996. [24] Szargut J. Chemical exergies of the elements. Applied Energy 1989;32(4):269e86. [25] Bejan A, Moran MJ. Thermal design and optimization. John Wiley & Sons; 1996. [26] Szargut J, Morris DR, Steward FR. Exergy analysis of thermal, chemical, and metallurgical processes. 1987. [27] Sirwan R, et al. Thermodynamic analysis of an ejector-flash tank-absorption cooling system. Applied Thermal Engineering 2013;58(1):85e97. [28] Petela R. Exergy of undiluted thermal radiation. Solar Energy 2003;74(6):469e88.

CHAPTER

COMPARATIVE STUDY OF ACTIVE AND PASSIVE COOLING TECHNIQUES FOR CONCENTRATED PHOTOVOLTAIC SYSTEMS

2.15

Ali Radwan, Mohamed Emam, Mahmoud Ahmed
EgypteJapan University of Science and Technology (E-JUST), Alexandria, Egypt

1. INTRODUCTION Using concentrated sunlight on photovoltaic (PV) cells and replacing expensive solar cells with lowerpriced concentrating lenses or mirrors significantly lowers the cost of solar electricity. The efficiency of PV cells is 20% less than that of silicon solar cells and approximately 40% less than that of multijunction solar cells [1]. The remaining part of the absorbed solar energy is converted into heat, causing the temperature to rise in PV cells. This generated thermal energy in the PV systems causes junction damage and leads to a major decrease in the cells’ electrical efficiency [1,2]. Therefore, adapting an efficient cooling technique to CPV systems achieves higher electrical efficiency and allows for the design of higheconcentration ratio (CR) systems. Furthermore, the extracted thermal energy could be used for domestic or industrial applications. Major design considerations for the cooling of CPV cells are the cell temperature, the uniformity of temperature, the usability of thermal energy, reliability and simplicity, and consumed power [3]. Because CPV cells are temperature-sensitive devices, an efficient thermal management technology is becoming essential to provide high performance and increase PV cell lifetime. However, oldfashioned thermal management technologies such as large-scale liquid cooling systems have limited use because of the low rate of heat dissipation, complexity, and large consumption of manufacturing material. Therefore, it is essential to develop novel thermal management devices that dissipate large amounts of heat rapidly to keep these systems operating efficiently. Moreover, there are many ways to maintain or improve on the compactness of the design of such devices, using active or passive cooling techniques. In active cooling, external energy is required to cool the solar cells. Accordingly, a fraction of the electrical output power of the PV cell is consumed to circulate flow and overcome friction in the thermal absorber. On the other hand, active cooling is more easily controlled than passive cooling.


On leave from the Mechanical Engineering Department, Assiut University, Assiut 71,516, Egypt.

Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00027-5 Copyright © 2018 Elsevier Inc. All rights reserved.

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Although active cooling might be cost-effective and less efficient owing to the consumption of a fraction of output energy, the heat dissipated from the PV cell can be used in other thermal applications [4]. Microchannels and impinging jets are promising options for the cooling technology of a CPV plant [5]. These small-scale devices are capable of dissipating a large amount of heat flux from hot surfaces [6]. These devices use effective, advanced technology to limit the temperature of high generated heat flux areas [7]. With regard to the use of a microchannel heat sink (MCHS) as an active cooling technique, several investigations have been carried out to study the use of wide microchannel heat sinks (WMCHS) as a simple design and compact cooling system for electronic device applications. Although WMCHS offer a significant heat transfer augmentation, they are associated with a loss in dramatic pressure. Consequently, alternative configurations have been proposed to decrease the incurred pressure loss and simultaneously increase heat transfer. One of those configurations is the manifold microchannel heat sink (MMCHS) [8]. The MMCHS consists of a manifold system that distributes the cooling fluid via multiple inleteoutlet ports. By reducing the flow length through microchannels, a significant reduction in pressure drop was attained. In addition, a decrease in thermal resistance might be achieved by interrupting the thermal boundary layers’ growth. This design was originally suggested by Harpole and Eninger [9], who confirmed a significant enhancement in the heat transfer coefficient relative to the conventional MCHS at a constant pumping power. Rahimi [10] experimentally studied the performance of the combination of microchannels and a PV module as a hybrid PV/thermal (T) system using water as a coolant. In their experiments, the microchannel hydraulic diameter was 0.667 mm and the Reynolds number (Re) varied up to 70. They reported that an approximately 30% increase in the output power compared with uncooled conditions. Based on numerical simulation, Reddy et al. [11] concluded that the optimum dimensions of the microchannel were 0.5 mm in width and an aspect ratio of 8. Moreover, the pressure drop was low in straight flow channels. Bladimir et al. [12] numerically calculated the pressure loss and temperature uniformity of the heated walls of different proposed microchannel configurations. They suggested a new design to achieve a smaller pressure drop and a better flow and temperature uniformity. They recommended using microchannel distributors to cool the CPV cells, fuel cells, and electronics. A two-dimensional (2D) model for CPV systems with an MCHS was developed by Radwan et al. [13,14]. Their study compared the conventional cooling technique and the MCHS technique using CPV systems operating up to CR ¼ 40. They concluded that using a microchannel cooling technique attained the ultimate possible reduction of solar cell temperature owing to the high heat transfer coefficient associated with microscale thermal absorbers. Another promising approach to regulate CPV systems thermally is to use a phase change material (PCM) as a cooling medium. Numerous studies were carried out to integrate PCMs within PV systems for thermal management [15]. The PCM absorbs a significant amount of thermal energy as latent heat during the solideliquid phase transition at a constant phase change temperature. Thus, the electric conversion efficiency increases by preventing overheating of CPV cells during the daytime and releasing it during the night. Browne et al. [16] presented a comprehensive review of PV thermal regulation using PCM as a heat sink. They indicated that although different configurations of PV-PCM systems were investigated, novel designed systems are still needed to overcome complications and enhance efficiency. In addition, Park et al. [17] compared the performance of a PV-PCM module installed on a vertical wall surface with that of a reference PV module without PCM under real outdoor climatic conditions. They concluded that the optimal melting temperature was 25 C regardless of the direction of installation,

2. PHYSICAL MODEL

477

whereas the optimal thickness of PCM varied slightly according to the direction in which the PV-PCM module was installed. In addition, electric power generation from the PV-PCM module increased by 1.0%e1.5% compared with that of the reference PV module without a PCM. Hasan et al. [18] investigated five different types of PCMs with a phase transition temperature of 25  4 C and the latent heat range between 140 and 213 kJ/kg. Experiments were carried out using four different cell-size PV-PCM systems at three different values of solar irradiance ranging from 500 to 1000 W/m2, and the ambient temperature was 20  1 C. Their results showed that using calcium chloride PCM in an aluminum-based PV-PCM system maintained a lower PV temperature for a prolonged period at 1000 W/m2, (up to 30 min at 18 C below the reference system and up to 5 h at 10 C below the reference system). Work by Hasan et al. [19] evaluated the PV-PCM system under different outdoor climatic conditions using calcium chloride hexahydrate CaCl2e6H2O or eutectic of cupric-palmitic acid. They concluded that both systems achieved a higher temperature drop and more power savings compared with the reference PV without the PCM. One main obstructions for PCM applications is the low thermal conductivity of such materials. Therefore, different techniques have been used to increase the thermal performance of PCMs in thermal energy storage and thermal management systems. Fan et al. [20] presented a comprehensive review of experimental and computational investigations to improve the thermal conductivity of PCM for latent thermal energy storage. Moreover, Zhang et al. [21] reviewed and explained advances in the investigation, fabrication, and characterization of composite PCMs along with mathematical models describing the phase change heat transfer characteristics. The insertion of metal fins inside PCM containers is the technique most widely adopted for the thermal regulation of PV cells. Huang et al. [22,23] investigated the effect of fin spacing, width, and fin type on PV-PCM system performance. They noticed that the insertion of fins improved the effective thermal conductivity of PCMs and enhanced the thermal performance of the PV-PCM system. Because the fin spacing was reduced, the maximum temperature was decreased and uniformity of temperature of the PV cells was achieved. However, drawbacks were apparent in that the fins constituted barriers to the liquid PCM movement. Thus, the possibility of convective heat transfer in the molten PCM may have been reduced. Enhancement in conduction within a PCM should balance the suppression of natural convection. In addition, period of thermal regulation decreases as the volume of the PCM is replaced by the metal mass of fins. Based on a survey of the literature, it is clear that a comparison of active and passive thermal management techniques for CPV systems has not been sufficiently investigated. Therefore, the objective of the current chapter was to investigate the performance of the CPV system incorporated with MCHS and PCM in a numerical manner. In the MCHS, the conventional design of WMCH was compared with a new MCHS design as an option to reduce the friction power that is consumed. On the other hand, with the PCM cooling technique, insertion of metal fins inside the PCM to improve thermal conductivity is proposed. Accordingly, a comprehensive 2D model of CPV layers integrated with a proposed heat sink was developed and numerically simulated. The model couples a thermal model for CPV layers and the governing equations of cooling mediums. The current results may provide detailed guidance for the industrial field about the limitations and benefits of each cooling technique.

2. PHYSICAL MODEL In the current chapter, a CPV system combined with active and passive cooling techniques was developed. The active cooling technique was accomplished using the MMCHS design and compared

478

CHAPTER 2.15 COMPARATIVE STUDY OF COOLING TECHNIQUES

with the conventional WMCHS design. The passive cooling technique was attained using a PCM heat sink. Moreover, the effect of incorporating fins in the PCM domain was compared with the conventional rectangular cavity containing the PCM. The investigated solar cell was taken to be a generic polycrystalline cell as characterized by Sandia National Laboratory. The solar cell included various layers, depending on the manufacturing technology used. These layers include a glass cover, an antireflective coating (ARC), silicon layer, an ethylene vinyl acetate (EVA) layer, and a tedlar polyester tedlar (TPT) layer. The 3.0-mm glass cover was made of tempered glass with high transparency. An ARC layer with a thickness of 0.0001 mm (100 nm) was used to limit the reflection of incoming radiation. In addition, a silicon wafer 0.2 mm thick was used in these panels, which were responsible for producing electricity [24]. The silicon layer was embedded in the transparent encapsulation EVA layer, with a thickness of 0.5 mm above and below the silicon layer to fix it and provide both electrical isolation and moisture resistance. Moreover, the TPT polymer layer was a photo-stable layer 0.3 mm thick, made of polyvinyl fluoride. That layer provided additional insulation and moisture protection for the silicon layer [25]. The solar cell length was 12.5 cm. In active cooling, a compact MCHS was attached to the back surface of the TPT layer. It was made of high thermal conductive aluminum and was recommended because it was economical compared with the use of copper for the same thermal regulation of CPV systems [26]. Water was used as a coolant because of its effective properties, because it could accomplish a higher thermal performance for PVeT systems compared with air in PVeT systems [27]. However, to ensure better temperature uniformity and lower friction power, the MMCHS design was proposed to replace the conventional WMCHS design in the CPV systems. The manifold distribution system was placed on the bottom of the flat microchannel in a direction transverse to the main direction of flow. The coolant was pumped in through a common inlet header that branched out into parallel manifold inlet channels. Upon entering the microchannel, the fluid underwent a 90-degrees turn and passed through the microchannel midpitch distance (P/2), removing the generated heat from the concentrated solar cell. Subsequently, it flowed through another 90-degree turn and then exited downward through the outlet manifold channels. Another common outlet header was used to collect the outlet flow rate. The complete layers of the CPV system integrated with the proposed MCHS design are presented in Fig. 1A and B for the WMCHS and MMCHS designs, respectively. In the heat sinks, the thermophysical properties the optical properties of the solar cell layers are presented in Tables 1 and 2, respectively. For the passive cooling technique, a schematic diagram of the hybrid CPVePCM system considered in the current work is presented in Fig. 1C. As shown in the figure, the PCM was placed between two aluminum flat plates and then attached to the rear side of the CPV cell. The aluminum front/back walls, which were 3 mm thick, were included to achieve uniform temperature distribution over the front surface of the system. Moreover, they protected the PCM and provided a high rate of heat transfer during both melting and solidification. This was enhanced by a series of aluminum fins 3 mm thick extending into the PCM from the front wall. The interior dimensions of the container were 125 mm in height by 150 mm in depth. The main criterion for selecting a suitable PCM for a particular application was its phase transition temperature, which should be close to the PV standard operating temperature of 25 C. Other relevant parameters included high values of thermal conductivity and latent heat; the stability of the cycling heat process also must be taken into account to reach an appropriate decision [28]. In the current work, the selected PCM was salt hydrate CaCl2$6H2O. The thermophysical properties of both the PCMs and aluminum are shown in Table 3.

2. PHYSICAL MODEL

(A)

479

Net concentrated solar flux Glass Top EVA

δg δEVA

δsc

Silicon layer Lower EVA

δt δw

Channel wall

Inlet

Tedlar

Outlet

H Net concentrated solar flux

(B) δg δEVA

δsc

δt δw P

H

Outlet

Inlet Adiabatic

(C)

3 mm

PCM

H = 125 mm

Net concentrated solar flux

δ = 3 mm

δPCM = 150 mm Glass Top EVA

Silicon

Tedlar

Aluminum

FIGURE 1 Computational domain for (A) wide microchannel heat sinkeconcentrated photovoltaic (CPV) system, (B) manifold microchannel heat sinkeCPV system, and (C) phase change material (PCM)eCPV system. EVA, ethylene vinyl acetate.

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CHAPTER 2.15 COMPARATIVE STUDY OF COOLING TECHNIQUES

Table 1 PhotovoltaiceThermal Layer Physical Properties [24] Layer Glass (Cover) Antireflective coating Encapsulation (ethylene vinyl acetate) Silicon Tedlar Aluminum channel

Density (kg/m3)

Specific Heat (J/kg K)

Thermal Conductivity (W/m K)

Thickness (mm)

2 32

3 0.01

3000 2400

500 691

960

2090

0.311

0.5

2330 1200 2719

677 1250 871

130 0.15 202.4

0.2 0.3 0.2

Table 2 Optical Properties of Each Layer Material

Reflectivity

Absorptivity (a)

Transmissivity

Emissivity

Glass cover Ethylene vinyl acetate layer Silicon layer Back sheet

0.04 0.02

0.04 0.08

0.92 0.90

0.85

0.08 0.86

0.90 0.128

0.02 0.012

0.9

Table 3 Thermophysical Properties of Selected Phase Change Material (PCMs) and Aluminum Microchannel Walls and PCM Cavity [18] Thermophysical Properties

CaCl2e6H2O (PCM)

Aluminum

Melting point, ( C) Heat of fusion, (kJ/kg) Thermal conductivity Solid (W/m  C) Liquid (W/m  C) Density Solid (kg/m3) Liquid (kg/m3) Specific heat capacity Solid (kJ/kg K) Liquid (kJ/kg K) Thermal expansion coefficient (k1) Thermal cyclic stability Chemical classification

29.8 191

N/A N/A

1.08 0.56

211 N/A

1710 1560

2675 N/A

1.4 2.1 0.0005 Yes [51] Salt hydrate

0.903 N/A N/A e e

N/A, not applicable.

3. MATHEMATICAL MODEL

481

3. MATHEMATICAL MODEL A 2D solidefluid conjugate heat transfer model, including different layers of the PV cell, was developed to estimate the electrical and thermal performance of the CPV/T system. The overall CPV/T system involved multiple solid domains and fluid domains. In the currently developed solidefluid conjugate heat transfer model, the following assumptions were adopted: 1. Solar cell optical and physical properties were isotropic and temperature was independent. 2. Thermal contact resistances among each layer of the solar cell and heat sinks were negligible. 3. The flow in the MCHS was laminar, incompressible, and steady-state. However, in the PCM liquid phase it was assumed to be incompressible, Newtonian, and unsteady. 4. The water’s thermophysical properties were temperature dependent.

3.1 PHOTOVOLTAIC MODULE LAYERS The heat conduction equation in the Cartesian coordinates system for each solid layer can be represented as [29]:

 v vT v vT (1) k þ k þ qi ¼ 0 and i ¼ 1; 2; .6 vx vx vy vy where the variable ki represents the thermal conductivity of the layer i and the term qi characterizes the heat generation in the layer i owing to the absorption of solar radiation. In this work, the value of i changed from 1 to 6 for glass, upper EVA, ARC, silicon, lower EVA, and tedlar layers, respectively. The heat generation per unit volume of the layer caused by solar irradiance absorption of the CPV cell layers can be determined using the equation as reported in Zhou et al [30]: qi ¼

ð1  hsc ÞGai sj Ai Vi

(2)

where qi is the heat generation per unit volume in layer i; hsc is the solar cell electric efficiency, whose value changes to 0 when the internal heat generation of other layers is calculated; ai, Ai, and Vi are the absorptivity, area, and volume of layer i, respectively; and sj is the net transmissivity of layers above layer i. Solar energy absorbed by all layers was taken into consideration to simulate the actual situation. In addition, solar irradiance absorption of layers located in the interval between each cell and neighboring cells was taken into account. The silicon layer efficiency was calculated using the equation [1,31]: hsc ¼ href ð1  bref ðTsc  Tref ÞÞ

(3)

where href and bref are the solar cell efficiency and temperature coefficient at a reference temperature of Tref ¼ 25 C, respectively. These values are provided by the manufacturer data sheet for most solar cells. bref is taken to be 0.0045K1 for polycrystalline silicon [32].

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CHAPTER 2.15 COMPARATIVE STUDY OF COOLING TECHNIQUES

3.2 MICROCHANNEL HEAT SINK DOMAIN For a microchannel substrate, the heat conduction equation in a Cartesian coordinate system without heat generation can be written as:

  v vTch v vTch kch kch þ ¼0 (4) vx vy vx vy For MCHS, the continuity, momentum and energy equations of laminar, incompressible, and steady flow can be written in a Cartesian coordinates system as [33]: For the continuity equation: vðruÞ vðrvÞ þ ¼0 vx vy

(5)

For the momentum equations:



 vðruÞ vðruÞ vP v vu v vu þv ¼ þ m þ m vx vy vx vx vx vy vy

 vðrvÞ vðrvÞ vP v vv v vv þv ¼ þ m þ m u vx vy vy vx vx vy vy

u

(6) (7)

For the energy equation:



 vðrCuTÞ vðrCvTÞ v vT v vT þ ¼ Kl þ Kl vx vy vx vx vy vy

(8)

where u, v, p, m, r, Cf, kf, and Tf are the velocity components in the x and y directions, pressure, fluid viscosity, density, specific heat, thermal conductivity, and temperature, respectively. Because of substantial changes in water properties inside the microchannel, especially at higher CR values, the variation in water’s thermophysical properties with changes in temperature is considered using higherordered polynomial equations presented in Jayakumar et al. [34].

3.3 PHASE CHANGE MATERIAL HEAT SINK DOMAIN The enthalpy-porosity technique is used to model the PCM. In this technique, the liquidesolid interface is not explicitly tracked. Instead, the presence of the solid or liquid phase is monitored using a quantity known as a liquid fraction (l). The liquid phase of PCM is assumed to be incompressible, Newtonian, and unsteady. The liquid PCM density variation in the buoyancy term is modeled by the Boussinesq approximation to involve thermal buoyancy. Accordingly, the governing equations for the 2D transient analysis of PCM during melting, including buoyancy-driven convection, are written as [35,36]: For the continuity equation: vðruÞ vðrvÞ þ ¼0 vx vy

(9)

For the momentum equations:
2  vu vu vu vP v u v2 u r þ ru þ rv ¼  þ m þ þ Sx vt vx vy vx vx2 vy2

(10)

3. MATHEMATICAL MODEL


2  vv vv vv vP v v v2 v ! r þ ru þ rv ¼  þ m þ þ FB þ Sy vt vx vy vy vx2 vy2

483

(11)

where r is the density; u and v are the velocities of the liquid PCM in the x and y directions, respectively; P is the pressure; m is the dynamic viscosity; and FB is a buoyancy force given by the Boussinesq approximation as presented in Appendix A. The energy equation for melt is:
2  vH vH vH v T v2 T þ rl u þ rl v ¼ kl rl þ (12) vt vx vy vx2 vy2 The energy equation for solid is:
2  vH v T v2 T ¼ ks þ rs vt vx2 vy2

(13)

The enthalpy of the material, H, is computed as the sum of the sensible enthalpy, h, and the latent heat, as presented in Appendix A.

3.4 BOUNDARY CONDITIONS To solve the governing equations, the boundary conditions must be identified. First, for the PV layers, the thermal boundary condition for the upper wall of the glass layer is that it is subjected to convection and radiation heat loss. In this case, the convective heat transfer coefficient, ambient temperature, surface external emissivity, and external radiation temperature should be applied accurately, whereas the lower TPT surface is subjected to the same type of boundary condition with a different convection heat transfer coefficient that equals half the value applied at the top, as concluded by Zhou [30]. The side walls of the computational domain are assumed to be adiabatic owing to their symmetry. Second, for the CPV with MCHS, the lower wall of the computational domain is assumed to be adiabatic for the CPV/T system, to achieve the highest possible gain of thermal energy. The fluid inlet velocity component normal to the inlet section is identified and assumed to be uniform. In the meantime, the 0-gauge pressure is identified as boundary conditions at the MCHS outlet section. No-slip and no-temperature jump boundary conditions are considered at the interface between the solidefluid domains because the Knudsen number falls in the no-slip regime (Kn < 0.001) [37]. Furthermore, the maximum channel flow Re is estimated to be within the laminar flow regime (i.e., Rein < 2200) [38]. The channel inlet temperature is assumed to be uniform at 30 C. Third, for the CPV with PCM heat sink (initially t ¼ 0), the system contains a solid PCM maintained at a temperature (Tini) lower than the melting temperature (Tm) of the employed PCMs and equal to 25 C. Furthermore, no-slip boundary conditions are taken at the solidefluid interfaces. However, for all existing solidesolid interfaces, a thermally coupled boundary condition is applied. In addition, the adiabatic boundary condition is applied on the upper and lower ends of the CPVePCM system, as presented in Fig. 1C. For the front surface of the CPV cell, the thermal boundary condition is combined with convection and radiation loss. The exterior back boundary is subjected to a convective heat loss for the CPVePCM system, and convection and radiation loss for the CPV system without PCM. The convective heat transfer coefficient from the glass cover to the atmosphere, from the exterior back to the ambient, and from radiation from the top glass to the sky are presented in Appendix A.

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CHAPTER 2.15 COMPARATIVE STUDY OF COOLING TECHNIQUES

3.5 SOLUTION METHODS AND CONVERGENCE CRITERIA The developed comprehensive thermal model for PV layers, coupled with the heat sinks either using MCHS or PCM, was numerically simulated to determine the solar cell temperature and consequently the performance parameters. The solution steps commenced by estimating an initial value of electrical efficiency (href ¼ 0.2). Then the corresponding internal heat generation for the silicon layer was determined using Eq. (2) and the heat generation for other PV layers in the cell part and the interval part were also calculated. The model governing equations were solved and the new solar cell temperature was obtained. The iteration procedure was repeated until the error between the two consequent solar cell temperatures reached 103 and the maximum residuals in the solution of conjugate heat transfer equations was less than 106. Therefore, parallel computing was implemented using a Dell Precision T7500 workstation with a 3.75-GH Intel Xeon processor, 48 core, and 64-MB installed memory. The SIMPLE algorithm was used to solve pressureevelocity coupling equations. The second-order upwind scheme was used to solve momentum and energy equations. For the PCM domain, the PREssure STaggering Option scheme was adopted for the pressure correction equation. Furthermore, for every heat sink design, a grid independence test was conducted using several mesh sizes to ensure that results did not change with a further increase in the number of elements. In addition, the model was validated by comparison with available experimental and numerical data.

3.6 NUMERICAL RESULTS VALIDATION The current model was validated using different sets of available experimental and numerical results. The first set was used to validate the uncooled solar cell model with available experimental results [18] and numerical results presented in Zhou et al. [30]. In this part, the iterative technique for Eqs. (1)e(3) was applied for all layers of the solar cell. The second set of results was used to validate heat transfer characteristics in MCHSs for both WMCHS and MMCHS configurations with the available experiments [6] and numerical results using Lattice Boltzmann method (LBM) [28] for WMCHS and using the experimental results of Choue et al. [39] and the numerical results of Zhou et al. [40] for MMCHS at different values of Reynolds numbers. The final set of results were used to validate the PCM domain by comparing the average predicted and measured temperatures on the front surface of the system versus the time available in Huang et al. [23], and with the numerical computations of Huan et al. [41]. Finally, the PVePCM system was validated by comparison with the average predicted PV cell temperature versus time with the measured results of Hasan et al. [18].

3.6.1 Uncooled Concentrated Photovoltaic System Validation Firstly, the uncooled CPV model was validated by comparing the average predicted solar cell temperature versus time with the measurements of Hasan et al. [18] in Fig. 2A. Moreover, the predicted difference between the maximum solar cell temperature and the ambient temperature (DT) was compared with the numerically calculated difference in Zhou et al. [30] at various operating conditions, as presented in Fig. 2B. The solar radiation changed from 300 to 1000 W/m2 and the ambient temperature varied from 10 to 40 C with a wind speed of 1.0 m/s, as shown in Fig. 2. Excellent agreement was found between the current predicted results and those available in Hasan et al. [18] and Zhou et al. [30].

3. MATHEMATICAL MODEL

485

FIGURE 2 Uncooled photovoltaic (PV) model validation with (A) the experimental results of Hasan et al. [18], and (B) the numerical results [30]. EVA, ethylene vinyl acetate.

3.6.2 Microchannel Heat Sink Validation To validate the current results with the experimental results, Fig. 3 compares the predicted values (current study) and experimental values of the Nusselt number published in Kalteh et al. [6]. The same dimensions, boundary conditions, and fluid properties were applied for fair comparison. In their study, a wide microchannel with a length of 94.3 mm, width of 28.1 mm, and height of 0.580 mm was studied. The microchannel heat sink was heated from the bottom at constant heat flux (20.5 kW/m2), where the Re varied from 70 to 300. Comparison between measured and predicted values showed good agreement with a maximum relative error of about 4.4%. This value of error may be attributed to experimental data uncertainties and the absence of details about the measured values. To validate the predicted results further, the current CFD results were compared with the numerical results using the LBM [42] in Fig. 3A. To validate the fluid flow characteristics in WMCHS, the friction factor was validated with the analytical results of the fully developed laminar flow friction characteristics presented in Rohsenow and Hartnett [43] in the case of the wide microchannel. Excellent agreement was obtained between the predicted friction factor and the analytical results. Furthermore, the heat transfer characteristics in MMCHS were validated with the available numerical results of Manca et al. [40] in Fig. 3B. Excellent agreement was obtained. Consequently, the current CFD solution methodology was able to predict the heat transfer and friction characteristics of the investigated MCHS designs.

3.6.3 Phase Change Material Heat Sink Validation For the transient simulation of PCM model validation, the predicted results were validated with the available experimental data of Huang et al. [23] by comparing the average predicted and measured temperatures on the front surface of the system versus time, as shown in Fig. 4A. The incident solar

486

CHAPTER 2.15 COMPARATIVE STUDY OF COOLING TECHNIQUES

FIGURE 3 Comparison of predicted results with (A) measured results of [6] and numerical using Lattice Boltzmann method (LBM) [42]. (B) Numerical results of Manca et al. [40] and experimental results [39]. Nu, Nusselt number; Re, Reynolds number.

FIGURE 4 Comparison between predicted average temperature on front surface with (A) measured results of Huang et al. [23] and (B) numerical results of Huang et al. [41]. PCM, phase change material.

4. RESULTS AND DISCUSSION

487

irradiance and ambient temperature used were 750 W/m2 and 19 C, respectively. The top, bottom, and back surfaces were assumed to be adiabatic. Comparison indicated that good agreement was obtained between the current computational results and the experiments, with a maximum difference of about 2 C. Moreover, the computational results were compared with the available numerical results of Huang et al. [41], as shown in Fig. 4B for an ambient temperature of 20 C, and an incident solar irradiance of 1000 W/m2. Good agreement was shown between the predicted and the numerical results, with a maximum difference of about 4 C.

4. RESULTS AND DISCUSSION This section is divided into three subsections. The first one the performance of a CPV cell cooled with the investigated MCHS designs. The second subsection demonstrates the performance of the CPV system cooled with a PCM heat sink. Finally, the third subsection compares the active and passive cooling techniques. The comparison is based on the average solar cell temperature, temperature uniformity, electric efficiency, solar cell net gained electric power, and the CPV system’s thermal efficiency.

4.1 ACTIVE COOLING TECHNIQUE USING MICROCHANNEL HEAT SINK In the current section, the effect of jet pitch (P) in the MMCHS was investigated to determine the most efficient pitch value for the field of CPV systems. Then the appropriate pitch value was selected for comparison with the conventional WMCHS design at different operation parameters such as coolant flow rate and solar concentration ratio. The comparison was implemented by calculating the average solar cell temperature, temperature uniformity, and net gained electrical power.

4.1.1 Effect of Manifold Pitch Different values of the manifold pitch (P) are investigated. In case A, the distance between the two consecutive inlet ports was 1.25 mm and the computational domain length was 125 mm. Thus a total of 100 inlet ports for one solar cell was designed in this case. Similarly, in the case of B, and C, the pitch values were 2.5 and 5 mm, which gives 50 and 25 total inlet ports, respectively, for one cell. The same total mass flow rate was used for each case and the CR was selected to be 20 where the maximum temperature occurred. The comparison between the investigated pitches was implemented based on the average solar cell temperature, coolant outlet temperature, and consumed pumping power. The variations in the average solar cell temperature influenced by the cooling fluid mass flow rate at the investigated different pitch values is presented in Table 4. Generally, increasing the cooling mass flow rate led to a reduction in the solar cell temperature. This trend was observed by several researchers [44e46]. There are different hypotheses to interpret this trend. It is reported that at a lower Re, the heat transfer mechanism between the upper wall and the cooling fluid was dominated by convection, whereas at a higher Re, the heat transfer mechanism was dominated by conduction within the thin layer of the laminar wall region [46]. Another point of view relates this trend to the reduction of contact time between the fluid and the upper wall owing to the higher velocity associated with a higher flow rate [44]. The last interpretation is that at a high Re, the heat extracted by the cooling water reached the saturated level, and therefore the cell temperature slightly increased [45]. Furthermore, decreasing the

488

CHAPTER 2.15 COMPARATIVE STUDY OF COOLING TECHNIQUES

_ at Different Pitch Values Table 4 Variations in Average Solar Cell Temperature With m Pitch (mm)

m_ [ 50 g=min

m_ [ 100 g=min

m_ [ 200 g=min

m_ [ 400 g=min

m_ [ 800 g=min

m_ [ 1000 g=min

m_ [ 2020 g=min

(A) P ¼ 1.25 (B) P ¼ 2.5 (C) P ¼ 5

111.01 125.49 136.05

103.6 109.07 110.53

95.1 95.88 95.7

88.44 88.39 88.18

84.75 84.67 84.54

84.04 83.97 83.86

82.72 82.67 82.62

pitch reduced the solar cell temperature, especially at lower flow rates. This may be attributed to the reduction in the fluid pass under the heated CPV cell. Consequently, the flow might have been in the entrance region. The heat transfer in the entrance region was significantly higher than that in the fully developed regime. This might have caused a greater reduction in the solar cell temperature, as shown in the case of the lowest pitch (A). The solar cell temperature dropped from 136 to 111 C with a decrease in the pitch from 5 to 1.25 mm at the same lowest total cooling mass flow rate of 50 g/min and a solar concentration ratio of 20. In addition, a further increase in the mass flow rate beyond 800 g/min led to no significant effect of pitch value on the solar cell temperature. The reason for this lack of effect _ the heat transfer coefficient reached a sufficient value for it to be essential for was that at a higher m, heat removal from the back side of the solar cell regardless of the configuration. The maximum permissible solar cell temperature was 85 C; consequently, all investigated pitches attained the same maximum allowable temperature at the same coolant flow rate close to 800 g/min. Hence it is recommended that the higher pitch value be selected, because it is also the simplest and easiest to manufacture.

4.1.2 Average Solar Cell Temperature Comparison Conventional WMCHS was compared with MMCHS with P ¼ 5 mm. Fig. 5A and B shows the variations in the average solar cell temperature versus the cooling fluid mass flow rate for WMCHS and MMCH, respectively. Generally, increasing the cooling fluid mass flow rate led to an enhancement of the average solar cell temperature up to a certain limit. A further increase in the mass flow rate beyond this limit attained only a slight enhancement in the solar cell temperature. In addition, increasing the solar concentration ratio led to a significant increase in the solar cell temperature caused by a rise in the absorbed solar irradiance. In a comparison of Fig. 5A and B, it is apparent that MMCHS with P ¼ 5 mm achieved a higher average solar cell temperature, especially at lower mass flow rates; however, by increasing the mass flow rates, both configurations achieved a relatively equal solar cell temperature. The reason for this trend is that at a lower mass flow rate, the heat transfer coefficient for MMCHS was smaller than that of WMCHS. The heat transfer coefficient in the MMCHS was small enough to dissipate the required heat. However, at a higher mass flow rate, the heat transfer coefficient for both configurations exceeded the optimal necessary value to limit the cell temperature below the optimum operating temperature. Therefore, at CR ¼ 15 and 20, it is recommended to use the WMCH with m_ > 60 and m_ > 350 g=min, respectively, to limit the CPV system temperature without causing possible damage to its components. CPV systems can safely operate when they are combined with MMCHS, with m_ > 120 and m_ > 550 g=min at CR ¼ 15 and 20, respectively.

4. RESULTS AND DISCUSSION

489

FIGURE 5 Variations in average solar cell temperature with the cooling mass flow rate at various concentrations ratios (CR) for (A) wide microchannel heat sink (WMCHS) and (B) manifold microchannel heat sink (MMCHS) with P ¼ 5 mm.

4.1.3 Local Solar Cell Temperature Comparison Because the main purpose of this study was to provide a reliable and efficient cooling system, calculation of solar cell temperature uniformity is vitally important. However, the effect of temperature uniformity on CPV cells’ durability and efficiency was examined in few studies. These studies concluded that cell efficiency declined as a result of the cell’s nonuniform temperature distribution. It was found that cell temperature nonuniformity caused a reverse saturation current [47]. Moreover, thermal expansion depended on the local cell temperature. Consequently, CPV cells’ temperature nonuniformity implies mechanical stress and reduces the lifetime of the solar cell. A comparison of solar cell temperature uniformity is presented in Fig. 6AeC at mass flow rates of 50, 800, and 2020 g/min, respectively, and CRs of both 5 and 20. Generally, the local solar cell temperature increased with the axial distance for WMCHS, whereas for the MMCHS, the local solar cell temperature was nearly constant along the solar cell length. For instance, at m_ ¼ 50 g=min, the difference between the maximum local solar cell temperature and the lower local solar cell temperature for the WMCHS was about 11.3 and 46.8 C at CR ¼ 5 and 20, respectively. However, in the case of MMCHS, the maximum local solar cell temperature difference was about 1.1 C and 4.02 C at CR ¼ 5 and 20, respectively, at the same total coolant flow rate of 50 g/min. In Table 5, the difference between the maximum and minimum local silicon layer temperature (DT ¼ Tsc,max  Tsc,min) is presented at CR ¼ 5 and CR ¼ 20 and various values of m. Generally, increasing m decreased the temperature degradation in the silicon layer, and it was much smaller in the MMCHS compared with the conventional WMCHS. For example, at CR ¼ 20, where the temperature uniformity was crucial, the MMCHS attained a temperature uniformity of 4.02, 0.365, and 0.125 C at m_ of 50, 800, and 2020 g/min, respectively. However, the WMCHS achieved a maximum temperature difference of 46.8, 3.13, and 1.44 C at these total coolant mass flow rates.

490

CHAPTER 2.15 COMPARATIVE STUDY OF COOLING TECHNIQUES

FIGURE 6 Variations in local solar cell temperature with axial distance at cooling fluid mass flow rate of (A) 50 g/min (B) 800 g/min, and (C) 2020 g/min. CR, concentration ratio; MMCHS, manifold microchannel heat sink; WMCHS, wide microchannel heat sink.

4.1.4 Net Gained Electrical Power Comparison Use of an MCHS will significantly increase friction power loss owing to its small size. It is clear that for both configurations that were investigated, the friction power increased with the flow rates whereas the solar cell power increased until it reached a nearly constant value. A further increase in the cooling

4. RESULTS AND DISCUSSION

491

Table 5 Variations in Silicon Layer Temperature Uniformity (DT [ Tsc,min L Tsc,min) at _ for Investigated Configurations CR [ 5 and 20 and Various m CR [ 5

m_ ¼ 50 g=min m_ ¼ 800 g=min m_ ¼ 2020 g=min

CR [ 20

WMCHS

MMCHS

WMCHS

MMCHS

11.3 0.76 0.35

1.1 0.1 0.03

46.8 3.13 1.44

4.02 0.365 0.125

CR, concentration ratio; MMHCS, manifold microchannel heat sink; WMHCS, wide microchannel heat sink.

fluid mass flow rate led to a significant rise in the friction power while maintaining the solar cell power as a constant value. Therefore, the net power, which is defined as the difference between the solar cell electric power and the friction power, will first increase and then decrease again. The same trend was observed in Xu and Kleinstreuer [46] and was explained in detail in earlier studies [13,14]. In comparing the friction characteristics of both configurations, it is interesting that the MMCHS _ This was because consumed a lower friction power compared with the WMCHS at the same CR and m. of the distribution of coolant mass rate over large jets, which decreased the velocity in each channel below the cell; because the friction factor was proportional to the squared fluid velocity, the friction factor decreased dramatically in the MMCHS. The pumping power can be neglected compared with the WMCHS at the same m, as presented in Table 6. Moreover, it can be concluded that increasing CR caused a slight variation in the friction power that was affected by the variation in the cooling fluid thermophysical properties with CR. A comparison of the net gained electric power (Pnet ¼ Pel  Pf) for the CPV systems integrated with the MMCHS and WMCHS is presented in Fig. 7A and B for CR ¼ 5 and 20, respectively. For MMCHS, the net gained power increased with an increase in the cooling fluid mass flow rate and then remained unchanged with the coolant flow rate. This was attributed to the lower pumping power consumed with this configuration along with an increase in the coolant flow rate. However, in the case of WMCHS, the net CPV cells’ output power (Pnet) increased until it reached a maximum value, and _ at CR [ 5 and 20 for Investigated Table 6 Variations in Friction Power With m Configurations Wide Manifold Microchannel Heat Sink

Manifold Microchannel Heat Sink

_ (g/min) m

CR [ 5

CR [ 20

CR [ 5

CR [ 20

50 800 2020

0.0063 1.8443 11.6427

0.0046 1.7885 11.483

2.6E-06 8.6E-04 5.5E-03

1.7E-06 8.2E-04 5.4E-03

CR, concentration ratio.

492

CHAPTER 2.15 COMPARATIVE STUDY OF COOLING TECHNIQUES

FIGURE 7 Variation of the solar cell electric power versus the cooling fluid mass flow rate for MMCHS and WMCHS at (A) CR ¼ 5 and (B) CR ¼ 20.

then it significantly decreased again. This was caused by an increase in the coolant flow rate, which caused a significant increase in the gained solar cell electrical power up to a certain limit. The friction power in WMCHS dramatically increased with an increase in the flow rate. Consequently, the net gained electric power increased up to a certain limit and then significantly decreased again. This trend was in good agreement with the experimental results of Baloch et al. [44] and the numerical results of Xu and Kleinstreuer [46]. By comparing both investigated MCHS configurations, it was found that the solar cell net power integrated with the MMCHS was greater than that for WMCHS, especially at a higher mass flow rate, as shown in Fig. 7. This was because both investigated configurations attained the same cell temperature at higher m, whereas the MMCHS consumed a lower friction power at higher m. Furthermore, the coolant flow rate of 800 g/min was appropriate to achieve the safe operation of the silicon layer below 85 C; hence the MMCHS with P ¼ 5 mm was more appropriate because it achieved a temperature requirement with a higher net power. In more detail, at CR ¼ 20 and m_ ¼ 800 g=min, the net gained electric power for the investigated cell area of 12.5  12.5 cm2 was 39.6 and 41.1 W using WMCHS and MMCHS, respectively.

4.2 PASSIVE COOLING TECHNIQUE USING PHASE CHANGE MATERIAL In the current section, two major sets of numerical simulation tests were carried out. The first set of numerical simulations was performed to study the thermal behavior of the CPVePCM system without fins using salt hydrate CaCl2$6H2O (PCM). The second set of numerical simulations was carried out to examine the effects of the insertion of a different number of aluminum fins on the thermal regulation of the CPVePCM system.

4. RESULTS AND DISCUSSION

493

4.2.1 Thermal Performance of the Concentrated PhotovoltaicePhase Change Material System Without Fins Thermal regulation of the CPVePCM system depends on the thermal behavior of the PCM during melting. The transient variations in the average solar cell temperature of the nonfinned CPVePCM system with 15-mm thick PCM and CR ¼ 5 are presented in Fig. 8. The same figure presents the temperature variations with elapsed time along the height at the center of the nonfinned CPVePCM system (location points A, B, and C) (Fig. 8) as well as the time evolution of the liquidesolid interface of the PCM during the melting process. Based on the figure, using PCM salt hydrate CaCl2$6H2O with a melting point of 29.8 C, the CPVePCM without fins could maintain the solar cell at an average temperature of 70 C for 390 min whereas the temperature at the complete melting point of PCM was around 88 C. Based on the figure, generally three stages of temperature variation for solar cells are associated with the phase change process of the cooling material. First, a steep increase in the average solar cell temperature is observed, followed by a gradual increase with time. This variation most likely results from sensible heating of the PCM by conduction heat transfer through the aluminum front plate. Subsequently, phase transition of the PCM adjacent to the aluminum front plate causes a thin melting layer on the PCM. During this period, the PCM acts as an insulation material for the CPV cell, whereas heat transfer is dominated by conduction, raising the CPV temperature. Second, as time passes there is a decrease in the average cell temperature after which it remains almost constant for a period. This stage indicates the start of the convective heat transfer that balances conductive heat transfer. During

FIGURE 8 Average predicted solar cell temperature and temperature variations with time in center vertical line of concentrated photovoltaicephase change material (CPV-PCM) system with the time evolution of solideliquid interface of CPV-PCM system at ambient temperature of 30 C and 1 m/s wind velocity. CR, concentration ratio.

494

CHAPTER 2.15 COMPARATIVE STUDY OF COOLING TECHNIQUES

this period, the natural convection current becomes more significant in the liquid PCM as the melting fraction increases [48,49]. Finally, as time passes, the cell temperature gradually begins to increase until the PCM reaches the complete melting point. This variation is observed when the hot molten liquid touches the aluminum rear plate. Furthermore, the solid PCM, which acts as the cold source that drives the natural convection currents, starts to disappear from the upper part of the system. During this period, natural convection currents are weakened in this region. In addition, the temperature of the liquid PCM at the upper part of the system increases, which results in less heat transfer from the hot wall to the liquid PCM. With the lapse of time, the region of weak convection currents extends from up to down while raising the cell temperature gradually until it reaches a fully liquid phase. In addition, along the height at the center of the CPVePCM system at points A, B, and C, heat transfer is initially dominated by conduction, with an increase in linear temperature over time. After 100 min, the melting interface reaches point A, where heat transfer is dominated by convection. This causes the temperature to increase sharply toward the solar cell temperature whereas the temperatures in the solid phase locations (B and C) maintain a slow conduction-dominated increase. This behavior is observed at points B and C after 200 and 300 min, respectively.

4.2.2 Thermal Performance Comparison for Concentrated PhotovoltaicePhase Change Material Systems With a Different Number of Fins In the current work, a detailed analysis is presented of the effect of inserting various numbers of aluminum fins on the thermal regulation of the CPV-PCM system. Fig. 9AeC presents the transient variations of the average solar cell temperature of the CPV-PCM system with different numbers of fins (each fin is 100 mm in length) and no fins, at CRs of 5, 10, and 20, respectively. At CR ¼ 5, increasing the number of fins led to a significant reduction in the average solar cell temperature, where it was reduced from 70 C to 52 C as the number of fins increased from zero to four. This can be explained by the fact that metal fins increased heat transfer inside the PCM by increasing the surface area over which the heat transfer to or from the PCM occurred. By increasing the CR to 10 and 20, a similar trend was observed in Fig. 9B and C, as when the number of fins increased from zero to four fins. At CR ¼ 10, the average solar cell temperature was reduced from 106 C to 76.5 C, whereas at CR ¼ 20 min, the average solar cell temperature was reduced from 155 C to 115 C. Moreover increasing the value of CR led to a significant increase in the melting rate. This was because as the value of CR increased, the amount of solar irradiance received by the CPVePCM system also increased. Hence, the amount of the front wall heat flux transferred to the PCM increased, which indicated a higher melting rate. Predicted temperature distributions during the PCM melt process within the CPV-PCM system with four fins at CR ¼ 5 are presented in Fig. 10. As seen in the figure, when aluminum fins were added to the system, the formation of a deep cavity in the upper part of the CPV-PCM system was reduced and divided into several smaller, shallower cavities between the fins, which reduced the thermal stratification within the system. After 170 min, a natural convection flow of hot molten PCM passed through the gap at the end of the fins into the upper part of the system; it then turned to flow downward through the gap, near the liquidesolid interface into the lower section. After 235 min, the molten PCM reached the aluminum rear plate and its temperature rose, causing an increase in the heat transfer rate from the side to the PCM adjacent to it. Then the melting velocity increased and the CPVePCM temperature began to rise quickly. This flow pattern was maintained until the PCM was fully molten. Once the PCM in the uppermost section was fully molten (after 260 min), the temperature of the CPVePCM system increased rapidly.

4. RESULTS AND DISCUSSION

495

FIGURE 9 Average predicted solar cell temperature of concentrated photovoltaicephase change material concentrated photovoltaicephase change material system with different number of fins and no fins at (A) concentration ratio (CR) ¼ 5, (B) CR ¼ 10, and (C) 20, an ambient temperature of 30 C and 1 m/s wind velocity.

To demonstrate the effect of using fins on the temperature uniformity of the CPVePCM system, Fig. 11 presents the local solar cell temperature for the CPVePCM with a different number of fins at 00 min. This figure shows that the temperature difference between the top and base of the solar cell (125 mm in height) for the nonfinned CPVePCM system equals 13.5 C. The use of aluminum fins provided improved thermal control whereas the temperature difference was reduced to 7 C for the CPVePCM system with two fins. Increasing the number of fins to four was able to decrease the temperature difference to 4.5 C and reduce the solar cell temperature.

496

CHAPTER 2.15 COMPARATIVE STUDY OF COOLING TECHNIQUES

t = 80 min

t = 120 min

t = 170 min

t = 235 min

t = 260 min

t = 300 min

FIGURE 10 Predicted isotherms of concentrated photovoltaicephase change material system with four fins at concentration ratio ¼ 5 at different times.

4.3 COMPARISON BETWEEN THE PROPOSED ACTIVE AND PASSIVE COOLING TECHNIQUES The current section compares the investigated MCHS designs and the proposed PCM configurations implemented based on the predicted average solar cell temperature, solar cell efficiency, net power, and thermal efficiency. Because the PCM model is an unsteady model, the average solar cell

4. RESULTS AND DISCUSSION

497

FIGURE 11 Variations in local solar cell temperatures of concentrated photovoltaicephase change material system without fins and with two and four fins after 100 min at concentration ratio (CR) ¼ 10.

temperature changes with time instantaneously. In the current section, the average solar cell temperature and stored thermal energy over the period from the initial time (ti) to the complete melting time (tm) was calculated to be straightforwardly compared with the steady-state solution of the MCHS domain. The average solar cell temperature, stored thermal energy, and thermal efficiency of the CPePCM system are calculated based on the equations: T sc;avgPCM Qth;avgPCM

1 ¼ tm  ti 1 ¼ tm  ti

hth;PCM ¼

Z Z

t¼tm

Tsc ðtÞdt

(14)

Qth ðtÞdt

(15)

t¼ti t¼tm

t¼ti

Qth;avgPCM  mPCM G  Asc  ðtm  ti Þ

(16)

Fig. 12A and B present the most essential parameters that affected the selection of the appropriate CPV cooling technique at CR ¼ 5 and 20, respectively. The heat sink designs that were compared were the WMCHS and MMCHS, with P ¼ 5 mm as an example for the active cooling technique, and the conventional cavity of PCM without fins and with four fins as examples for the passive cooling technique. In Fig. 12A, at CR ¼ 5, the MCHS designs operated at m_ ¼ 100 g=min, which was capable of achieving a lower cell temperature; a further increase in the m increased the friction

498

CHAPTER 2.15 COMPARATIVE STUDY OF COOLING TECHNIQUES

FIGURE 12 Variations in average solar cell temperature, solar cell electrical efficiency, net gained electrical power, and concentrated photovoltaicethermal system thermal efficiency with different active and passive cooling techniques at (A) concentration ratio (CR) ¼ 5 and (B) CR ¼ 20. MMCHS, manifold microchannel heat sink; WMCHS, wide microchannel heat sink.

power whereas the cell temperature remained unchanged, as discussed earlier. However, in the CPVePCM system, the parameters were calculated from the initial time only to the complete melting time. The CPVeWMCHS system attained the lowest average cell temperature, followed by the CPVeMMCHS system. Moreover, including the fins significantly reduced the cell temperature from an average value of 72 C for no fins to around 58 C for the case of four fins. Although the MCHS consumed a portion of the CPV electrical power, the electrical efficiency and net gained power of the systems using the PCM were smaller than those using the MCHS. These were returned to power enhancement owing to efficient cooling using the MCHS, which was much greater than that consumed to overcome friction. However, regarding thermal efficiency, the CPVeMMCHS system attained the highest thermal efficiency compared with the other configurations. This high thermal

5. CONCLUSION

499

efficiency was attributed to the coolant passing through a shorter distance under the cell and to its being divided into several jets that absorbed heat from the cell at relatively the same value over the cell length. However, in the CPVeWMCHS system, the solar cell temperature at the end of the MCHS was high; consequently, the cell lost a large amount of heat to the atmosphere via combined radiation and convection. In CPVePCM systems, thermal efficiency using four fins was much greater than without the use of fins. The same trend observed at CR ¼ 5 in Fig. 12A was detected as shown in Fig. 12B at CR ¼ 20, except that in the active technique using MCHS, both WMCHS and MMCHS attained relatively equal values for the solar cell temperature and thermal efficiency. This occurred at m_ ¼ 800 g=min, when both configurations attained the same cell temperature. However, the net gained electric power of the CPVeMMCHS was much higher compared with all proposed designs because it has the lowest consumed friction power of the cooling configurations with lower attained cell temperatures.

5. CONCLUSION Active and passive cooling techniques were compared for CPV systems. The active technique using an MCHS was compared using PCM as a passive cooling technique across different designs. A comprehensive 2D model was developed to investigate the effect of various designs and operation conditions on CPVeT system performance parameters. The comparison was implemented based on the average solar cell temperature, solar cell electric efficiency, system net power, and system thermal efficiency. Based on the results, there were several findings: •

•

•

• •

•

In an active cooling technique with MMCHS, the solar cell temperature is reduced from 136 to 111 C with a decrease in pitch from 5 to 1.25 mm at a cooling mass flow rate of 50 g/min and CR of 20. Use of a WMCHS with a minimum coolant mass flow rate of 60 and 350 g/min at CR ¼ 15 and 20, respectively, is recommended. In addition, CPV systems can safely operate when they are combined with MMCHS at a minimum coolant flow rate of 120 and 550 g/min at CR ¼ 15 and 20, respectively. At CR ¼ 20, using an MMCHS attains a solar cell temperature uniformity of 4.02, 0.365, and 0.125 C at coolant mass flow rates of 50, 800, and 2020 g/min, respectively. However, the WMCHS achieves a maximum temperature difference of 46.8, 3.13, and 1.44 C at coolant mass flow rates of 50, 800, and 2020 g/min, respectively. In the passive cooling technique, at CR ¼ 5, including fins significantly reduces the cell temperature from an average value of 72 C without fins to around 58 C with the use of four fins. At CR ¼ 10, the cell temperature uniformity of a nonfinned CPVePCM system equals 13.5 C. The use of aluminum fins enhances thermal control when the temperature difference is reduced to 7 and 4.5 C for a CPVePCM system with two and four fins, respectively. The CPVeWMCHS system attains the lowest average cell temperature, followed by the CPVeMMCHS. Moreover, including fins significantly reduces the cell temperature from an average value of 72 C without fins to around 58 C with the use of four fins. The MCHS consumes a portion of the CPV electrical power, whereas electrical efficiency and the net gained power of the systems using the PCM are smaller than those with the use of the MCHS.

500

CHAPTER 2.15 COMPARATIVE STUDY OF COOLING TECHNIQUES

NOMENCLATURE Amush C g G(t) h H k L m_ N P t T V Vw

Mush zone constant (Kg/m3 s) Specific heat capacity (J/kg$K) Gravitational acceleration (m/s2) Incident solar radiation (W/m2) Heat transfer coefficient (W/m2$K) microchannel height (m), and total specific enthalpy (J/kg) Thermal conductivity (W/m$K) Microchannel length, solar cell length (m), and latent heat (N m) Unit cooling fluid mass flow rate (Kg/s) Number of inlet or outlet ports Pressure (Pa), electrical power (W) Phase change material thickness (m), time (s) Temperature ( C) Velocity vector (m/s) Wind velocity (m/s)

Greek symbols a b bl ε s m s r d l n h

Absorptivity Backing factor and solar cell temperature coefficient (K1) Thermal expansion coefficient (K1) Emissivity Transmittivity Fluid viscosity (Pa s) StephaneBoltzmann constant 5.67  108 (W/m2$K4) Fluid density (kg/m3) Thickness (m) Liquid fraction Kinematic viscosity (m2 s) Solar cell and thermal efficiency

Subscripts

a conv. eff el f g in i m out ref s Sc Sc, x

Ambient Convection Effective Electrical Fluid Glass Inlet Initial Melting Outlet Reference condition, G ¼ 1000 W/m2, T ¼ 25 C Sky and solid Solar cell Local solar cell

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T th w w

501

Tedlar Thermal Wall Water

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CHAPTER 2.15 COMPARATIVE STUDY OF COOLING TECHNIQUES

APPENDIX A AUXILIARY EQUATIONS USED IN THE CURRENT MODEL The CPV/T system thermal efficiency is identified as: hth ¼

Pth GðtÞ$Asc

whereas the friction power, solar cell electrical power, and net gained electrical power are described as: _ in Pfrict ¼ DP$m=r Pel ¼ hsc sg bsc GðtÞwsc $lsc Pnet ¼ Pel  Pfrict The channel Re and hydraulic diameter are calculated based on the following correlations: Re ¼ Dh ¼

rin Vin Dh min

2ðHch  Wch Þ ðHch þ Wch Þ

The equivalent radiative heat transfer coefficient from the glass cover to the sky and the sky temperature are calculated using the following equations as reported by Rejeb et al. [50]:   sεg Tg4  Ts4 hrad;gs ¼ ðTg  Ts Þ Ts ¼ 0:0522Ta1:5 whereas the convective heat transfer coefficient from the glass cover to the ambient temperature and from the back sheet of the heat sink to the atmosphere are calculated based on the following correlations [30]: hcon;ga ¼ 5:82 þ 4:07Vw hconv;alamb ¼ 2:8 þ 3Vw The buoyancy force used in the PCM model is given by the Boussinesq approximation as: ! F B ¼ ro b1 ! g ðT  To Þ Parameters Sx, and Sy are Darcy’s law damping terms (as the source term), which are added to the momentum equation owing to the phase change effect on convection; they are defined as: ð1  lÞ2 $Amush $u Sx ¼  3 l þg

APPENDIX A

505

ð1  lÞ2 $Amush $v Sy ¼  3 l þg The enthalpy of the PCM material, H, is computed as the sum of the sensible enthalpy, h, and the latent heat, DH: H ¼ h þ DH where: Z h ¼ href þ

T

cp dT Tref

The latent heat content can be written in terms of the latent heat of the material, L: DH ¼ lL where DH may vary from 0 (solid) to L (liquid). Therefore, the liquid fraction, l, can be defined as: 8 DH > > > ¼0 T < Tm > > L > > > < DH T  Tsolidus ¼ Tm < T < Tm þ DTm l¼ L T  Tsolidus > liquidus > > > > > DH > > ¼1 T > Tm þ DTm : L The parameter Tm is the melting temperature of the PCM and DTm is the phase transition range, which is defined as the difference between the liquidus and solidus temperatures as: DTm ¼ Tliquidus  Tsolidus The PCM thermal conductivity, depending on its phase, is defined as: 8 > ks T < Tm > > > < ðks þ kl Þ kpcm ¼ Tm < T < Tm þ DTm > 2 > > > : kl T > Tm þ DTm

CHAPTER

OPTIMIZATION OF SLOPE ANGLES OF PHOTOVOLTAIC ARRAYS FOR DIFFERENT SEASONS

2.16 Ahmet Senpinar Firat University, Elazig, Turkey

1. INTRODUCTION Sun, wind, geothermal, biomass, and wave energy are some of the available alternative or renewable energy sources. These sources have a much lower negative effect on the environment than conventional energy sources [1]. Among these, solar energy is particularly vital for human health and the environment as it is abundant, renewable, and clean. Energy obtained from the sun on earth per unit time is known as the solar constant and is represented by GSC. The value of the solar constant as accepted by the World Radiation Center is 1367 W/m2 (1.96 cal/cm2 min) [2]. The sun is a gaseous body, with a mass of approximately 2
1030 kg and a diameter of 1.39
109 m. The distance from the sun to earth is approximately 1.49
1011 m [3]. Solar radiation has many advantages as a renewable energy source, particularly in terms of its abundance and freedom from pollution. It is utilized for generating both thermal energy and electricity directly using photovoltaic (PV) cells. Thus, solar insolation data are a significant parameter for the design and calibration of solar energy applications [4e6]. For example, calculations of solar insolation on horizontal surfaces are widely used for simulations, modelling, and sizing of solar processes. Data on solar radiation, which are measured hourly and daily, have significant importance for PV system designs, meteorology, solar maps, and engineering applications. Some researchers also use sky clearness to measure surface global solar irradiance [7,8]. PV systems are implemented in multiple ways, and the application of this technology is expanding throughout the world [9,10]. Current applications range from simple domestic PV energy systems to those for illumination, cooling, pumping water, plants for PV electricity generation, hybrid systems, space and telecommunication systems, etc. [11,12]. Evidently, the use of solar electricity has a significant place among energy resources in supplying future energy requirements. During the past few years, photovoltaic solar systems have become one of the most popular renewable energy sources in Europe [13,14]. Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00028-7 Copyright © 2018 Elsevier Inc. All rights reserved.

507

508

CHAPTER 2.16 OPTIMIZATION OF SLOPE ANGLES

Standalone PV systems are typically used in rural and remote areas to provide necessary electricity. Building-integrated photovoltaics can be an appropriate alternative source to receive solar energy [15]. Determination of the optimal slope angle and orientation for a fixed PV array is important for maximizing its energy. Several studies have been conducted by various researchers to determine the optimal location for solar radiation collection using different empirical models [16e20]. The calculation of the optimal slope angle for a PV array at any location and time of the year is necessary before its installation [21]. A key aspect in the efficiency of a solar array is its slope angle relative to the horizontal. The slope angle varies with season and location. In general, PV systems in the northern hemisphere are mounted facing due south at a certain angle. Variations of values for the slope angle have been proposed. Many studies have used angles calculated by Ø þ 20 degrees [22], Ø þ (10 / 30) degrees [23], Ø þ 10 degrees [24], and Ø  10 degrees [25], whereas other researchers suggest two values for the slope angle, such as Ø  20 degrees [26], Ø  8 degrees [27], or Ø  5 degrees [28], where Ø is the latitude angle of the region, with “þ” for winter and “” for summer. For optimal performance on any given day, a fixed array should be mounted on the ground with a horizontal angle of (Ø  d) degrees [29], where d is the declination angle known as the angle between the direction of the sun and the equator plane. This study recognizes the importance of seasonally adjusted slope angles to the optimal application of PV arrays in different locations across Turkey. The optimal slope angle of a fixed PV array is obtained for different periods and latitudes in the northern hemisphere. The optimal slope angle must be well determined to ensure system efficiency. If the slope angle of a PV system is chosen appropriately, the output power of the PV system increases. The optimal slope angle changes according to the time and location. The slope angles of some cities are presented, and calculations are performed to identify the optimal slope angle and orientation for PV arrays. Daily, monthly, and seasonal average slope angles can be calculated using the MATLAB software program. Graphical results associated with each city are presented.

2. MATHEMATICAL MODEL 2.1 PV ARRAY

Solar energy is utilized in two ways as thermal and electrical energy. One means of collecting solar energy as electricity is to use PV cells to generate electrical energy with solar radiation. The current generated by the PV cell is proportional to the effect of solar radiation on the cell. The power obtained from a PV cell is low because the current and voltage obtained from a single PV cell are also low. Therefore, to obtain adequate output power, PV cells are connected in series to form PV modules. In many applications, the power from one module is inadequate for the load. If higher voltages or currents than those available from a single module are required, modules must be connected into arrays [1]. When the modules are connected in parallel, their currents increase. When they are connected in series, their voltages increase. The current and voltage vary depending on the amount of sunlight shining on the PV cell. The IeV equation is then   I ¼ Il  I0 eðqVÞ=ðkTÞ  1 (1) where Il is the component of the PV cell current due to photons.

2. MATHEMATICAL MODEL

509

2.2 THE LATITUDE AND LONGITUDE OF ANY POINT ON EARTH The sun shines at different angles at different times in different places on earth. To determine a point on earth, certain information is needed. This information is gathered by a process of dividing the earth into a grid of latitudes and longitudes. The 0 degree meridian longitude passes through the former site of the Royal Astronomical Observatory in Greenwich, England, and is called the prime meridian. Points east of the prime meridian have negative longitudes, and points west of it have positive ones. The angle Ø on the earth’s surface measured north or south of the equator to a point is its latitude. Latitude values increase toward the poles, with the north pole being þ90 degrees and the south pole 90 degrees. Observers at different latitudes will see the sun take different paths across the celestial sphere. Fig. 1 shows the sun paths for the year as seen on the equator. Fig. 2 shows the paths seen at the north pole. This is useful to determine the position of the sun in the sky at any time of the year and at any latitude. The solar PV systems consist of two groups: fixed and tracking systems. Fixed systems are systems in which the array of solar cells is placed with a specific fixed slope. The slope angle changes according to the season and region. In general, PV systems in the northern hemisphere are mounted facing due south at a certain angle [2]. Tracking arrays follow the sun to maximize the incident beam radiation on their surfaces. Tracking control is based on angles of incidence and surface azimuth angles. Solar tracking systems are more expensive and complex than fixed systems. In this chapter, a PV system will be analyzed. Here, an effort will be made to note the areas where a PV system is open to the discretion of the designer. The system’s reliability, performance, and

FIGURE 1 Visualization of the sun paths across the sky for different latitudes on equator [3].

510

CHAPTER 2.16 OPTIMIZATION OF SLOPE ANGLES

FIGURE 2 The sun paths for different latitudes at the north pole [3].

advantage are among the most common concerns. The system is related to optimal slope angles of PV arrays in different seasons. This system is advantageous, economical, and sustainable.

2.3 CALCULATION OF SOLAR ANGLES PV arrays can be mounted to track the sun, but fixed systems must be maintained at a certain angle to the horizontal to fully exploit available sunlight at the location. If this slope angle is determined well, the amount of insolation and the generated energy increase. To maximize energy, solar panels, such as photovoltaic modules, are usually oriented toward the equator with an optimal slope angle from the horizon, which depends on climatic conditions and site latitude [16e18,30]. Slope angle and location are also important considerations because energy demand dictates the design and operation of a standalone PV cell system and the number of modules and batteries to be used. Thus, the performance of a system is subject to load, insolation level, and module characteristics. Slope angle can be determined using the meridians of longitude and latitude for any location. As latitude increases, the curvature of the earth has the effect of orienting the observer away from the sun. An array is sloped toward the equator to compensate for this effect. The earth revolves around the sun once a year in an elliptical orbit that is almost circular, with the earth to sun distance varying by approximately 3% from a mean distance of 150 million km. The earth is closest to the sun in the summer season and farthest away in the winter season because the rotational axis of the earth is inclined at 23.44 degrees to the axis of the orbital plane [2]. Thus, in winter, the earth is sloped with the northern hemisphere away from the sun, and in summer, the northern hemisphere is sloped toward the sun. This phenomenon is referred to as the slope or declination angle d of the axis relative to the suneearth line. Some angles are shown in Fig. 3A and B.

2. MATHEMATICAL MODEL

511

FIGURE 3 Some angles for a sloped surface (A and B).

Because these angles constantly change with the seasons relative to the position of a location, it is necessary to compute the optimal slope angle 12 times a year to provide monthly optimal slope angles that can also be used to calculate seasonal angles if necessary. Some of the angles to consider when calculating an optimum are as follows [1,2]: Latitude angle (Ø): Latitude is defined with respect to an equatorial reference plane, and it changes north positive, 90 degrees  Ø  90 degrees. Values north of the equator are positive and those south are negative. Equinox: This is the time when the lengths of day and night are equal. March 20 is known as the vernal equinox and September 23 as the autumnal equinox. On these dates, the sun’s rays are parallel to the equator. Declination angle (d): The declination angle is the angular position of the sun at solar noon with respect to the plane of the equator, north positive: 23.45 degrees  d  23.45 degrees. The variation of the declination angle through the year is shown in Fig. 4. The declination d can be found from the equation of Cooper:    ð360$ð284 þ nÞÞ d ¼ 23:45 sin degrees (2) 365 where n represents the day of the year (n ¼ 1, for 1 January) [2]. The day of the year n can be obtained with the help of Table 1. Fig. 3A and B shows the zenith, slope, solar azimuth angle, surface azimuth angle, and solar altitude angle for a sloped surface. The declination angle is zero during equinox dates (March 20 and September 23) because the incidence angle is parallel to the equator. In addition, the value of the declination angle is 23.45 degrees on summer solstice and 23.45 degrees on winter solstice. Zenith angle (qz): The zenith angle (qz) is the angle between the vertical and the line to the sun and is calculated as follows [2]: cosqz ¼ cosd
cos

cosu þ sind
sin


(3)

512

CHAPTER 2.16 OPTIMIZATION OF SLOPE ANGLES

FIGURE 4 Changes in the declination angle as annual.

Table 1 Suggested Average Days for Months and Values of n by Months [2] Months

n for ith Day of Month

Date

n, Day of Year

d, Declination

January February March April May June July August September October November December

i 31 þ i 59 þ i 90 þ i 120 þ i 151 þ i 181 þ i 212 þ i 243 þ i 273 þ i 304 þ i 334 þ i

10 11 10 10 11 10 11 10 10 11 10 11

10 42 69 100 131 161 192 222 253 284 314 345

22.03 14.58 4.80 7.53 17.78 23.01 22.10 15.36 4.21 8.10 17.91 23.12

where u is the solar hour angle and is determined for 24 h time by the (Senpinar) formula as follows [1]: u ¼ ððhour
60 þ minuteÞ  720Þ=4 degrees

(4)

2. MATHEMATICAL MODEL

513

FIGURE 5 Changes in the solar hour angle as 24 h time.

The solar hour angle at noon is zero. Fig. 5 shows the variation of the solar hour angle for 24 h. Solar altitude angle (as): The solar altitude angle is the angle between the horizontal and the line to the sun; it is complementary to the zenith angle and calculated as follows: as þ qz ¼ 90 degrees and as ¼ ð90  qz Þ degrees

(5)

Incidence angle (q): The incidence angle (q) is the angle between the beam radiation on a surface and the normal angle to that surface and is calculated as follows [2]: cos q ¼ cos qz
cos b þ sin qz
sin b
cosðgs  gÞ

(6)

where g represents the surface azimuth angle. Solar azimuth angle (gs): The solar azimuth angle (gs) is the angular displacement from south of the projection of beam radiation on the horizontal plane. Displacements east of south are negative and west of south are positive; the solar azimuth angle changes in the range of 180 to 180 degrees. For north or south latitudes between 23.45 and 66.45 degrees, gs will be between þ90 and 90 degrees. To calculate gs, we must know the sun’s position [2]. A general formula for gs, from Braun and Mitchell 0 [31], is conveniently written in terms of gs , a pseudo surface azimuth angle in the first or fourth quadrant: 0

gs ¼ a1 a2 gs þ 180
a3 ðð1  a1 a2 Þ=2Þ

(7)

514

CHAPTER 2.16 OPTIMIZATION OF SLOPE ANGLES

FIGURE 6 Solar azimuth angle, zenith angle, and change in solar altitude angle.

where 0

sin gs ¼ ððsin u
cos dÞ=sinqz Þ

(8)

where a1, a2, and a3 are constants related to sunrise and sunset; g represents the surface azimuth angle, the deviation of the projection on a horizontal plane of the normal to the surface from the local meridian, 180  g  180 degrees [2]. Fig. 6 shows changing of the zenith angle and solar altitude angle according to the solar azimuth angle. The value of the solar azimuth angle is zero at noon. Slope angle (b): The slope angle (b) is the angle between the plane of the surface in question and the horizontal, and its value changes according to 0  b  180 degrees [2]. tan b ¼ tan qz jcos gs j

(9)

3. RESULTS AND DISCUSSION

3.1 GEOGRAPHICAL LOCATION AND INSOLATION LEVEL Turkey is geographically in the northern hemisphere between latitudes 36e42 degrees (N) and longitudes 26e45 degrees (E) [32]. There is a 19 degrees longitude difference between locations at the easternmost and westernmost ends of the country. Although Turkey has good insolation potential, levels vary among locations. The yearly average total radiation time in Turkey has been calculated as 2640 h per year (7.2 h/day), and the total average annual solar radiation is 1311 kWh/m2 per year (3.6 kWh/m2 day, Table 2) [33].

3. RESULTS AND DISCUSSION

515

Table 2 Monthly Solar Energy Amount of Turkey Monthly Total Solar Energy Months

(Kcal/cm2-month)

(kWh/m2-month)

Sunshine Duration (h/month)

January February March April May June July August September October November December TOTAL (per year) AVERAGE

4.45 5.44 8.31 10.51 13.23 14.51 15.08 13.62 10.60 7.73 5.23 4.03 112.74 308.0 cal/cm2-day

51.75 63.27 96.65 122.23 153.86 168.75 175.38 158.40 123.28 89.90 60.82 46.87 1311 3.6 kWh/m2-day

103.0 115.0 165.0 197.0 273.0 325.0 365.0 343.0 280.0 214.0 157.0 103.0 2640 7.2 h/day

3.2 APPLICATIONS OF OPTIMAL SLOPE ANGLES FOR DIFFERENT SEASONS Solar radiation data are used in several forms. The most detailed information available is beam and diffuse solar radiation on a horizontal surface, per hour. Daily data are often available, and hourly radiation can be estimated from daily data. Data for the amount of monthly total solar radiation on a horizontal surface are used in some process design methods [2]. Some solar collectors “track” the sun by moving in prescribed ways to minimize the incidence angle of beam radiation on their surfaces and thus maximize the incident beam radiation [2]. Installation and operation of these collectors requires relevant data on the angles of incidence and the surface azimuth angles. Tracking PV systems are classified by their motions. Rotation can be about a single axis (horizontal eastewest, horizontal northesouth, or parallel to the Earth’s axis), or it can be about two axes. For a plane rotating about a horizontal eastewest axis with a single daily adjustment, the beam radiation is normal to the surface at noon each day [2], cos q ¼ sin2 d þ cos2
cos u

(10)

The slope of this surface can be calculated as follows: b ¼ j
 dj

(11)

For a plane rotated about a horizontal eastewest axis with continuous adjustment to minimize the angle of incidence [2],
1=2 cos q ¼ 1  cos2 d
sin2 u (12)

516

CHAPTER 2.16 OPTIMIZATION OF SLOPE ANGLES

the slope of this surface is tan b ¼ tan qz jcos gs j

(13)

where gs is the solar azimuth angle. If the slope of an array is set at an angle qz to the horizontal, the radiation on the array is normal to the surface at noon. Thus, an array would be exposed to the maximum level of solar radiation available at that location [34]. The slope of an array can also be seasonally adjusted. In summer or winter, the slope angle of an array is different from the other seasons; however, the slope of an array at any time of year can be set as an optimal value for the rest of the season. For the best average slope to achieve optimal summer and winter and thus annual performance, an array should be mounted at (Ø  15) and (Ø þ 15) degrees, respectively, with a slope angle of (0.9
Ø) degrees [29]. Daily and monthly average slope angles can be calculated using the MATLAB software program. For optimal seasonal performance, one simply chooses the average value of slope angle for the season. Using monthly average slope angles, the annual average optimal slope angle can be determined. Periodic adjustment of the slope angle can be economically advantageous at higher latitudes and help maximize the performance and generate efficiency of fixed systems. The amount of insolation received at different locations across Turkey varies according to geographical position and local climatic conditions. Thus, the researcher calculated an optimal slope angle for 13 cities across Turkey using data on insolation levels and meteorological records from 2014. The meteorological data for the 13 cities are shown in Tables 3 and 4 along with the average monthly and seasonal optimal slope angles. First, monthly average values for each city were calculated. The annual average slope angle value (0.9
Ø) degrees was then calculated using the monthly average values [29]. Fig. 7AeD presents the average values of optimal slope angles for some cities in Turkey. Fig. 8 presents seasonal average values.

4. CONCLUSION A growing number of studies reflect the growing interest in renewable energy sources, also known as the energy sources of the future. These include solar energy systems, the efficiency of which is subject to multiple factors including the accurate prediction of the optimal slope angle for an array at different times of the year. The prediction of solar radiation is quite important for many solar applications and is affected by geographic location and climatic conditions. Tables 3 and 4 show how optimal slope angles vary according to geographical locations across Turkey. Monthly, seasonal, and annual values are shown. As winter and summer values vary considerably in Turkey, the efficiency of PV arrays can be maximized if they are mounted according to these seasonal variations. It is, thus, economically beneficial to adjust the slope angle of a PV system monthly in latitudes such as those found in Turkey, calculated according to seasonal values. The mathematical model can be used to calculate the appropriate monthly or seasonal optimal slope angle for any location on earth.

Table 3 Seasonal and Annual Average Values of Optimum Slope Angles for 13 Different Cities in Turkey Annual Values ( )

Seasonal Values ( ) Latitude ( )

Longitude ( )

Spring ( )

Summer ( )

Autumn( )

Winter ( )

Ankara Elazig _ Istanbul

39.56 38.68 41.01 38.21 36.52 39.55 40.09 37.01 41.17 39.45 38.43 37.05 37.12

32.52 39.14 28.58 38.19 36.12 44.02 26.24 35.18 36.20 37.02 35.30 37.22 38.22

30.92 30.04 32.37 29.57 27.88 30.91 31.45 28.37 32.53 30.81 29.79 28.41 28.48

20.40 19.52 21.85 19.05 17.36 20.39 20.93 17.85 22.01 20.29 19.27 17.89 17.96

48.52 47.64 49.97 47.17 45.48 48.51 49.05 45.97 50.13 48.41 47.39 46.01 46.08

58.64 57.76 60.09 57.29 55.60 58.63 59.17 56.09 60.25 58.53 57.51 56.13 56.20

Malatya Hatay(Dortyol) Igdir Canakkale Adana Samsun Sivas Kayseri Gaziantep Mugla

35.60 34.82 36.91 34.38 32.86 35.59 36.08 33.30 37.05 35.50 34.58 33.34 33.40

4. CONCLUSION

Cities

517

Table 4 Monthly Average Values of Optimum Slope Angles for 13 Different Cities in Turkey Cities Ankara Elazig _ Istanbul Malatya Hatay (Dortyol) Igdir Canakkale Adana Samsun Sivas Kayseri Gaziantep Mugla

January ( )

February ( )

March ( )

April ( )

May ( )

June ( )

July ( )

August ( )

September ( )

October ( )

November ( )

December ( )

60.40 59.52 61.85 59.05 57.36

52.88 52.00 54.33 51.53 49.84

41.94 41.06 43.39 40.59 38.90

30.06 29.18 31.51 28.71 27.02

20.75 19.87 22.20 19.40 17.71

16.48 15.60 17.93 15.13 13.44

18.45 17.57 19.90 17.10 15.41

26.26 25.38 27.71 24.91 23.22

37.56 36.68 39.01 36.21 34.52

49.40 48.52 50.85 48.05 46.36

58.61 57.73 60.06 57.26 55.57

62.65 61.77 64.10 61.30 59.61

60.39 60.93 57.85 62.01 60.29 59.27 57.89 57.96

52.87 53.41 50.33 54.49 52.77 51.75 50.37 50.44

41.93 42.47 39.39 43.55 41.83 40.81 39.43 39.50

30.05 30.59 27.51 31.67 29.95 28.93 27.55 27.62

20.74 21.28 18.20 22.36 20.64 19.62 18.24 18.31

16.47 17.01 13.93 18.09 16.37 15.35 13.97 14.04

18.44 18.98 15.90 20.06 18.34 17.32 15.94 16.01

26.25 26.79 23.71 27.87 26.15 25.13 23.75 23.82

37.55 38.09 35.01 39.17 37.45 36.43 35.05 35.12

49.39 49.93 46.85 51.01 49.29 48.27 46.89 46.96

58.60 59.14 56.06 60.22 58.50 57.48 56.10 56.17

62.64 63.18 60.10 64.26 62.54 61.52 60.14 60.21

(A)

(B)

Graphics of Adana and Istanbul

(C)

(D) ( )

Graphics of Samsun and Hatay Dortyol

Graphics of Gaziantep and Igdir

Graphics of Ankara and Mugla

FIGURE 7 Average optimum slope angles for some cities in Turkey (AeD). 70

25

60 20 50 40 30

15

10

20 5 10 0

FIGURE 8 Seasonal average optimum slope angles for 13 cities in Turkey.

0

Spring Autumn Winter Summer

520

CHAPTER 2.16 OPTIMIZATION OF SLOPE ANGLES

NOMENCLATURE Io q V qz u as q g gs b d

Reverse saturation current, ampere (A) Electron electric charge (1.6
1019 C) Voltage (volt, V) The zenith angle (degrees) The solar hour angle (degrees) The solar altitude angle (degrees) The incidence angle (degrees) The surface azimuth angle (degrees) The solar azimuth angle (degrees) Slope angle (degrees) Declination angle (degrees)

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CHAPTER

DESIGN, ENERGY AND EXERGY ANALYSES OF LINEAR FRESNEL REFLECTOR

2.17

Melik Z. Yakut, Arif Karabu
ga, Ahmet Kabul, Re¸sat Selba¸s Suleyman Demirel University, Isparta, Turkey

1. INTRODUCTION Renewable energy is also defined as energy obtained from natural sources and sustainability. The current pollutant effect of carbon dioxide increases the importance of renewable energy sources as the need for energy increases day by day. Compared to fossil fuels, renewable energy has many economic and environmental advantages. The sun is a major source of energy for orbiting planets. It is also an indispensable resource for life in the world. Today a large part of the various energy sources emerge as a result of events that caused formation of the sun. Solar energy consists of rays of various wavelengths. It is possible to use solar energy almost everywhere that energy is needed. Solar energy is clean. There is no polluting smoke, gas, carbon monoxide, sulfur, or nuclear waste in the use of solar energy. Solar energy can be used for direct conversion into electricity (by photovoltaic conversion) and into thermal energy. Further, thermal energy conversion can be classified into three categories [1]: 1. low temperature range (150
C). There are two types of systems that benefit from solar energy. The first type is the direct thermal focusing effect and the other includes the technological products that provide direct electrical energy production. Solar thermal energy is more economical and environmentally friendly and is available in many different areas. Solar thermal energy is used in factories, schools, and hospitals to provide both hot water and heating needs. Depending on the temperature of the water supplied by the thermal energy, it is also possible to generate electricity with various converting equipment. The linear Fresnel reflector (LFR) works by linear condensation. The receiver pipe/pipes passing through the focal point are at a constant height and the reflection is performed with the flat mirrors arranged in rows following the sun. Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00029-9 Copyright © 2018 Elsevier Inc. All rights reserved.

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CHAPTER 2.17 DESIGN, ENERGY AND EXERGY ANALYSES

Solar energy collectors are special kinds of heat exchangers that transform solar radiation energy to internal energy of the transport medium. The major component of any solar system is the solar collector. This is a device that absorbs the incoming solar radiation, converts it into heat, and transfers the heat to a fluid (usually air, water, or thermal oil) flowing through the collector [2]. LFR, as shown Fig. 1, uses long segments of mirrors, located at the focal axis of the different rows, to focus sunlight onto a fixed absorber located at a common focal point of the reflectors. The fixed absorber includes one or several absorber tubes. The distances and angles of the reflectors to each other are shown in Fig. 2. A secondary concentrator is used to reflect the rays within an accepting angle. This

FIGURE 1 Construction principle of linear Fresnel reflector.

FIGURE 2 Geometry of linear Fresnel reflector.

2. SYSTEM DESCRIPTION

525

concentrated energy is transferred through an absorber into water. Then through a heat exchanger energy is extracted and used to generate power or other commercial applications [3]. LFR shows a number of advantages when compared to other concentrating solar power (CSP) technologies when it comes to industrial applications, including: (1) direct steam generation capability (capability possible in other CSP technologies, but rarely used), eliminating the need for heat exchangers that increase plant costs and reduce thermal energy production efficiency; (2) highly variable temperature and pressure ranges that can be adapted depending on the industrial application; (3) lowest land occupancy, knowing that a large chunk of steam-consuming facilities are located in industrial zones where land availability is scarce; (4) high modularity, ranging from a few hundred kilowatts to several megawatts; (5) low environmental impact due to the limited raw material use and deletion of synthetic fluids (capability possible in other CSP technologies, but rarely used); and (6) lowest leveled cost of energy due to its modularity, simple and efficient design, direct steam generation, and low O&M requirements [4,5]. In addition, Fresnel reflectors can be very useful for solar energy, especially in large installations. The potential integration of LFR technology has been studied for a wide spectrum of industries that use steam for thermal applications. These applications address direct human needs such as water and food; assistance of other energy/energy-consuming industries such as oil-gas, petrochemicals, and mining; and temperature regulation needs [4,6]. In this study, we present the design and performance analysis of an LFR. The numerical calculations of the LFR system are calculated using the Engineering Equation Solver (EES) software. The use of renewable energies for power generation is a major issue for today’s society in order to avoid energy dependence and reduce the impact of greenhouse emissions [7]. Medium- and high-temperature heat can be produced by using concentrating solar technologies. Based on the reflector configurations, the solar-concentrating technologies may be classified as: LFR, parabolic trough, parabolic dish, and power tower. Among these, the LFR system is simple in design and a cost-effective system for medium-temperature (100e400
C) applications. The performance of LFR system significantly depends on the receiver design. The earlier research work on LFR has been reported in the following order. The design and performance investigation of LFR was reported first, followed by heat loss analyses from the cavity receiver for LFR [8]. LFR technology is regarded as a prospective method for CSP, solar industrial heating, and solar cooling due to its simplicity in structural design and low manufacturing costs. Generally, an LFR (Fig. 1) consists of three main components: mirror field, receiver, and tracking system. The direct solar radiation can be reflected by an array of parallel mirrors to a fixed focal line at which the receiver is mounted [9].

2. SYSTEM DESCRIPTION Skew of each mirror element is very important in optical design. The position of the sun, relative to the axis of rotation of the LFR elements, is determined from the solar profile angle. The skew of each mirror element is chosen such that a ray is perpendicular to the plane of the aperture of the collector. The mirrors are placed in such a way that the reflected rays do not touch each other until the focal plane. A tubular absorber of appropriate size placed in the focal plane of an LFR solar concentrator would intercept all the solar radiation from the constituent mirror elements. The design has been used in 10 reflective mirrors. Each mirror is chosen to be 610 and 2000 mm in width.

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CHAPTER 2.17 DESIGN, ENERGY AND EXERGY ANALYSES

2.1 DESIGN PARAMETERS The location at the first mirror, Q1 ¼ R þ f tanðx0 Þ

(1)

Here, Q is the distance of the first mirror, R is the radius of the absorber, f is the focal distance from the aperture plane, and x0 is the subtends angle of the sun. Each mirror value (angle, distance, space) for: Qn ¼ Qn1 þ W cosðqn1 Þ þ S2

(2)

Sn ¼ W sinðqn1 Þtanð2qn þ x0 Þ 20 13   W Q þ Þ cosðq 1 C7 6B 1 2 6B C7 q1 ¼ 1=2 tan1 6B C7 W 4@ A5 sinðq1 Þ f 2

(3)

(4)

Here, Qn is for mirror element located at a distance from the center of aperture plane; W is the width of the mirror; and q is geometrical optics relations, the skew of mirror element [3]. W þ f tanðx0 Þ (5) 2 By considering all of the above values, the values of skew, shift, and location can be calculated by EES in the above equations for each mirror element using iteration method. Q1 ¼

2.2 ENERGY AND EXERGY ANALYSES In this section, the energy and exergy analyses of LFR are calculated (Table 3). In Section 2.1, design parameters (Tables 1 and 2) are set to maximize solar energy. There are two different energy inputs in the system. These are solar energy and the energy of the water entering the system. To find the solar energy going to the receiver, multiply the radiation energy, the area of the mirrors, the number of mirrors, and the reflection coefficient of the mirror. The incident radiation energy is 600 W/m2, the reflection coefficient of mirrors is 0.92, reflection area is 1.22, and the number of mirrors is 10. The energy obtained is defined as “B.” The net energy coming to the receiver is found by multiplying the value of “B,” the area of the receiver, and the absorptivity of the receiver. This obtained value is defined as “Ib.” The receiver pipe is covered with glass. To find the area of receiver, multiply Table 1 Admissible Values Design Parameters

Symbol

Rate

Width of mirrors Focal distance from plane The sun’s the subtends angle

W f

610 mm 2500 mm

(x0)

160 ¼ 0.00465421 radian

2. SYSTEM DESCRIPTION

527

Table 2 Reflector Location Parameters Mirror No

Location (mm)

Shift (mm)

Skew (degree)

1 2 3 4 5

305.2 948.5 1639 2425 3211

0 37.75 115 230.5 371.5

6932 13.57 19.39 24.35 27.95

Table 3 Admissible Values for Energy and Exergy Analyses Parameter

Symbol

Rate

Mass flow rate of water Specific heat of water Water output temperature Water input temperature Reflectivity of mirror Permeability Mirror area Mirror number Pipe area Solar radiation Ambient temperature Sun temperature

m_ w cp Tw,out

0.0162 kg/s 4187 J/kg K 311 K

Tw,in qref a Am An A B Tair ¼ T0 Tsun

296 K 0.92 0.95 1.22 m2 10 0.5026 m2 600 W/m2 293 K 6000 K

the Ib, the diameter, and length of the glass cover. The diameter and length of the glass cover are 0.08 and 2 m, respectively. Meanwhile, the solar energy from the outer surface of the cavity is considered zero. The energy of the water entering the system is calculated using Eq. (6). This equation multiplies the water mass, the specific heat, and the water temperature difference. In the system, the water mass is 0.0162 kg/s, the specific heat of the water is 4180 J/kg
C, the input water temperature is 23
C, and the output water temperature is 38
C. The net energy rate of the water “DE_n;water ” is found by:   DE_n;water ¼ m_ w cp Tw;out  Tw;in (6) where “m_ w ” is the mass flow, “cp” is the specific heat of the water, “Tw,out” is the output water temperature, and “Tw,in” is the input water temperature. Radiation energy from mirrors to receiver is: Ib ¼ Bqref Am An

(7)

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CHAPTER 2.17 DESIGN, ENERGY AND EXERGY ANALYSES

where “B” is the radiation energy from sun, “qref” is the reflection coefficient of mirrors, “Am” is the area of mirror, and “An” is the mirror number. The solar energy input rate “DE_nsolar;in ” is found by: E_nsolar;in ¼ Ib aA where “a” is the transmissivity of receiver, and “A” is the area of receiver. The energy efficiency of the system “h” is determined by: ! DE_n;water h¼ E_nsolar;in

(8)

(9)

In order for the system to be able to perform an exergy analysis, it is necessary to find the input _ w ” is determined by: exergy values. The total exergy rate of water “DEx _ w ¼ Ex _ w;out  Ex _ w;in DEx _ w;out ” is the output water exergy, and “Ex _ w;in ” is the input water exergy: where “Ex      _ w;out ¼ m_ w cp Tw;out  Tair  Tair ln Tw;out Ex Tair      _ w;in ¼ m_ w cp Tw;in  Tair  Tair ln Tw;in Ex Tair

(10)

(11) (12)

where “Tair” is the ambient temperature. Exergy is considered with a reference environment. If a thermodynamic system is in equilibrium with the environment, the state of the system is called the “dead state” and the temperature is called the dead state temperature. It is generally equal to environment temperature. So, dead state can be considered as the reference state [7]. _ solar;in ” is determined by: The solar exergy input rate “Ex "   4 # 1 T 4 T air air _ solar;in ¼ E_nsolar;in 1 þ  Ex (13) 3 Tsun 3 Tsun where “Tsun” is the sun temperature. The exergy efficiency rate “j” is defined as: j¼

_ w DEx _ Exsolar;in

(14)

3. RESULTS AND DISCUSSION The design, energy and exergy analyses were applied to the LFR system. In the study, numerical calculations were done with the EES program. The results are generally tabulated in Table 4. The inlet and outlet values of the water are substituted in Eq. (6). The net energy change of the water entering the LFR was calculated as 1017 W. As shown in Fig. 3, the output water temperature of the system is influential on the efficiencies. When the temperature of the output water rises, this causes the efficiencies to increase. The rays from the sun are focused on the

3. RESULTS AND DISCUSSION

529

Table 4 Results of Analyses Result of the Analyses

Rate

Unit

Net energy changing rate of the water Radiation energy from mirrors to receiver The solar energy input rate The energy efficiency The exergy of output water The exergy of input water Net exergy changing rate of the water The solar exergy input rate The exergy efficiency

1017

W

6734

W/m2

3215

W

31.64 36.03

% W

1.035

W

35

W

3006

W

1.164

%

0.8

0.06 Exergy efficiency

0.7

0.05

0.6

0.04

0.5

0.03

0.4

0.02

0.3 310

315

320

325

330

Exergy efficiency

Energy efficiency

Energy efficiency

0.01 335

Outlet temperature (K)

FIGURE 3 Efficiencies change depending on output water temperature.

receiver pipe with 10 mirrors. The energy reflected to the receiver was found to be 6734 W/m2 using Eq. (7). The total solar energy entering the system was calculated as 3215 W using Eq. (8). The first law efficiency of the system was calculated as 31.64% using Eq. (9). In order to find the net exergy change of the water in the system, the exergy values of the input and output water were

530

CHAPTER 2.17 DESIGN, ENERGY AND EXERGY ANALYSES

found. The exergy of the input and output water were found to be 1.035 and 36.03 W, respectively. It is normal to increase the exergy rate of water due to the solar exergy gain by solar radiation. Using Eq. (10), the net exergy change of the water was calculated as 35 W. The solar energy entering the system was calculated as 3006 W by using Eq. (13). The net exergy change of the system was calculated using Eq. (14). The exergy of the system was found at 1.164%. The energy and exergy analyses of the system efficiencies are given in Fig. 4. The exergy efficiency change depends on the ambient temperature as shown in Fig. 5. Exergy value is less than energy value.

FIGURE 4 Energy and exergy efficiencies of the system.

exergy efficiency

0.012

Exergy efficiency

0.01 0.008 0.006 0.004 0.002

292

294

296 298 300 Ambient temperature (K)

FIGURE 5 Exergy efficiency change depending on ambient temperature.

302

304

NOMENCLATURE

531

This is because the ambient temperature (dead state) is included in the calculations. This demonstrates the importance of environmental temperature in exergy analysis. So, this shows the real useful part of the energy.

4. CONCLUSIONS This study’s design and performance analysis of LFRs are presented. Performance analysis includes energy and exergy analyses. As a result, the following main conclusions can be extracted from the study: • •

• •

The values obtained from the analysis results show that a linear Fresnel reflector applicability is possible. Linear Fresnel reflector systems, if possible in a closed system, can reach high temperatures. When the heat loss is analyzed, it shows a significant heat loss in the cavity part. Isolation is required in order to prevent these losses. If the cavity region of the linear Fresnel reflector systems is simulated with computer aided engineering programs, the results are obtained more efficient and realistic. The energy efficiency of the LFR is higher than the corresponding exergy efficiency. This shows that the effect of the environment temperature on the efficiency cannot be undervalued.

NOMENCLATURE A Am An B cp CSP E_n;solar f Ib LFR m_ w Qn qref Sn Tair Tsun Tw,in Tw,out W a h qn x0 j DEn;water DEx;water

Pipe area (m2) Mirror area (m2) Mirror number Solar radiation W/m2 Mass flow rate of water (J/kg K) Concentrating solar power The solar energy (W) Focal length (mm) Radiation energy from mirrors to receiver (W) Linear Fresnel reflector Mass flow rate of water (kg/s) Mirror element located (mm) Reflectivity of mirror Distance between mirrors (mm) Ambient temperature (K) Sun temperature (K) The water input temperature (K) The water output temperature (K) Width of mirror (mm) Permeability Energy efficiency Skew of mirror (degree) The sun’s subtended angle (radian) Exergy efficiency The net energy rate of the water (W) The total exergy rate of water (W)

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CHAPTER 2.17 DESIGN, ENERGY AND EXERGY ANALYSES

REFERENCES [1] Tiwari GN. Solar energy fundamentals, design, modelling and applications. Delhi: Alpha Science; 2002. [2] Kalogirou SA. Solar energy engineering: processes and systems. Cyprus: Academic Press; 2009. [3] Gouthamraj K, Rani KJ, Satyanarayana G. Design and analysis of rooftop linear Fresnel reflector solar concentrator. International Journal of Engineering and Innovative Technology (IJEIT) 2013;2(11):66e9. [4] Hobeika S, Alexander B, Benmarraze S, Itskhokine D, Yang F, Benmarraze M. Case study: linear Fresnel reflectors (LFR) solar systems for industrial applications. 2015. Retrieved from: http://www.solareuromed. com/en/documentation. [5] Yanga F, Itskhokinea D, Benmarrazea S, Benmarrazea M, Hoferb A, Lecatc F, Ferrie`rec A. Acceptance testing procedure for linear Fresnel reflector solar systems in utility-scale solar thermal power plants. 2015. Retrieved from: http://www.solareuromed.com/en/documentation. [6] Itskhokinea D, Le`cuillier P, Benmarrazea S, Rabut Q, Guillier L. Fresnel 1 project: design, construction and testing of a linear Fresnel pilot plant in the Pyrenees. 2015. Retrieved from: http://www.solareuromed.com/en/ documentation. [7] Sait HH, Martinez-Val JM, Abbas R, Munaz-Anton J. Fresnel-based modular solar fields for performance/cost optimization in solar thermal power plants: a comparison with parabolic trough collectors. Applied Energy 2015;141:175e89. [8] Reddy KS, Kumar KR. Estimation of convective and radiative heat losses from an inverted trapezoidal cavity receiver of solar linear Fresnel reflector system. International Journal of Thermal Sciences 2014;80:48e57. [9] Lin M, Sumathy K, Dai YJ, Wang RZ, Chen Y. Experimental and theoretical analysis on a linear Fresnel reflector solar collector prototype with V-shaped cavity receiver. Applied Thermal Engineering 2013;51: 963e72.

CHAPTER

INTEGRATION OF REFLECTORS TO IMPROVE ENERGY PRODUCTION OF HYBRID PVT COLLECTORS

2.18

Khaled Touafek, Ismail Tabet, A. Khelifa, Hafsia Haloui, Hanane Ben cheikh el hocine, Mohaled T. Baissi, Ali Malek Centre de De´veloppement des Energies Renouvelables, CDER, Ghardaı¨a, Algeria

1. INTRODUCTION The concept of a hybrid photovoltaic thermal (PVT) collector uses two types of energy, electrical and thermal. The weakening and the fall of efficiency allowed the researchers to find new solutions that solve this problem. This work detects one of these innumerable techniques. A photovoltaic module produces more electricity if it is cooled. In the case of hybrid PVT collectors integrated into a roof, heat will be more than a module mounted alone. High temperature of photovoltaic cells causes a reduction in its electrical efficiency. This effect can be resolved by the application of recovering heat by means of fluid (water or air), which circulates inside the cells. The hybrid solar collectors are a more economical solution and are less bulky for use in hot water, heating, and electricity production [1]. Several institutes and research centers around the world have studied hybrid collectors. Hybrid collectors using air and water with absorbers were evaluated experimentally [2] and analytically [3,4]. Kern and Russell [5] give the main concepts of these systems that use water or air as the heat transfer fluid. Bhargava et al. [6] and Prakash [7] present the results of their work on the effect of flow and air channel. Sopian et al. [8] studied work on the performance of hybrid collectors in 1995 and 1996. The thermal efficiency of these PVT systems was in the range of 45%e65%. Bergen and Lovvik [9] analyzed the transfer of energy between the various components of the PVT hybrid system using liquid as a heat transfer fluid. Brinkworth et al. [10] presented a parametric habitat study. Garg and Adhikari [11] studied the PVT system using air for heating in single and double glazing. The results found were very encouraging; they found 70% thermal yields with liquid cooling and 60% for air-cooling. Huang et al. [12] proposed the PVT hybrid collector with a hot water tank and Zondag et al. [13] included another PVT system design. B.S. Sandnes et al. [14] studied thermal photovoltaic collectors based on a polymer absorber. The increase in total energy production of the PVT hybrid system can be achieved by using diffuse Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00030-5 Copyright © 2018 Elsevier Inc. All rights reserved.

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CHAPTER 2.18 INTEGRATION OF REFLECTORS

aluminum reflectors as amplifiers that will produce a uniform distribution of solar radiation reflected on the surface of the hybrid collector [15e19]. In 2007, a new study of a system combining hybrid solar water collector and solar flare in an integration phase with a building located in Macon was realized [20]. The system is composed of mono- and polycrystalline cells. They demonstrate that, in the case of glazing, the annual electrical efficiency of the combined hybrid system is 6.8%, which is 28% lower than the performance of a nonintegrated PV solar collector (9.4%). They explain this drop in electrical efficiency by an increase in the operating temperature of the PV panels (which may be greater than 100
C) due to the glass cover. On the other hand, in the absence of glazing, the electrical efficiency is 10%, which is 6% higher than that of the integrated PV solar collector. The sharp increase in temperature of the PV modules in the summer prevents the use of ethylene vinyl acetate (EVA) as the adhesive of PV panels in a vitreous component. Fraisse et al. [21] note that in this type of configuration, the use of amorphous cells is the most suitable because they are less sensitive to temperature variations. However, the electrical efficiencies obtained are low given the low electrical efficiency of the amorphous PV cells (4%e7%). Chow et al. [22] present the modeling and comparative study of the performance of a PVT hybrid water solar collector. Two prototypes of hybrid solar collectors were constructed, the first of which was modeled in 2006 [23]. The second, more efficient component was modeled more finely [22]. It is a glazed solar collector composed of a crystalline silicon PV panel bonded to a metallic absorber. Water circulation tubes are welded to the back of this absorber. The system is coupled to the horizontal storage tank. The results of the simulation show that the mean annual thermal efficiency of this PVT hybrid water solar collector is 38.1% and that of the solar collector at water is 43.2%. Moreover, the comparison of the hybrid solar collector with a PV solar collector shows that the cooling with water as heat transfer fluid makes it possible to reduce the operating temperature of the PV modules. In this sense, the annual power output of the hybrid solar collector is 2.2% higher than that of the PV solar collector. Chow et al. [24] continued the study of PVT hybrid solar collectors through the integration of a system to the facade of a building. The thermal efficiency was estimated at 38.9% at low temperature and the electrical efficiency at 8.56%. Kalogirou et al. [25] conducted a previous study of solar PVT hybrid air collectors [26]. They analyzed the behavior of PVT hybrid water, solar collectors with cell-based PV panel polycrystalline silicon or amorphous cells at three sites. These components have been integrated into industrial buildings and each has a total surface area of 300 m2. The evaluation of the economic aspect of these systems has shown that they are advantageous in particular for sunny sites. It was noted that hybrid water systems made up of PV modules without thermal protection on the front face have large thermal losses, resulting in a lower operating temperature of the system. A glass cover can be added to the front panel to remedy this issue. Research on hybrid solar collectors with heat transfer fluid is constantly evolving, so the list of systems presented earlier is not exhaustive. We can cite the solar collector PVT with nonglazed water marketed by the company Millennium Electric. In addition, ECN offers PVTWINS PV/T solar collector. This is the product of a collaboration between ECN, ZEN Solar and Shell Solar and Renewable Energy Systems (RES) in England. Later, Solar Design Associates companies, Sunearth Unisolar carried out a project called PV BONUS from 1997 to 2003. They combined a Unisolar PV rolled solar collector with a Sunearth solar thermal collector. However, the numerous technical difficulties encountered, mainly due to the mechanical incompatibility of construction materials,

2. SYSTEM DESCRIPTION

535

prevented the project from being completed. The Power light company, from 1997 to 2003, managed a PV BONUS project in which they developed a system consisting of a Unisolar flexible laminated PV solar collector glued to a flexible EPDM absorber. However, following delamination of PV modules, marketing was delayed. In 1999, ICEC developed and tested a PVT component with a liquid coolant. Among the many possibilities of thin-film technologies, the most promising are those based on compound semiconductors, in particular: amorphous silicon (a-Si), cadmium telluride (CdTe), copper indium selenium (CIS), and copper indium gallium selenium (CIGS) [27]. Many authors have adopted different PV subjects and thermal sensors, such as in 2011, when G. N. Tiwari, R. K. Mishra, and S. C. Solanki presented an examination of the various photovoltaic modules (c-Si, p-Si, r-Si, A-Si, CdTe, and CIGS) and their electrical and thermal applications such as thermal heating, drying, etc. In 2013, R. K. Mishra and G. N. Tiwari tried to evaluate and compare the energy matrices of a hybrid thermal water, photovoltaic collector (HPVT) in the constant collecting temperature mode with five different types of photovoltaic modules, namely mono and crystalline silicon amorphous silicon (thin film), silicon, CdTe, and CIGS. They found that monocrystalline silicon is the best alternative for the production of electrical and thermal energy [28]. G. N. Tiwari and Ankita Gaur also discuss the application of HPVT [29].

2. SYSTEM DESCRIPTION The concentration of sunlight has been used since ancient times in China to perform useful tasks. A legend tells that Archimedes used a “burning mirror” to concentrate the rays of the sun on the fleet of Roman invaders and repel them from Syracuse. In 1973, a Greek scientist, Dr. Ioannis Sakkas, was curious as to whether Archimedes had really been able to destroy the Roman fleet in 212 B.C. J.C. aligned nearly 60 Greek sailors, each with a tilted rectangular mirror to catch the sun’s rays and directed them toward a tarred plywood silhouette about 49 m away. The ship caught fire after a few minutes. In 1866, Auguste Mouchout used a cylindrical-parabolic collector to produce steam for the first solar steam engine. The Italian Alessandro Battaglia in Genoa, Italy, obtained the very first patent for a solar collector in 1886. In the years that followed, inventors such as John Ericsson and Frank Shuman developed energy devices, solar energy for irrigation, refrigeration, and locomotion. In 1913, Shuman completed the construction of a 55 HP parabolic solar power station in Meadi, Egypt, for irrigation. Another Genoan, Professor Giovanni Francia (1911e80), designed and built the first concentrating solar power plant, which was commissioned in Sant’Ilario d’Enza, near Genoa, Italy, in 1968. It had the architecture of current solar power plants with a solar receiver placed in the center of a field of solar collectors. It was capable of producing 1 MW with superheated steam at 100 bar and 500
C. The 10 MW Solar One tower power plant was developed in Southern California in 1981, but the nearby solar energy generating systems (SEGS) cylindrical-parabolic technology, which was built in 1984, was more exploitable. The SEGS installation of 354 MW remains today the largest solar power plant in the world. Solar power plants use relatively new technologies with significant potential for development. They offer an opportunity to sunny countries comparable to that of wind farms in coastal countries. The most promising areas for the implementation of these technologies are those in the southwestern United States, South America, much of Africa, the Mediterranean and Middle Eastern countries, the desert plains of India and Pakistan, China, Australia, etc. [30] (Fig. 1, [31]).

536

CHAPTER 2.18 INTEGRATION OF REFLECTORS

FIGURE 1 Average solar irradiation.

In many parts of the world, a square kilometer of land would be enough to generate up to 120 GWh of electricity per year. This energy is equivalent to the annual production of a conventional 50 MW power plant. The production of electricity from solar radiation is a direct process. Since the solar energy is not very dense, it is necessary to concentrate it in order to obtain operable temperatures for the production of electricity. The radiation is concentrated at a point or in a line, where the thermal energy is transmitted to the heat transfer fluid. The intensity of the concentration is defined by the concentration factor. The higher the temperature, the higher the temperature reached. The addition of reflectors can prevent heat loss at the top with thermal insulation on the sides. That prevents loss of heat at the back and edges. After coverage, the solar cells form the first surface of absorption with a black plate of aluminum directly after the cells; this plate absorbs the radiation between the cells. After the plate, copper tubes are welded to the aluminum plate to ensure the circulation of the heat transfer fluid with glass cover, solar cell, copper tube, and insulation. Touafek et al. [32,33] designed and built a hybrid solar PVT water collector. They studied a hybrid solar component composed of a glass solar collector with liquid coolant and a planar absorber of nonselective aluminum and monocrystalline silicon PV module. The PVT concentrator means the concentration of solar radiation on a hybrid PVT collector. The PV module consists of three layers: • • •

Glass layer, which is the face, exposed to the incident solar radiation. The layer containing the photovoltaic cells (included in the EVA). The protective layer, which is the Tedlar.

2. SYSTEM DESCRIPTION

537

FIGURE 2 The three layers of the photovoltaic module.

The photovoltaic cell is composed of a semiconductor material that absorbs light energy and transforms it directly to the electric current; the cells (in monocrystalline silicon) have a rate of efficiency of 15%e24% in the laboratory. Fig. 2 shows the three layers of the photovoltaic module. A photovoltaic module housed in an enclosure metal, which includes the lateral and transverse thermal insulation, constitutes the hybrid PVT collector (Fig. 3). The thermal system is placed on the bottom of the PV module. Theoretical models are used to calculate (predict) the thermal production of hybrid collectors. These models are based on the distribution of the heat flux in the different layers of the collector. The thermal study of the hybrid collector revealed various physical processes involved in its functioning; it is therefore a prerequisite for the development of a mathematical model. Energy balances represent the rules for the evolution of the model of an initial state at a given time. They reflect the principle of conservation of energy. Each element of the system can thus be presented by an equation of energy balance, which is written as: X X dTi (1) Qi  Qi ¼ Mi $Cpi dT i i

FIGURE 3 Sectional view of the hybrid collector.

538

CHAPTER 2.18 INTEGRATION OF REFLECTORS

The thermal energy provided by the solar radiation is given as follows: Qg ¼ Apv $Ig $asi $sglass

(2)

The glass surface becomes an emitting surface; the thermal losses by radiation are expressed as follows:   Qray; air ¼ s$εglass $Aglass T4glass  T4air (3) We have expressed heat losses by convection by the equation of heat transfer between the glass and the external environment: Qconv; air ¼ hi $Apv ðTglass  Tair Þ

(4)

This convective transfer coefficient, which is a function of the wind speed, is given by the following expression [2]: hi ¼ 2:8 þ 3:0 V The electrical energy produced by the hybrid collector [34] is given by: Qele ¼

Qg h $exp½bðTsi  Tref Þ asi ref

(5)

with b, temperature coefficient, which represents the relationship between the efficiency of the solar cell and the temperature, which is equal to 0.004 for a silicon solar cell; Tsi, temperature of solar cell in [K]; href, is the reference efficiency measured for a reference temperature Tref taken equal to 25K. The heat equation by conduction between the sensor glass and the photovoltaic cells is given by: Qcond; glas; si ¼

lglass Apv ðTglass  Tsil Þ Eglass

(6)

with Everre, glass thickness. The other layers of the hybrid collector are traversed by a flow of heat by the same mechanisms as that described previously. Touafek et al. [35] describe the details of the energy model of the hybrid PVT collector.

3. EXPERIMENTAL APPARATUS AND PROCEDURE In this section, the experimental study is discussed. The aim of our experimental study was to extract the electrical performances (characteristics I ¼ f(v)) and to determine the temperature distribution of the PVT hybrid collector. For this, we placed on the same structure three collectors for comparison. The first was a single PV collector, the second and third were a hybrid PVT collector with and without reflectors. The module used is based on silicon. It is of type UDES 50 in. monocrystalline technology: • • •

Its dimensions are: length: 1290 mm; width: 330 mm, thickness: 30 mm. Composition of the module: 2  36 monocrystalline silicon cells in series. The absorber is the internal element of the hybrid collector; its main role is to absorb heat from the solar panel (cooling system) and transmit this heat to the outlet (Fig. 4).

3. EXPERIMENTAL APPARATUS AND PROCEDURE

539

FIGURE 4 Absorber.

In our study, we proposed a prototype absorber (serpentine), which is in direct contact with the rear face of the module (Fig. 4). The metal support is the main component of the collector, which supports all elements of the sensor and ensures the safety of the interior elements (Fig. 5). It is constructed entirely of iron and galvanized sheet metal. The insulation used is glass wool, which insulates the inside of the heat exchange sensor with external factors. The glass wool is cut to the same internal dimensions of the support (bottom and sides) as shown in Fig. 6. The glass wool is placed inside the body of the collector; the insulating plate is then placed on top and fixed. Subsequently, the absorber is placed on the rear face of the PV module by sliding it inside the metal support. Finally, the silicone is placed in the terminal of the PV module to confirm that the module is firmly attached to the collector frame, as shown in Fig. 7, which shows a hybrid water-based PVT collector. In the aim to study the effect of reflectors, we created a prototype of the hybrid PVT collector with reflector. Fig. 8, is a photo of the prototype of hybrid PVT collectors with two reflectors.

540

CHAPTER 2.18 INTEGRATION OF REFLECTORS

FIGURE 5 The metal support.

FIGURE 6 Glass wool.

3. EXPERIMENTAL APPARATUS AND PROCEDURE

541

FIGURE 7 Prototype of hybrid PVT water collector.

FIGURE 8 Prototype of PVT collector with reflectors.

To take temperature measurements, we used thermocouples type “K”, to measure, remove the input, and output temperature of the PVT hybrid collector (Fig. 9). With two thermocouples inside the collector, the first is placed on the absorber and the second on the insulating plate, both in the middle. Ts PVT: Water outlet temperature. Te PVT: Water inlet temperature. During these tests, we measured the temperatures of each hybrid collector layer at a concentration such as the temperature of the PVT cells, the absorption tank, the temperature at the inlet and outlet, and the voltage and current of each photovoltaic panel.

542

CHAPTER 2.18 INTEGRATION OF REFLECTORS

FIGURE 9 The location of the thermocouple on the PVT collector.

The purpose of these tests is to show the behavior and electrical PVT hybrid system and the effect of the addition of the solar reflector on performance.

4. RESULTS AND DISCUSSION The site of the experimental study is Ghardaı¨a in the south of Algeria. The daily evolution of the global solar radiation is measured and stored every 1 min. The solar irradiance in W/m2. Figs. 10 and 11 represented the global radiation and ambient temperature on the day of experimental study. The two curves show that the sky is clear during the test day (Fig. 10) and (Fig. 11). Fig. 11 shows the variation in ambient temperature during the tests. We note that the ideal test day for our study illumination is 1000 W/m2 and ambient temperature of 25K at noon. The temperature of the inlet and outlet temperature of the heat transfer fluid is shown in Figs. 12 and 13. An increase in the temperature values of fluids during the day is observed. They reach maximum values around noon due to very interesting solar radiation. Fig. 14 shows the daily variation of the fluid temperature difference at the outlet and the input of the PVT water collector. Temperature of the heat transfer medium varies by an average of 10
C between the inlet and the outlet. The temperature of the inlet and outlet temperature of the heat transfer fluid is shown in Figs. 15 and 16. One observes an increase in the temperature values of the fluid during the day. They reach maximum values around noon due to solar radiation, which is very interesting. The temperature value of the fluid at the input of the PVT collector reaches 37
C at midday, and the temperature of the fluid at the collector output reaches 41
C at midday. An increase in the temperature of the heat transfer fluid averaging 10
C between the inlet and the outlet was found. The electrical performance of PVT hybrid collectors, PVT with reflectors, and PV module was studied. We have noted the electrical parameters and have summarized the I (V) plot. The following

4. RESULTS AND DISCUSSION

FIGURE 10 Evolution of the total solar irradiance during the day of test.

FIGURE 11 Evolution of the ambient temperature during the day of test.

543

544

CHAPTER 2.18 INTEGRATION OF REFLECTORS

FIGURE 12 Variation of the water temperature at the input of the PVT collector.

FIGURE 13 Variation of the water temperature at the output of the PVT collector.

4. RESULTS AND DISCUSSION

FIGURE 14 Variation of the difference between the temperature entered and the output of the PVT collector.

FIGURE 15 Variation of the water temperature at the input of the PVT concentrator collector.

545

546

CHAPTER 2.18 INTEGRATION OF REFLECTORS

FIGURE 16 Variation of the temperature at the output of the PVT concentrator collector.

figures show the current, voltage characteristics of the hybrid PVT collector and vacuum PV collector at different hours (Fig. 17). The power of our hybrid collector with concentration (reflector) have been increased compared to the PV module (without reflectors) because the hybrid system contains a cooling system and, in addition, a concentrator improves electrical and thermal efficiency.

FIGURE 17 Common characteristic curves.

REFERENCES

547

5. CONCLUSIONS Available solar energy can be used in photovoltaic and thermal conversion. During its exploitation of photovoltaic conversion, the cell efficiency can be improved with decreases of the temperature. This phenomenon is due to the part of the solar radiation not absorbed by the cells and which will be the source of their heat. On the other hand, this part of the absorbed radiation is lost in the form of heat, which can be exploited for different uses. One of the solutions to these mentioned problems is the cooling of the collectors by water or air. This solution can be achieved by combining two photovoltaic and thermal systems in one collector, called a hybrid PVT collector. The addition of reflectors increases the energy production of hybrid collector by the diminution of the reflected loss in the glass layer of cells.

NOMENCLATURE Apv Ci hi Ig Mi Q Ta Tciel Te Ti Ts asi εverre h l s sglass

Collector area (m2) Specific heat at pressure of the node I [J/(kg$K)] Coefficient of exchange by convection between the glass surface and the air (W/m2$k4) Total radiation absorbed by the solar cell (W/m2) Mass of the node i (kg) Heat flow (W) Ambient temperature (K) Temperature of the sky (K) Inlet temperature of the fluid (K) State variable considered (temperature) Fluid outlet temperature (K) Coefficient of absorptivity of the solar cell Emissivity of glass Efficiency Thermal conductivity [W/(m$K)] StefaneBoltzmann constant (W/m2$k4) Coefficient of transmissivity of glass

REFERENCES [1] Jong MJ, Zondag MHA. System studies on combined PV thermal panels. In: 9th International Conference on Solar Energy in High latitudes, Northsun, 6e8 May, The Netherlands; 2001. [2] Suzuki A, Kitamura S. Combined photovoltaic and thermal hybrid collector. Proceedings of the 1st photovoltaic science and engineering conference in Japan Japanese Journal of Applied Physics 1979; 19(Suppl. 19-2):79e83. [3] Florschuetz LW. Extension of the Hottel-Whillier model to the analysis of combined photovoltaic/thermal flat plate collectors. Solar Energy 1979;22:361e6. [4] Takashima T. New proposal for photovoltaic/thermal solar energy utilization method. Solar Energy 1994;52: 241e5. [5] Kern Jr EC, Russell MC. Combined photovoltaic and thermal hybrid collector systems. In: Proc. 13th IEEE Photovoltaic Specialists, Washington DC, USA; 1978. p. 1153e7.

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[6] Bhargava AK, Garg HP, Agarwal RK. Study of a hybrid solar system e solar air heater combined with solar cells. Energy Conversion and Management 1991;31:471e9. [7] Prakash J. Transient analysis of a photovoltaic/thermal solar collector for cogeneration of electricity and hot air/water. Energy Conversion and Management 1994;35:967e72. [8] Sopian K, Liu HT, Yigit KS, Kakac S, Veziroglu TN. An investigation into the performance of a double pass photovoltaic thermal solar collector. In: Proc. ASME Int. Mechanical Engineering Congress and Exhibition, San Francisco, USA35. AES; 1995. p. 89e94. [9] Bergene T, Lovvik OM. Model calculations on a flat-plate solar heat collector with integrated solar cells. Solar Energy 1995;55:453e62. [10] Brinkworth BJ, Cross BM, Marshall RH, Hongxing Y. Thermal regulation of photovoltaic cladding. Solar Energy 1997;61:169e78. [11] Garg HP, Adhikari RS. Performance analysis of a hybrid photovoltaic/thermal (PV/T) collector with integrated CPC troughs. International Journal of Energy Research 1999;23:1295e304. [12] Huang BJ, Lin TH, Hung WC, Sun FS. Performance evaluation of solar photovoltaic/thermal systems. Solar Energy 2001;70:443e8. [13] Zondag HA, De Vries DW, Van Helden WGJ, Van Zolingen RJC, Van Steenhoven AA. The yield of different combined PV-thermal collector designs. Solar Energy 2003;74:235e69. [14] Sandnes B, Rekstad J. A photovoltaic/thermal (PV/T) collector with a polymer absorber plate. Experimental study and analytical model. Solar Energy 2002;72(1):63e73. [15] Tripanagnostopoulos Y, Yianoulis P, Patrikios D. Hybrid PV e TC solar systems. In: Proc. of Int. Conf. WREC IV, Denver, USA; 1996. p. 505e8. [16] Tripanagnostopoulos Y, Nousia T, Souliotis M. Hybrid PV - ICS systems. In: Proc. of Int. Conf. WREC V, Florence, Italy; 1998. p. 1788e91. [17] Tripanagnostopoulos Y, Nousia Th, Souliotis M. Low cost improvements to building integrated air cooled hybrid PV e thermal systems. In: Proc. 16th European PV Solar Energy Conf. Glasgow, UKvol. II; 2000. p. 1874e7. [18] Tripanagnostopoulos Y, Tzavellas D, Zoulia I, Chortatou M. Hybrid PV/T systems with dual heat extraction operation. In: Proc. 17th PV Solar Energy Conference, Munich, Germany; October 22e26, 2001. p. 2515e8. [19] Tripanagnostopoulos Y, Nousia T, Souliotis M, Yianoulis P. Hybrid Photovoltaic/Thermal solar systems. Solar Energy 2002;72:217e34. [20] Projet de Recherche Inte´gre´ 6.2. Inte´gration de capteurs hybrides photovoltaı¨ques-thermiques au baˆti. Ed. Rapport final. Lyon, France. 2004. 52 p. [21] Fraisse G, Menezo C, Johannes K. Energy performance of water hybrid PV/T collectors applied to combisystems of direct solar floor type. Solar Energy 2007;81(11):1426e38. [22] Chow TT, HE W, JI J. Performance evaluation of photovoltaic-thermosyphon system for subtropical climate application. Solar Energy 2007;81:123e30. [23] Chow TT, HE W, JI J. Hybrid photovoltaic-thermosyphon water heating system for residential application. Solar Energy 2006;80(3):298e306. [24] Chow TT, HE W, JI J. An experimental study of fac¸ade-integrated photovoltaic/water-heating system. Applied Thermal Engineering 2007;27(1):37e45. [25] Kalogirou SA, Tripanagnostopoulos Y. Industrial application of PVT solar energy systems. Applied Thermal Engineering 2007;27(8):1259e70. [26] Hollick JC. Solar cogeneration panels. Renewable Energy 1998;15:195e200. [27] Mishra RK, Tiwari GN. Energy matrices analyses of hybrid photovoltaic thermal (HPVT) water collector with different PV technology. Solar Energy 2013;91:161e73. [28] Tiwari GN, Ankita G. Photovoltaic thermal (PVT) systems and its applications. In: 2nd International Conference on Green Energy and Technology; 2014.

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[29] Tiwari GN, Mishra RK, Solanki SC. Photovoltaic modules and their applications: a review on thermal modeling. Applied Energy 2011;88:2287e304. [30] Sylvain Q. Les centrales solaires a` concentration. Belgique: universite´ de LIEGE; 2007. [31] IEA SolarPACES, http://www.solarpaces.org/CSP_Technology/docs/solar_dish.pdf; 2007. [32] Touafek K, Malek A, Haddadi M. Etude Expe´rimentale du Capteur Hybride Photovoltaı¨que Thermique. Revue des Energies Renouvelables 2006;9(3):143e54. [33] Touafek K, Malek A, Haddadi M. Experimental study on a new hybrid photovoltaic thermal collector. Applied Solar Energy 2009;45(3):181e6. [34] Bakker M, Strootman KJ, Jong MJM. PVT panels: fully renewable and competitive. Germany: ISES SWC Go¨teborg; 2003. [35] Touafek K, Khelifa A, Adouane M. Theoretical and experimental study of sheet and tubes hybrid PVT Collector. Energy Conversion and Management 2014;80:71e7.

CHAPTER

THERMODYNAMIC AND THERMOECONOMIC COMPARISONS OF TWO TRIGENERATION SYSTEMS

2.19

Parisa Heidarnejad1, Alireza Noorpoor1, Ibrahim Dincer2, 3 University of Tehran, Tehran, Iran1; UOIT, Oshawa, ON, Canada2; YTU, Istanbul, Turkey3

1. INTRODUCTION Using more efficient systems appears to be an alternative to solving the problem of the lack of fossil energy sources and climate changes possibly caused by greenhouse gas emissions. Trigeneration systems that produce electricity, heating, and cooling are considered promising solutions to develop systems that use energy efficiently. Several studies have been conducted on analyzing, evaluating, and improving the performance of trigeneration systems. Zhai et al. [1] investigated the performance of a solar trigeneration system and showed that the energy and exergy efficiency of hybrid systems increased 47.8% and 2.7%, respectively, compared with solar thermal power systems. This system included an absorption chiller system, screw expander, and solar collector. They also found that the solar collector was the main source of energy and exergy loss. The results of the economic analysis showed that the payback period for the system was 18 years. Wang et al. [2] undertook a parametric optimization of an organic Rankine cycle (ORC)-based solar trigeneration system with a genetic algorithm method and indicated that their system could reach a maximum exergy efficiency of 60.33% at the optimum point. The proposed system was combined with an ORC and ejector cooling system to produce power, cooling, and heating outputs. The parametric analysis was conducted by varying the angles of the hour and slope of the aperture plane for the collector. Al-Sulaiman et al. [3] presented an exergy model of a solar-driven combined cooling, heating, and power system with an ORC system and found that their system improved exergy efficiency compared with systems that used single generation, heating cogeneration, and cooling cogeneration. The system that was studied employed an absorption chiller to provide cooling and a heat exchanger for heating. The performance of all components of the system was studied from an exergy viewpoint and revealed that solar collectors and ORC evaporators had the main share of the total exergy destruction rate of the system, and that it is essential to design them carefully. Wang et al. [4] suggested a trigeneration system using CO2 as a working fluid and performed a thermodynamic simulation mathematically. This system used the Brayton cycle and an ejector cooling system driven by solar energy as an energy source. Sensitivity analysis was performed to see the effect of the design parameters of the system on the energy and exergy of the system as criteria to assess the system’s performance. Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00031-7 Copyright © 2018 Elsevier Inc. All rights reserved.

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CHAPTER 2.19 THERMODYNAMIC AND THERMOECONOMIC COMPARISONS

Ahmadi et al. [5] developed a trigeneration system consisting of a gas turbine and ORC for electric power, an absorption chiller for cooling power, and a domestic water heater for hot water. This system worked based on the waste heat of a gas turbine; the results indicated that carbon dioxide emissions for the trigeneration system were less than for the other systems. They showed that the combustion chamber contributed the most to the total exergy destruction of the system because the combustion reaction occurs in it. They also investigated the effect of the design parameters on the exergy efficiency and environmental impact of the system. Al-Sulaiman et al. [6] performed a thermodynamic analysis of a biomass trigeneration system and determined that the fuel use efficiency of trigeneration increased compared with the system that produced only electrical power. They considered four performance modes for a system (single generation, heating cogeneration, cooling cogeneration, and trigeneration) and compared the performance of the system in these four cases. The results revealed that the ORC evaporator and biomass burner had the highest exergy destruction rate compared with the other components. Tippawan et al. [7] examined a trigeneration system including a solid oxide fuel cell as a prime mover and an absorption chiller and showed that in the trigeneration plant, there was at least a 32% gain in efficiency compared with the conventional power cycle. They validated the proposed model by comparing it with data in the literature. A parametric study was carried out to assess the net electrical efficiency and efficiency of heating cogeneration, cooling cogeneration, and trigeneration by varying the design parameters. Boyaghchi et al. [8] carried out a detailed exergy analysis of a solar trigeneration system and determined the optimum design of the proposed system. They investigated the system performance in two modes: summer and winter. The optimal performance of the proposed system was determined by multiobjective optimization by applying the evolutionary algorithm. The results of optimization showed that exergy efficiency had the potential for improvement by 27% and 13% in summer and winter modes, respectively. The cooling options of trigeneration systems employ traditional and thermally activated technologies. Thermally activated technologies are favored because of the higher overall efficiency of the system, lower emissions, and the reduction in net cost. Major thermally activated technologies include absorption chillers, adsorption chillers [9e14], ejector refrigeration [15e17], and desiccant dehumidifiers [18,19]. These cooling and dehumidification systems can be driven by steam, hot water, or hot exhaust gas derived from prime movers [20]. Recycling heat waste from industrial smokestacks is an opportunity to reduce gas emissions. One-third of energy used in industrial plants is wasted as thermal energy owing to the plant’s inefficient performance. It is not feasible to recover most of this waste heat because of its low temperature, because the economic profit of a recovery system highly depends on the quality of the waste heat. Industrial processes, such as cement production, largely consume high quality energy sources. Steam Rankine cycles, organic Rankine cycles, and Kalina cycles are existing technologies to recover the waste heat of industrial plants. To use medium-temperature waste heat, the ORC is an appropriate cycle to recover the energy of flue gas owing to the lower boiling temperature of organic fluids compared with water. Several studies were conducted on recovering the waste heat of cement plants. Bronicki et al. [21,22] studied several industries that used ORC technology through waste heat sources, such as the A.P. Cement Plant in India, the Gold Creek Power Plant in Canada, and the Heidelberger Zement AG Plant in Germany. Karellas et al. [23] conducted energy and exergy analyses and compared two different waste heat recovery systems proposed for cement plants. These two technologies were the water-steam Rankine cycle and the ORC. Results indicated that when the exhaust temperature was above 310
C, the water-steam cycle

2. SYSTEM DESCRIPTION

553

performed more efficiently than the ORC system. Results also showed that the payback period of waste heat recovery system for the cement industry made it an attractive solution. Roy et al. [24] optimized an ORC system with a low-temperature heat source, operating with different working fluid such as ammonia, R123, R12, and R124a. They developed a model to optimize and compare the system’s performance, especially exergy efficiency and irreversibility. Results showed that R123 had the best performance compared with the other fluids because it yielded higher efficiency and output power for the turbine. In a study conducted by Fergani et al. [25], an ORC system with three different organic fluids was considered to take advantage of the waste heat recovery from a cement plant. In this study, exergy, exergo-economic, and exergo-environmental analyses of the system were conducted. Results of the comparison of different fluids showed that cyclohexane and benzene were the best fluids from thermodynamic, exergo-economic, and exergo-environmental viewpoints, respectively. Multiobjective optimization was performed by considering the exergy efficiency, the cost, and the environmental impact per exergy unit of the net produced power as the objective functions. In this study, two trigeneration systems with different configurations were proposed to recover the waste heat of a cement plant. These two systems were designed to use two different cooling options to meet the demand for cooling. In this regard, an ejector cooling system and absorption chiller were considered, assessed, and compared from the thermodynamic and thermoeconomic viewpoints The exergetic coefficient of performance (COP) of the cooling technologies used in both trigeneration systems, the exergy efficiency, and the product cost rate of both trigeneration systems were selected as evaluation criteria and their sensitivity was examined by varying chosen design parameters such as the evaporator temperature and the heater temperature difference.

2. SYSTEM DESCRIPTION Figs. 1 and 2 present the layouts of two trigeneration systems that are common in all parts except for refrigeration systems. An absorption chiller is used by one and an ejector refrigeration system is used by the other. The main outputs of the presented systems are electric power, heating, and cooling using the waste heat of a cement plant as an energy source. In Fig. 1A, the electricity is generated by the superheated vapor of fluid R123 at point 3, which is heated by hot exhaust gases of the cement plant at point 1 in the vapor generator. The superheated vapor at point 3 enters the ORC turbine to generate power and the extracted vapor from the turbine enters the absorption chiller at point 4 to provide a cooling effect. The exiting stream from the chiller enters a heater at point 5 and warms the water to heat the space; then, by pumping this stream into a vapor generator, the cycle is completed. In Fig. 1B, the electricity is generated by the superheated vapor of fluid R123 at point 3, which is heated by hot exhaust gases of the cement plant at point 1 in the vapor generator. The superheated vapor at point 3 enters the ORC turbine to generate power; the extracted vapor from the turbine divides into two parts to drive the heating and cooling subsystem for the heater and the ejector refrigeration, respectively. The high-temperature stream at point 5 enters a heater and warms the water to heat the space. On the other hand, the stream at point 6 enters the ejector supersonic nozzle. The outlet stream of the ejector is mixed with the turbine outlet in mixer 1 and discharges to the condenser to be converted into subcooled liquid by expelling the heat into the cooling water. The outlet of the heater and condenser are mixed in mixer 2 and pumped into a vapor generator to absorb heat from the heat source.

554

CHAPTER 2.19 THERMODYNAMIC AND THERMOECONOMIC COMPARISONS

FIGURE 1 Layout of studied trigeneration-absorption system.

FIGURE 2 Layout of studied trigeneration-ejector system.

4. EXERGY ANALYSIS

555

3. ENERGY ANALYSIS Mass and energy need to be conserved during a process or through a system. Therefore, in this section, mass and energy balance were applied to the components of both systems to satisfy the first law of thermodynamics. By using these equations, the energy balance for each component of the systems is expressed as shown in Table 1: X X m_ ¼ m_ (1) in

out

 X   X  V2 V2 _ _ þ gz  þ gz QW ¼ m_ h þ m_ h þ 2 2 out in

(2)

4. EXERGY ANALYSIS Applicable tools for the efficient use of energy resources have improved. Exergy analysis is a method that helps engineers and designers to achieve a more efficient and thus a more sustainable system. Exergy analysis is based on mass conservation, energy principles, and the second law of thermodynamics. Unlike mass and energy, exergy is not conserved during a process or through a system, and an amount of exergy is always destroyed, which is indicates thermodynamic imperfections. To quantify the destroyed exergy, it is essential to formulate the exergy balance for each component. Determining exergy destruction leads to an identification of the location, types, and reasons for inefficiencies and solutions to improve them. By applying the second law of thermodynamics according to this equation for each component of the system, exergy destruction rates are achieved, as listed in Table 2: X X _ Qþ _ W þ Ex _ D Ex m_ e exe þ Ex (3) m_ i exi ¼ i

  T0 _ _ ExQ ¼ Q 1  T

(4)

_ W ¼ W_ Ex

(5)

Table 1 Energy Balance for Each Component of the System Components

Trigeneration-Absorption Chiller

Trigeneration-Ejector Refrigeration

Turbine Pump Heater Ejector Condenser Evaporator Vapor generator Absorption chiller

H3  H4  W_ turb ¼ 0 H6  H7 þ W_ p ¼ 0 H5  H6 þ H10  H11 ¼ 0 e e e

H3  H4  H7  W_ turb ¼ 0 H13  H17 þ W_ p ¼ 0 H5  H18 þ H19  H20 ¼ 0 H6 þ H9  H10 ¼ 0 H11  H12 þ H15  H16 ¼ 0 H8  H9 þ H25  H24 ¼ 0 H1  H2 þ H8  H3 ¼ 0 e

H1  H2 þ H7  H3 ¼ 0 H4  H5 þ Q_eva  Q_abs  Q_cond ¼ 0

556

CHAPTER 2.19 THERMODYNAMIC AND THERMOECONOMIC COMPARISONS

Table 2 Exergy Destruction Rates for Each Component of the System Components

Trigeneration-Absorption Chiller

Trigeneration-Ejector Refrigeration

Turbine Pump Heater Ejector Condenser Evaporator Vapor generator Absorption chiller

m_ 3 ðex3 ex4 Þ  W_ Turb W_ pump  m_ 6 ðex7  ex6 Þ m_ 5 ðex5  ex6 Þ  m_ 10 ðex11  ex10 Þ e e e

m_ 3 ex3 m_ 4 ex4 m_ 7 ex7 W_ Turb W_ pump1  m_ 17 ðex17  ex13 Þ m_ 5 ðex5  ex18 Þ  m_ 19 ðex20  ex19 Þ m_ 9 ex9 þ m_ 6 ex6  m_ 10 ex10 m_ 11 ðex11  ex12 Þ  m_ 15 ðex16  ex15 Þ m_ 8 ðex8  ex9 Þ  m_ 25 ðex24  ex25 Þ m_ 1 ðex1  ex2 Þ  m_ 8 ðex3  ex8 Þ e

m_ 1 ðex1  ex2 Þ  m_ 7 ðex3  ex7 Þ _ chevp m_ 4 ðex4  ex5 Þ  Ex

_ Q and Ex _ W are respectively the exergy rate related to heat transfer and power crossing the in which, Ex boundary of the control volume.

5. THERMOECONOMIC ANALYSIS Thermoeconomics is a combinational method that analyzes the cost-effectiveness of the system based on an exergy analysis; traditional economic methods lack such a sufficiency. A thermoeconomic approach reveals the correlation between the inefficiencies of the system and the capital cost that needs to be allocated, and suggests useful solutions to decrease these inefficiencies and achieve a costefficient system or process. Like mass, energy, and exergy, cost flows are required to be balanced during a process or through a system. In other words, the fuel cost rate and cost associated with capital and investment as well as operating and maintenance lead to the product’s cost. The fuel and product are related to the heat transfer, power, and mass flow rate crossing the boundary of the control volume. This statement is formulated as shown subsequently, and is applied to each component of the system. In this study, the cost balances are customized as listed in Table 3: C_Q; k þ

X

C_i; k þ Z_k ¼

X

C_e; k þ C_W; k

(6)

_ q; k C_Q; k ¼ cq; k Ex

(7)

_ W; k C_W; k ¼ cw; k Ex

(8)

_ k C_k ¼ ck Ex

(9)

_ W Here, C_W; k and C_Q; k are the cost rate associated with work and heat transfer, respectively, and Ex _ and ExQ are the exergy rates of work and heat transfer, respectively, that cross the boundary of the control volume. cw; k , cq; k , and ck are the average cost per unit of exergy. C_W; k and C_Q; k are in dollars per unit of time whereas cw; k , cq; k , and ck are in dollars  OM   CI  per unit of exergy. and operating and maintenance Z_ . The Z_k contains the cost rate of capital investment Z_ capital cost of equipment is a function of the size, construction materials, and design parameters.

5. THERMOECONOMIC ANALYSIS

557

Table 3 Cost Rate Balances for Each Component of the System Components

Trigeneration-Absorption Chiller

Trigeneration-Ejector Refrigeration

Turbine Pump Heater Ejector Condenser Evaporator Vapor generator Absorption chiller

C_3 þ Z_turb ¼ C_4 þ C_W; turb C_6 þ C_W; p þ Z_p ¼ C_7 C_5 þ C_10 þ Z_H ¼ C_6 þ C_11 e e e C_1 þ C_7 þ Z_VG ¼ C_2 þ C_3 C_4 þ Z_chiller ¼ C_5 þ C_cooling

C_3 þ Z_turb ¼ C_4 þ C_7 þ C_W; turb C_13 þ C_W; p þ Z_p ¼ C_17 C_5 þ C_19 þ Z_H ¼ C_18 þ C_20 C_6 þ C_9 þ Z_ejc ¼ C_10 C_11 þ C_15 þ Z_cond ¼ C_12 þ C_16 C_8 þ C_25 þ Z_eva ¼ C_9 þ C_24 C_1 þ C_8 þ Z_VG ¼ C_2 þ C_3 e

Considering the condenser, evaporator, heater, and vapor generator as a heat exchanger, the relations for the capital investment cost of the components are: Pump [26]: CI Zpump ¼ 3540 W_ pump

(10)

 CI      2 log10 ZTurb ¼ 2:6259 þ 1:4398 log10 W_ Turb  0:1776 log10 W_ Turb

(11)

0:71

Turbine [27]:

Heat exchanger [26]:  CI ZHE ¼ 130

AHE 0:093

0:78 (12)

Absorption chiller [28]: 0:67  CI ZChiller ¼ 11443 Q_eva

(13)

Because the capital costs for the ejector, valve mixers, and pipes are incomparable to these components, they are assumed to be zero. Since existing data for capital costs are extracted from different sources and ages, it is necessary to make them identical through the cost indices. In this study, the Chemical Engineering Plant Cost Index is used to bring the investment costs up to date. CI OM Z_ and Z_ are calculated by dividing the annual amount of capital cost and operating and maintenance cost per unit of working hours (hours or seconds) of a system. In this study, by multiplying the capital investment by the capital recovery factor and maintenance factor, capital investment is converted into the annualized investment cost using the equations: Z_k ¼ ZkCI  CRF  4=t CRF ¼

ið1 þ iÞN ð1 þ iÞN  1

(14) (15)

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CHAPTER 2.19 THERMODYNAMIC AND THERMOECONOMIC COMPARISONS

in which (4) is the maintenance factor, (i) is the interest rate, (t) is the working hours of the system per year, and (N) is the system lifetime. The variable C_ expresses the cost rates related to the stream of matter, power, and heat transfer whereas Z_ is associated with all remaining costs (monetary costs). To determine the cost rate flow in the system, we apply a seven-step approach: 1. calculate the thermodynamic properties of the states, such as pressure, temperature, enthalpy, entropy, and exergy with the aid of mass, energy, and exergy balance 2. formulate the cost balance for every component of the system 3. calculate the investment costs of the components using Eqs. (10)e(13) 4. annualize the investment costs by dividing them by the working hours of a system per year 5. make the base year of the calculated costs common by applying economic indices 6. Auxiliary equations are needed if there is more than one unknown output of the cost balance, to supplement the equations. 7. By balancing the number of unknown variables and equations, the matrix of the equations is made to start solving. For example, for equipment, if there is n exergy stream leaving this component, it is required to formulate n  1 auxiliary equations.

5.1 THERMOECONOMIC EVALUATION The following thermoeconomic variables are the main tools to evaluate the cost efficiency of a component and optimize the performance of a thermal system.

5.1.1 Average Cost of Fuel The average unit cost of the fuel ðcF Þ of the component is introduced as: cF ¼

C_F E_F

(16)

This equation expresses the average cost at which each exergy unit of fuel is generated from the component.

5.1.2 Average Cost of Product The average unit cost of the fuel ðcP Þ of the component is introduced as: cP ¼

C_P E_P

(17)

This equation expresses the average cost at which each exergy unit of fuel is supplied to the component.

5.1.3 Cost Rate of Exergy Destruction  

The cost related to exergy destruction C_D is a hidden cost that can be revealed solely by thermoeconomic analysis. The cost associated with exergy destruction in a component or process is defined as: _ D C_D ¼ cF Ex

(18)

6. RESULTS AND DISCUSSION

559

5.1.4 Cost Rate of Exergy Loss When there is waste owing to mass rejection or heat transfer from a system to its surroundings, exergy is lost. Then the monetary loss associated with the exergy loss must be calculated within the overall system as: _ L C_L ¼ cF Ex

(19)

5.1.5 Relative Cost Difference Relative cost difference (r) expresses the relative increase between the average cost of the product and the average cost of fuel. It can be stated as: cP  cF r¼ (20) cF The source of this increase is exergy-related and noneexergy related costs. In some cases, the relative cost difference can be considered an objective function in the optimization of the thermal system. In other words, in each iteration of the optimization, the relative cost difference must be lower than the first iteration.

5.1.6 Thermoeconomic Factor To assess the performance of the system, it necessary to identify the contribution of exergy-related and noneexergy related costs. This is facilitated by the thermoeconomic factor ( f ) and is formulated as: f ¼

Z_  _ L þ Ex _ D Z_ þ cF Ex 

(21)

A low value of thermoeconomic factor for a component suggests that it is possible to replace the component with higher quality (a higher price) and, as a result, a lower exergy destruction rate to have a more cost-efficient system. Similarly, a high value of thermoeconomic factor for a component suggests a decrease in the investment costs of this component at the expense of its exergetic efficiency.

6. RESULTS AND DISCUSSION Thermodynamic and thermoeconomic analyses of two trigeneration systems were performed through Engineering Equation Solver (EES) software. These systems used the waste heat of exhaust gas from a cement plant. The working fluid in both systems was assumed to be R123 because of its thermodynamic and environmental properties [8]. LiBreH2O was considered to be a medium in the absorption chiller. Assumptions for simplifying thermodynamic and thermoeconomic modeling are that: 1. The system is operated in steady state and pressure drops are neglected in the pipelines and heat exchangers. 2. The flow process across the throttle valve is isenthalpic. 3. The condenser outlet state is assumed to be a saturated liquid and the outlet state of the evaporator is assumed to be a saturated vapor. 4. The isentropic efficiencies of the pumps and turbine are known.

560

CHAPTER 2.19 THERMODYNAMIC AND THERMOECONOMIC COMPARISONS

5. All of the potential and kinetic energies are neglected. 6. The cost related to exergy loss is neglected. 7. A zero-unit cost is assumed for exhaust gases entering the vapor generator and cooling water entering the condenser. Some inputs parameters for modeling the system are listed in Table 4. By using the equations in the previous sections and the parameters in Table 4, the exergy destruction rates and investment cost rates were calculated for each component and overall for the two systems. The overall thermodynamic and thermoeconomic performance of the two systems is provided in Table 5 and the parameters are discussed and compared. As listed in Table 5, a comparison of two different trigeneration systems for a predefined amount of energy and exergy source (in this case, waste heat from a cement plant) led to the following considerations. Table 5 shows that the trigeneration-ejector system provided 167 kW electricity more than the trigeneration-absorption system. On the other hand, the trigeneration-absorption system had 3281 and 1774 kW heating and cooling capacity, respectively, more than the trigeneration-ejector system. Compared from exergy point of view, the two systems had the same performance (both exergy efficiency and exergetic COP) because of the interchange of heating and cooling at the same temperature, and thus the same difference in the dead-state temperature in both systems. Compared from an economic point of view, the trigeneration-absorption system had the higher investment cost rate because components with a higher capacity were used. By considering the zero amount for the cost of fuel for both systems, the product cost rate for the trigeneration-absorption system was more than the trigeneration-ejector system. Therefore, when a source of waste heat is available, the selection of a trigeneration system involves selecting between two systems with different configurations. In fact, this process is mostly carried out based on the results of modeling and the importance of each parameter (efficiency and cost) for the decision maker. By selecting the trigeneration-absorption system compared with the trigeneration-ejector system, more cooling and heating capacity is gained, which leads to a higher product cost rate. Fig. 3 represents the exergy destruction rates for the components of the two trigeneration systems that were studied. As is shown, the total exergy destruction rate for the trigeneration-absorption system was more than for the trigeneration-ejector system. The turbine and heater of the trigeneration-absorption system contributed more to the exergy destruction rate compared with the trigeneration-ejector system, whereas the exergy destruction rates for the vapor generator were the same for both systems.

Table 4 Input Data for the Modeling of Two Trigeneration Systems Parameter Dead state temperature (
C) Dead state pressure (kPa) Cement plant flue gas temperature (
C) Cement plant flue gas pressure (kPa) Cement plant flue gas mass flow rate (kg/s) Turbine inlet pressure (kPa) Evaporator temperature (
C)

15 101.3 150 101.3 867 1700 10

6. RESULTS AND DISCUSSION

561

Table 5 Thermodynamic and Thermoeconomic Analysis Results

Total energy input (kW) Total exergy input (kW) Electricity output (kW) Heating output (kW) Cooling output (kW) Exergy of electricity output (kW) Exergy of heating output (kW) Exergy of cooling output (kW) Exergy destruction rate (kW) Energy efficiency (%) Exergy efficiency (%) Energetic COP Exergetic COP Investment cost rate ($/h) Product cost rate ($/h)

Trigeneration-Absorption Chiller

Trigeneration-Ejector Refrigeration

10,470 3,284 1,042 5,060 3,238 1,042 507.2 30.79 1,783 89 48.12 0.75 0.04 103.7 103.7

10,470 3,284 1,209 1,779 1,464 1,209 215.7 13.31 1,493 42.51 42.61 0.42 0.04 39.5 39.5

COP, coefficient of performance.

To observe the effect of important variables on the technical and economic performance of the system, a parametric study was conducted. In this section, the evaporator temperature and heater temperature were selected to investigate variations in their performance on the two trigeneration systems.

Exergy destrucon rate (kW)

1800 1600 1400 1200 1000 800

trig-ejc

600

trig-abs

400 200 0 Vapor Generator

Heater

Turbine

Total

FIGURE 3 Exergy destruction rates for common components of the trigeneration-absorption (trig-abs) and trigenerationejector (trig-ejc) system.

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CHAPTER 2.19 THERMODYNAMIC AND THERMOECONOMIC COMPARISONS

Exergec COP

0.09 trig-ejc

0.07

trig-abs

0.05 0.03 0.01

8

9

10

11

12

13

Evaporator temperature (°C) FIGURE 4 Exergetic coefficient of performance (COP) changes with variation of evaporator temperature in trigenerationejector (trig-ejc) and trigeneration-absorption (trig-abs) systems.

As shown in Fig. 4, by increasing the evaporator temperature, the exergetic COP of the both system increased. By increasing the evaporator temperature of the absorption chiller, the cooling exergy of the evaporator increased and the power consumed by the chiller pump decreased; as a result, the exergetic COP of the trigeneration-absorption system increased. The increase in exergetic COP of the trigeneration-ejector system resulted from the increase in the cooling exergy of the evaporator whereas the amount of exergy fed to the ejector was constant. As shown in Fig. 5, by the increasing heater temperature difference, the exergetic COP of the trigeneration-ejector system decreased and the exergetic COP of the trigeneration-absorption system remained constant. In the trigeneration-ejector system, increasing the heater temperature difference led to an increase in the amount of exergy fed to the ejector whereas the output exergy was constant; therefore, exergetic COP decreased. In the trigeneration-absorption system, input exergy to the chiller generator and chiller pump and output exergy of the chiller evaporator were independent of variations in the heater temperature difference; thus, the exergetic COP of the trigeneration-absorption system was fixed because of these variations.

Exergec COP

0.09 trig-ejc

0.07

trig-abs

0.05 0.03 0.01 5

10

15

20

25

Heater temperature difference (°C) FIGURE 5 Exergetic coefficient of performance (COP) changes with variations in heater temperature difference in trigeneration-ejector (trig-ejc) and trigeneration-absorption (trig-abs) systems.

Exergy efficiency (%)

6. RESULTS AND DISCUSSION

50.5 50 49.5 49 48.5 48 47.5 47

trig-ejc

8

9

563

trig-abs

10

11

12

13

Evaporator temperature (°C) FIGURE 6 Exergy efficiency changes with variations in evaporator temperature in trigeneration-ejector (trig-ejc) and trigeneration-absorption (trig-abs) systems.

Exergy efficiency (%)

Fig. 6 illustrates the effect of the evaporator temperature on the exergy efficiency of both systems. The exergy efficiency of the trigeneration-absorption system improved by increasing the evaporator temperature. This increase occurred because of an increase in the cooling exergy of the chiller evaporator, whereas the heating exergy of the heater, electric power, and total input exergy to the system were constant. In the same way, the exergy efficiency of the trigeneration-ejector system increased by increasing the evaporator temperature. This resulted from an increase in the cooling exergy and a decrease in electric power generated by the system, whereas the total input exergy to the system was fixed. Fig. 7 presents the effects of the heater temperature difference on the exergy efficiency of both systems. The exergy efficiency of the trigeneration-ejector system decreased by increasing the heater temperature difference. When the heater temperature difference increased, the heating exergy generated by the heater decreased whereas the cooling exergy, electric power, and total input exergy to the system were constant; as a result, the exergy efficiency of the trigeneration-ejector system decreased. Fig. 7 shows that the exergy efficiency of the trigeneration-absorption system decreased by

52 trig-ejc

51

trig-abs

50 49 48 47 46 5

10

15

20

25

Heater temperature difference (°C) FIGURE 7 Exergy efficiency changes with variations in heater temperature difference in trigeneration-ejector (trig-ejc) and trigeneration-absorption (trig-abs) systems.

CHAPTER 2.19 THERMODYNAMIC AND THERMOECONOMIC COMPARISONS

Product cost rate ($/h)

564

110 90 trig-ejc

70

trig-abs

50 30 8

9

10

11

12

13

Evaporator temperature (°C) FIGURE 8 Product cost rate changes with variations in evaporator temperature in trigeneration-ejector (trig-ejc) and trigeneration-absorption (trig-abs) systems.

increasing the heater temperature difference. The increase in the heater temperature difference resulted in a decrease in heating exergy generated by the heater, whereas the cooling exergy, electric power, and total input exergy to the system were fixed. Fig. 8 presents the effects of the evaporator temperature on the product cost rate of both systems. The product cost rate of the trigeneration-absorption system increased by 0.2% because of an increase in the product exergy of the absorption chiller, whereas the product exergy of the heater and electric power were independent of this variation. The product cost rate of the trigeneration-ejector system decreased by 3% when the evaporator temperature varied between 8
C and 13
C. This decrease resulted from a decrease in the product exergy of evaporator 1 and electric power. As Fig. 9 demonstrates, by increasing the heater temperature difference, the product cost rates of the trigeneration-absorption and trigeneration-ejector systems decreased by 2.5% and increased by 0.6%, respectively. In the trigeneration-absorption system, by varying the heater temperature

Product cost rate ($/h)

110 trig-ejc

90

trig-abs

70 50 30 5

10

15

20

25

Heater temperature difference (°C)

FIGURE 9 Product cost rate changes with variations in heater temperature difference in trigeneration-ejector (trig-ejc) and trigeneration-absorption (trig-abs) systems.

NOMENCLATURE

565

difference, the product exergy of the heater decreased and the product exergy of the chiller evaporator and electric power did not change. In the trigeneration-ejector system, the product exergy of the heater increased whereas the electric power and product exergy of evaporator 1 remained constant.

7. CONCLUSIONS In this study, two trigeneration systems with different configurations for recovering the waste heat of a cement plant with the purpose of producing electricity, heating, and cooling power were studied. Two systems were analyzed, evaluated, and compared thermodynamically and thermoeconomically. For a better comparison, an identical amount of waste heat was considered as an energy source for both systems. The analysis was performed using EES software. The results showed that 89% and 48% of energy and exergy efficiency, respectively, for the trigeneration-absorption system and 61% and 50%, respectively, for the trigeneration-ejector system were achieved. The results of the thermoeconomic analysis indicated that the product cost rate was $103.7/h and $40.9/h, respectively, for the trigeneration-absorption and trigeneration-ejector systems.

NOMENCLATURE abs C_ ejc ex Ex_ 4 i

m_ N

t

trig Z

Z_

Absorption chiller Cost rate ($/h) Ejector Specific exergy (kJ/kg) Exergy (kW) Maintenance factor Interest rate Mass flow rate (kg/s) Component lifetime (year) Operating hours (h) Trigeneration Investment cost ($) Investment cost rate ($/h)

Subscripts chevp D e F i k L P Q_ Turb W_

Chiller evaporator Destruction Exit Fuel Inlet Component Loss Product Heat transfer Turbine Power

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CHAPTER 2.19 THERMODYNAMIC AND THERMOECONOMIC COMPARISONS

Superscripts CI OM

Capital investment Operating and maintenance

Abbreviation COP EES ORC

Coefficient of performance Engineering equation solver Organic Rankine cycle

REFERENCES [1] Zhai H, et al. Energy and exergy analyses on a novel hybrid solar heating, cooling and power generation system for remote areas. Applied Energy 2009;86(9):1395e404. [2] Wang J, et al. A new combined cooling, heating and power system driven by solar energy. Renewable Energy 2009;34(12):2780e8. [3] Al-Sulaiman FA, Dincer I, Hamdullahpur F. Exergy modeling of a new solar driven trigeneration system. Solar Energy 2011;85(9):2228e43. [4] Wang J, et al. Parametric analysis of a new combined cooling, heating and power system with transcritical CO2 driven by solar energy. Applied Energy 2012;94(0):58e64. [5] Ahmadi P, Dincer I, Rosen MA. Exergo-environmental analysis of an integrated organic rankine cycle for trigeneration. Energy Conversion and Management 2012;64(0):447e53. [6] Al-Sulaiman FA, Dincer I, Hamdullahpur F. Energy and exergy analyses of a biomass trigeneration system using an organic rankine cycle. Energy 2012;45(1):975e85. [7] Tippawan P, Arpornwichanop A, Dincer I. Energy and exergy analyses of an ethanol-fueled solid oxide fuel cell for a trigeneration system. Energy 2015;87:228e39. [8] Boyaghchi FA, Heidarnejad P. Thermodynamic analysis and optimisation of a solar combined cooling, heating and power system for a domestic application. International Journal of Exergy 2015;16(2):139e68. [9] Noorpoor AR, Heidararabi S, Heidarnejad P. Dynamic modeling, exergy assessment and optimization of a novel solar-driven trigeneration system. International Journal of Exergy 2016;20(4). [10] Ahmadi P, Dincer I, Rosen MA. Thermodynamic modeling and multi-objective evolutionary-based optimization of a new multigeneration energy system. Energy Conversion and Management 2013;76:282e300. [11] Ahmadi P, Dincer I, Rosen MA. Development and assessment of an integrated biomass-based multigeneration energy system. Energy 2013;56:155e66. [12] Ahmadi P, Dincer I, Rosen MA. Multi-objective optimization of a novel solar-based multigeneration energy system. Solar Energy 2014;108:576e91. [13] Ahmadi P, Rosen MA, Dincer I. Multi-objective exergy-based optimization of a polygeneration energy system using an evolutionary algorithm. Energy 2012;46(1):21e31. [14] Noorpoor A, Heidararabi S, Heidarnejad P. Dynamic modelling, exergy assessment and optimisation of a novel solar-driven trigeneration system. International Journal of Exergy 2016;20(4):405e44. [15] Boyaghchi FA, Heidarnejad P. Thermoeconomic assessment and multi objective optimization of a solar micro CCHP based on organic rankine cycle for domestic application. Energy Conversion and Management 2015;97:224e34. [16] Boyaghchi F, Heidarnejad P. Energy and exergy analysis and optimization of a-solar-driven combined ejector-cooling and power system based on organic Rankine cycle using an evolutionary algorithm. Scientia Iranica 2015;22(1).

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[17] Boyaghchi F, Heidarnejad P. Energy and exergy analysis and optimization of a m-solar-driven combined ejector-cooling and power system based on organic Rankine cycle using an evolutionary algorithm. Scientia Iranica Transaction B, Mechanical Engineering 2015;22(1):245. [18] Hands S, et al. Performance analysis & energy benefits of a desiccant based solar assisted trigeneration system in a building. Renewable Energy 2016;85:865e79. [19] Elmer T, et al. Experimental evaluation of a liquid desiccant air conditioning system for tri-generation/wasteheat-driven applications. International Journal of Low-Carbon Technologies 2016;11(12):1e16. [20] Wu DW, Wang RZ. Combined cooling, heating and power: a review. Progress in Energy and Combustion Science 2006;32(5e6):459e95. [21] Bronicki LY. Organic Rankine cycle power plant for waste heat recovery. 1999. [22] Bronicki LY. Organic rankine cycle power plant for waste heat recovery. Blueprint for the Clean, Sustainable Energy Age. Israel: UNESCO; 2000. p. 302. [23] Karellas S, et al. Energetic and exergetic analysis of waste heat recovery systems in the cement industry. Energy 2013;58:147e56. [24] Roy J, Mishra M, Misra A. Performance analysis of an organic rankine cycle with superheating under different heat source temperature conditions. Applied Energy 2011;88(9):2995e3004. [25] Fergani Z, Touil D, Morosuk T. Multi-criteria exergy based optimization of an organic rankine cycle for waste heat recovery in the cement industry. Energy Conversion and Management 2016;112:81e90. [26] Mohammadkhani F, et al. Exergoeconomic assessment and parametric study of a gas turbine-modular helium reactor combined with two organic rankine cycles. Energy 2014;65(0):533e43. [27] El-Emam RS, Dincer I. Exergy and exergoeconomic analyses and optimization of geothermal organic rankine cycle. Applied Thermal Engineering 2013;59(1):435e44. [28] Lian Z, Chua K, Chou S. A thermoeconomic analysis of biomass energy for trigeneration. Applied Energy 2010;87(1):84e95.

CHAPTER

COMPARATIVE EVALUATION OF POSSIBLE DESALINATION OPTIONS WITH VARIOUS NUCLEAR POWER PLANTS

2.20 Selim Dincer1, Ibrahim Dincer2, 3

1

Bogazici University, Istanbul, Turkey ; UOIT, Oshawa, ON, Canada2; YTU, Istanbul, Turkey3

1. INTRODUCTION The future of the world’s limited natural resources is a major global concerns. The freshwater shortage is only one example, but it is of vital importance to humans. Although 70% of the world’s surface is covered by water, only 2.5% of world’s water resources are fresh water. Up to 68.8% of the total fresh water is trapped in glaciers, 30% of it is ground water, and the rest is located in lakes, the atmosphere, rivers, soil moisture, and wetlands [1]. Another important factor that poses a threat to freshwater resources is a dramatic increase in the population. As the Center for Strategic and International Studies warned, a population growth rate of slightly over 1% might cause problems for infrastructure and freshwater resources. That study also stated that the most Middle Eastern countries were soon expected to have a 3% population growth rate, which in turn would increase water demands in an amount that could no longer be supplied by natural resources [2]. Therefore sustainable and environmentally friendly methods should be developed to produce fresh water. Desalination can be considered a clean technology that can meet the need for fresh water. Desalination is an available process to produce fresh water by removing salt and other minerals from seawater. The types of desalination systems are divided into two main groups: thermal distillation and membrane. Thermal distillation processes include multieffect distillation (MED) and multistage flash (MSF), in which seawater is heated and gradually condensed to remove undesirable particles from water. Membrane-type desalination processes such as reverse osmosis (RO) and electrodialysis use a semipermeable membrane to filter dissolved solids. Fig. 1 shows the distribution of global desalination capacity in terms of the technology used [3]. The main requirement of desalination processes is energy. Energy is needed in the form of heat, electricity, or both, depending on the desalination method. Thermal distillation technologies mainly require energy in the form of heat and a relatively small amount of electricity whereas membrane-type systems use only electricity for desalination [4]. Most existing desalination plants use fossil fuels as an energy source. The combustion Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00032-9 Copyright © 2018 Elsevier Inc. All rights reserved.

569

570

CHAPTER 2.20 COMPARATIVE EVALUATION OF POSSIBLE DESALINATION OPTIONS

MED

MSF

3%

MED 2%

ED

Other

Hybrid

1%

8%

23% 63%

FIGURE 1 Distribution of global desalination capacity in terms of technology used. ED, electrodialysis; MED, multieffect distillation; MSF, multistage flash.

of fossil fuels increases the emission of greenhouse gases, which is closely related to changes in the global climate [5]. Changes in the global climate mean a rise in the earth’s temperature stemming from increasing concentrations of carbon dioxide and other greenhouse gases. Increasing temperatures cause a rise in the sea level, which in turn results in the flooding of coastal settlements, changes in fertile zones, and other outcomes that could endanger populations [6]. Therefore, alternative carbon emission-free systems such as renewable energy sources and nuclear power plants (NPPs) to produce electricity instead of fossil fuels, which have a larger amount of carbon dioxide emissions, are gaining importance. Because nuclear energy is also a promising technology for nonelectrical applications, the number of studies on using nuclear energy for desalination, hydrogen production, and the process of heat applications is continuously increasing [7e11]. An NPP has enough waste heat and electricity to meet the requirements of the desalination process. Therefore nuclear-based desalination is a sustainable and environmentally friendly alternative to using fossil fuel as an energy source of desalination. Fig. 2 shows the electricity, heat, and freshwater flows between a nuclear reactor, a desalination system, and a customer. In this study, a cost assessment of various nuclear-based desalination systems is performed using the Desalination Economic Evaluation Program (DEEP) software package developed by the International Atomic Energy Agency (IAEA). A comparative cost assessment is conducted of possible scenarios. Steam, gas, and combined (steam and gas) cycle-based NPPs are considered as energy sources of the system. In the desalination part of the assessment, MSF, MED, RO, and hybrid systems (RO plus MED, and RO plus MSF) are compared.

2. DESALINATION METHODS Humankind has been practicing water desalination worldwide since the fourth century, when Greek sailors employed an evaporative process for desalination, especially seawater and brackish water. Since then, it has always been a hot topic in a discussion of the essential need for daily water in various

2. DESALINATION METHODS

571

FIGURE 2 The flowchart of nuclear-based desalination.

communities. It is still a critical topic for many countries, including the US and countries in the Gulf, the Far East, and Africa, where desalination is a significant process to produce fresh water to meet needs. Desalination technologies have advanced for various types of salty and brackish waters. In desalination applications various methods are commonly used for freshwater production, such as thermal (including MSF evaporation, MED, and vapor compression) and membrane (RO and electrodialysis). Here, we consider only three methods as briefly described subsequently. 1. Multieffect Distillation An MED plant consists of multiple stages or effects with a horizontal tube thin film configuration evaporator. In the first stage of an MED plant, seawater is sprayed onto the outer surface of the tubes carrying hot steam from an NPP. The feed seawater is heated and boiled while the hot steam is condensed during the process. The condensate water is recycled by an intermediate loop for repeated use. A certain amount of the feed water is evaporated in the first chamber; the remaining portion is transferred to the second stage. The seawater steam produced in the first chamber is passed through the tubes in the second effect and used as a heat source to evaporate the remaining seawater. Because the pressures of the chamber and the pipes are different, the seawater can be evaporated at the same temperature while the hot steam flowing in the pipe is condensed. The same process is repeated from effect to effect at lower temperature and pressure values. The final vapor is condensed by preheating the feed water at the last chamber [3]. 2. Multistage Flash MSF is the most common and simple thermal desalination process. In an MSF plant, feed seawater flows in the finned tubes from the last to the first stage. The temperature of the seawater is raised

572

CHAPTER 2.20 COMPARATIVE EVALUATION OF POSSIBLE DESALINATION OPTIONS

progressively in each stage, and the final heating takes place in a brine heater where heat is transferred from hot steam, which comes from an NPP as waste heat, to seawater. Afterward, heated seawater flows into the first stage. Because the pressure of the first stage is decreased by a vacuum pump, hot water first evaporates and then condenses onto the outer surface of the finned tubes. In other words, while the hot water is condensed, the cold water flowing in the opposite direction through the finned tubes is heated. Only a small amount of heated seawater can be condensed in the first stage, so the rest is transferred to the second stage, which has a lower pressure than the first one. This process is repeated in each following stage at progressively lower pressures. A typical MSF plant consists of 4e40 stages [3,12]. 3. Reverse Osmosis When the two solutions at different concentrations are separated by a semipermeable membrane, osmotic pressure causes the solvent to flow from the lower concentration to the higher concentration side. If an external pressure that is higher than the osmotic pressure is applied on the concentrated side, the solvent flows in the reverse direction. This process is called RO. In a membrane-type desalination plant, RO is achieved by pressurizing the feed seawater by pumps. The high-pressure feed seawater is passed through the semipermeable membrane, and eventually freshwater is obtained [13].

3. COST ASSESSMENT DEEP is a software package developed by IAEA to evaluate the cost of a specific desalination plant and compare the possible scenarios of desalination options. The software can be used to estimate the cost of freshwater production from five desalination options (two thermal, one membrane, and two hybrids) combined with 10 types of power plants (five fossil fuel, four nuclear, and one renewable) (Table 1) [7]. The input parameters required for DEEP can be divided into three main groups: user input data, technical parameters, and cost parameters. User input parameters including the desalination method, power plant type, capacity of both the power plant and desalination system, interest rate, discount rate, fuel escalation, and feed water salinity are determined according to the case to be worked on by the user. Technical parameters, the second group of input parameters, depend on the technology used in the processes. Efficiencies and temperature ranges are examples of technical parameters. Cost parameters include the specific cost of main parts such as fuel, construction, and operation and maintenance; and operational parameters such as the lifetime of the power plant and desalination system, availability, etc. DEEP calculates the energy production cost of the power plant and the water production cost of desalination parts considering specific cost elements, as shown in Fig. 3. The capital cost includes construction, initial investment, decommissioning, and interest during construction. The second cost component is the operating cost. The operating cost of the power plant consists of three main parts: the fuel cost, the operation and maintenance cost, and the carbon tax. When the operating cost of desalination is calculated, the energy cost is used instead of the fuel cost and the carbon tax is not included. Cost calculations are done in two steps. The first step is to calculate the energy production cost; then this cost is used to calculate the energy cost of the desalination system. The levelized cost of water production is calculated in the second step by combining the energy cost with other capital expenses and the operation and maintenance cost.

3. COST ASSESSMENT

Table 1 Power and Desalination Plants in Desalination Economic Evaluation Program Energy Source COAL OIL GT CC FH RH NSC NBC NCC NH

Steam cycle: coal Steam cycle: oil Gas turbine Combined cycle Fossil heat (boiler) Renewable heat Nuclear steam turbine Nuclear gas turbine Nuclear combined cycle Nuclear heat

Desalination MED MSF RO MED þ RO MSF þ RO

Multieffect distillation Multistage flash Reverse osmosis hybrid hybrid

FIGURE 3 Desalination Economic Evaluation Program main cost parameters.

573

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CHAPTER 2.20 COMPARATIVE EVALUATION OF POSSIBLE DESALINATION OPTIONS

4. SYSTEM DESCRIPTION In this study, 15 possible scenarios were obtained by integrating steam, gas, and a combined cycle (CC)-based NPP with each desalination method. Table 2 shows the nuclear reactor type and desalination method considered for each case. Nuclear power plants with a thermal power of 2000 MW are used as the energy source and the electricity output of each plant is evaluated according to its efficiency. In desalination, the salinity of the feed water and the desalination capacity of each process is 35,000 parts per million and 100,000 m/min, respectively. In hybrid desalination, the capacities of the thermal and membrane types are the same (50,000 m3/min for each). The salinity of the output water, required thermal energy, and electricity depend only on the desalination method used. Membrane-type desalination uses only electricity to produce fresh water, so in cases 3, 8, and 13, in which RO is used as the desalination method, the thermal requirement for desalination is zero. Thermal-type desalination processes essentially require heat to generate fresh water and a relatively small amount of electricity is needed to maintain the pressure difference between stages or chambers during the process. The thermal power and electricity requirements of each scenario studied were calculated as shown in Table 2. Fig. 4 shows the layout of case 14, the main power plant and desalination facilities and their input/ output values. In case 14, the integration of a CC-based NPP with a hybrid desalination system consisting of RO and MED was investigated. Combined cycleebased NPPs consist of a gas turbine, heat recovery steam generator, turbine, condenser, and pump. First, a specific amount of electricity is generated and supplied to the grid from the gas cycle (GC) with 2000 MW power. Hot gas at the turbine outlet is used to evaporate the water flow in a steam cycle (SC) by employing the heat recovery steam generator at 130 C. The produced steam is used in turbines to generate electricity. Water at 78 C coming from the first outlet of the turbine is used in the intermediate loop to provide the heat energy required for MED. The remaining water flows from the turbine’s second outlet to the condenser where the temperature of the water is decreased. The water is then pumped back to the heat recovery steam generator and the cycle is completed successfully. A portion of the generated electricity is supplied to the desalination plant to be used in both RO and MED. After determining the nuclear-based desalination options to be compared, the user input parameters, technical parameters, and cost parameters must be determined to calculate the hydrogen production cost using the DEEP software. User input parameters including financial parameters such as the discount rate, tax rate, interest rate, and fuel escalation are determined, as shown in Table 3. The default parameters provided by DEEP are used for technical and cost parameters. The default operation, performance, and cost data for both nuclear reactors and desalination methods are shown in Tables 4 and 5, respectively [11].

5. RESULTS AND DISCUSSION In this study, a comparative cost estimation is performed of various nuclear-based desalination processes using the DEEP software package. In each case, the total capital, specific capital, and annual operating costs of the NPP and desalination plant are calculated using the user-provided financial parameters and the default performance and cost parameters provided by DEEP, as shown in Table 6. Because the CC includes gas turbines, heat recovery steam generators, and steam turbines, the total

Table 2 Description of Studied Scenarios Cases 1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

Nuclear power plant (NPP) Nuclear power plant type Thermal power (MW thermal) Electricity output (MW electric)

Steam cycleebased NPP 2000

Gas cycleebased NPP 2000

Combined cycleebased NPP 2000

660 (33%)

840 (42%)

1060 (53%)

Desalination Desalination type

MED

MSF

Desalination capacity (mA3/d) Feed water salinity (ppm) Output water salinity (ppm) Required thermal power (MW thermal) Required electricity (MW electric)

RO

MED þ RO

MSF þ RO

MED

MSF

RO

MED þ RO

MSF þ RO

MED

MSF

RO

100,000

100,000

100,000

35,000

35,000

35,000

MED þ RO

MSF þ RO

25

25

199

117

117

25

25

199

117

117

25

25

199

117

117

240

280

e

120

140

240

280

e

120

140

240

280

e

120

140

6.8

12.2

14

10.4

13.1

6.8

12.2

14

10.4

13.1

6.8

12.2

14

10.4

13.1

MED, multieffect distillation; MSF, multistage flash; ppm, parts per million; RO, reverse osmosis.

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CHAPTER 2.20 COMPARATIVE EVALUATION OF POSSIBLE DESALINATION OPTIONS

FIGURE 4 Flow diagram of combined cycle with hybrid desalination system (screenshot from Desalination Economic Evaluation Program). MWe, megawatt electric; MWt, megawatt thermal.

Table 3 Financial Parameters Considered in Study Discount rate Inflation rate Interest rate Tax rate Equity: Debt Loan duration Depreciation period Power selling price Fuel escalation

5% 5% 4% 20% 60%:40% 20 years 20 years $120/MW hours 3%

capital cost of the CC-based NPP is greater than the total capital cost of the SC- and GC-based NPPs. The annual operating cost also shows the same trend, so the annual operating cost of the CC-based NPP has the highest value compared with the GC and SC. As can be seen from the comparison of RO with MED, thermal desalination processes require a relatively higher total capital cost. The annual operating cost of desalination depends not only on the desalination method used but also on the type of nuclear reactor, because the cost of electricity and heat from the reactor depends on the type of reactor.

5. RESULTS AND DISCUSSION

577

Table 4 Default Parameters of Nuclear Reactor Types Units

Steam Cycle

Gas Cycle

Combined Cycle

Month Year % % kg/kW hours

60 60 90 32% 0.029

60 40 90 42% 0.029

24 40 90 55% 0.029

$/kW (electrical or thermal) e $/MW hour (electrical or thermal) $/billion barrel $/MWh (electrical or thermal) %

4000

3500

4000

1 5.9

1 6

1 4.5

1.9 8.8

2.5 12

2.5 12

10%

10&

10%

%

0

0

0

%

15%

15%

15%

Operation and Performance Data Construction lead time Lifetime of energy plant Operating availability Technology efficiency Specific CO2 emissions Cost Data Specific construction cost Construction cost scale Specific fuel cost Primary fuel price Specific operations and maintenance cost Additional site-related cost factor Energy plant contingency factor Nuclear plant decommissioning cost factor

The cost of freshwater production for each of the 15 possible nuclear-based desalination options is presented in Fig. 5. The cost to produce fresh water consists of four main parts: overnight capital costs, other capital expenses, energy costs, and operation and maintenance costs. Overnight capital costs, other capital expenses, and operating and maintenance costs mainly depend on the type of desalination. This can be seen by comparing cases 1, 6, and 11, in which the same desalination method is integrated with different types of nuclear reactors. The contribution of overnight capital costs to the unit cost of water production is higher than the other capital expenses and the operating and maintenance costs. Thermal desalination processes such as MED and MSF have more overnight capital costs and other capital expenses than does membrane-type desalination for water production. On the other hand, the highest value of operation and maintenance costs is observed for RO. Fig. 6 compares overnight capital costs, other capital expenses, and operation and maintenance costs, depending on possible desalination processes. The difference between the unit cost of freshwater production is mainly the result of the cost of energy. The energy cost depends both on the type of NPP and the desalination technique used in the system, because the nuclear reactor type has an important role in determining the energy production cost and the desalination method affects the amount of energy to be used. For this reason, the change in the cost of energy with respect to the method of desalination and type of nuclear reactor was examined, as shown in Fig. 7.

578

CHAPTER 2.20 COMPARATIVE EVALUATION OF POSSIBLE DESALINATION OPTIONS

Table 5 Default Parameters of Desalination Methods Units

MED

Multistage Flash

RO

Month Year Year % Number Number

12 20 20 90% 3 23

12 20 20 90% 3 23

12 20 e 90% 3 23

$/(m3/d) $/MW (thermal) $/billion barrel $/kW hour $ $ $/m3 $/m3 $/m3

900 55,000 20 0.06 66,000 29,700 0.03 0.01 0.03

1000 55,000 20 0.06 66,000 29,700 0.03 e 0.03

900 e e 0.06 66,000 29,700 0.04 e 0.03

$/m3

0.02

0.02

0.01

$/m3

e

e

0.07

% % % %

1 7% 5% 10%

1 10% 5% 10%

1 7% 5% 10%

%

0.5%

0.5%

0.5%

Operation and Performance Data Water plant lead time Lifetime of water plant Lifetime of backup heat Water plant operating availability Management personnel Labor personnel Cost Data Base unit cost Backup heat source Fossil fuel price for backup heat Purchased power cost Management salary Labor salary Specific O&M spare part cost Tubing replacement cost (MED) Specific O&M chemical cost for pretreatment Specific O&M chemical cost for posttreatment O&M membrane replacement cost (RO) Unit size correction factor In/outfall-specific cost factor Water plant owner cost factor Water plant cost contingency factor Water plant O&M insurance cost

MED, multieffect distillation; O&M, operation and maintenance; RO, reverse osmosis.

Integrating any desalination system with a GC-based NPP is a more economical way to produce fresh water than integrating with a steam or CC-based NPP. Because the unit cost of electricity generated in a GC-based NPP is lower than for the other types, the cost of energy required for desalination in GC-based nuclear reactors is also lower. This can be seen by comparing the energy costs of desalination options with respect to the types of nuclear reactors used, as shown in Fig. 7. Although the application of RO in SCs and CCs provides a lower unit cost for water production, the integration of MED with a GC-based NPP is the most economical method.

Table 6 Cost Values of Desalination System and Nuclear Power Plant Cases 1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

Nuclear Power Plant (NPP) Nuclear power plant type Total capital cost (per million $) Specific capital cost ($/kW) Annual operating cost (per million $)

Steam cycleebased NPP 3565

Gas cycleebased NPP 3837

Combined cycleebased NPP 5742

5571

4568

5220

87

114

145

Desalination Desalination type

MED

MSF

RO

MSF þ RO 158

MED

MSF

RO

147

MED þ RO 158

Total Capital cost (per million $) Annual operating cost (per million $)

179

179

17

32

179

179

15

16

23

7

10

MED, multieffect distillation; MSF, multistage flash; RO, reverse osmosis.

MSF þ RO 158

MED

MSF

RO

147

MED þ RO 158

147

MED þ RO 158

MSF þ RO 158

179

179

14

11

12

17

31

14

16

22

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CHAPTER 2.20 COMPARATIVE EVALUATION OF POSSIBLE DESALINATION OPTIONS

1.80

Water Producon Cost $/m3

1.60 1.40 1.20 0.94

1.00 0.80 0.60 0.40 0.20

0.90 0.58

0.46

0.55

0.45 0.33

0.24 0.32

0.23 0.12 0.20 0.23 0.17 0.21 0.13 0.13 0.13 0.13 0.13 0.13 0.17 0.17 0.17 0.17 0.17 0.17 0.10 0.10 0.21 0.10 0.10 0.21 0.10 0.10 0.21 0.05 0.07 0.07 0.05 0.07 0.07 0.05 0.07 0.07 0.36 0.36 0.29 0.31 0.31 0.36 0.36 0.29 0.31 0.31 0.36 0.36 0.29 0.31 0.31

0.00 1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

Cases Overnight Capital Cost ($/m3)

Other Capital Expenses ($/m3)

O&M ($/m3)

Energy Cost ($/m3)

FIGURE 5 Comparison of freshwater production costs using different desalination techniques. O&M, operation and maintenance.

FIGURE 6 Overnight capital cost, other capital expenses, and O&M cost of different desalination options. MED, multieffect distillation; MSF, multistage flash; O&M, operation and maintenance; RO, reverse osmosis.

NOMENCLATURE

581

FIGURE 7 Energy costs of desalination options for steam, gas, and combined cycles. MED, multieffect distillation; MSF, multistage flash; RO, reverse osmosis.

SC- and CC-based power plants have similar unit cost values in each desalination system. RO is seen as the most economical way to produce fresh water in SC- and CC-based NPPs. Membrane-type desalination requires only electricity to produce fresh water, so the cost of energy for RO is smaller than for the thermal desalination type for SC- and CC-based NPPs. The energy cost of the MSF is more than that of the other types because the thermal power and electricity requirements of MSF are higher than those of MED and RO, as can be seen in Table 2. Integration of the MSF desalination process with any NPP results in a higher cost for freshwater production.

6. CONCLUSIONS This study considered combinations of desalination methods, including MED, MSF, and RO and hybrid systems with an NPP. A comparative cost evaluation of possible desalination processes was carried out for SC-, GC-, and CC-based NPPs. DEEP software, developed by IAEA, was employed to assess the costs of water production for each scenario. MED with a gas turbineebased NPP had the lowest fresh water production cost at $0.71/m3. Furthermore, the RO method was observed to be the most economical one for SC- and CC-based NPPs. Freshwater production costs for reverse osmosis with SC and CC NPPs were calculated to be $0.79/m3 and $0.78/m3, respectively.

NOMENCLATURE CC DEEP GC IAEA MED

Combined cycle Desalination Economic Evaluation Program Gas cycle International Atomic Energy Agency Multieffect distillation

582

MSF NPP RO SC

CHAPTER 2.20 COMPARATIVE EVALUATION OF POSSIBLE DESALINATION OPTIONS

Multistage flash Nuclear power plant Reverse osmosis Steam cycle

REFERENCES [1] World Economic Forum. Thirsty energy: water and energy in the 21st century [online]. 2009. p. 10e3. Available at:, http://www3.weforum.org/docs/WEF_WaterAndEnergy21stCentury_Report.pdf. [2] International Atomic Energy Agency. Use of nuclear reactors for seawater desalination. IAEA-TECDOC574. 1990. p. 9e15. [3] International Atomic Energy Agency. New technologies for seawater desalination using nuclear energy. IAEA-TECDOC-1753. 2015. p. 1e15. [4] International Atomic Energy Agency. Technical and economic evaluation of potable water production through desalination of seawater by using nuclear energy and other means. IAEA-TECDOC-666. 1992. p. 5e20. [5] Abdoelatef M, Field R, Lee Y. Economic evaluation of coupling APR1400 with a desalination plant in Saudi Arabia. Journal of the Korea Society of Systems Engineering 2016;12(1):73e87. [6] Dincer I, Rosen M. Exergy. 1st ed. Oxford (UK): Elsevier; 2013. p. 53e4. [7] Kavvadias K, Khamis I. ‘The IAEA DEEP desalination economic model: a critical review’. Desalination 2010;257(1e3):150e7. [8] Alonso G, Vargas S, del Valle E, Ramirez R. Alternatives of seawater desalination using nuclear power. Nuclear Engineering and Design 2012;245:39e48. [9] Khamis I, Kavvadias K. Nuclear desalination: practical measures to prevent pathways of contamination. Desalination 2013;321:55e9. [10] El-Emam R, Ozcan H, Dincer I. Comparative cost evaluation of nuclear hydrogen production methods with the Hydrogen Economy Evaluation Program (HEEP). International Journal of Hydrogen Energy 2015; 40(34):11168e77. [11] Mansouri N, Ghoniem A. Does nuclear desalination make sense for Saudi Arabia? Desalination 2017;406: 37e43. [12] International Atomic Energy Agency. DEEP 5 user manual [online]. 2013. Available at:, https://www.iaea. org/NuclearPower/Downloadable/NEA_Desalination/DEEP/DEEP5_Manual.pdf. [13] Raluy G, Serra L, Uche J. Life cycle assessment of MSF, MED and RO desalination technologies. Energy 2006;31(13):2361e72.

CHAPTER

COMPARATIVE EVALUATION OF POSSIBLE DESALINATION OPTIONS FOR AKKUYU NUCLEAR POWER PLANT

2.21 M. Furkan Polat1, Ibrahim Dincer2, 3

1

Bogazici University, Istanbul, Turkey ; UOIT, Oshawa, ON, Canada2; YTU, Istanbul, Turkey3

1. INTRODUCTION With the rise in population and economic growth, energy demand throughout the world is continuously increasing over the long term. In 2016, the world’s energy consumption was 101.78 quadrillion kJ, and it is been projected that in 2050 it is going to rise to 112.6 quadrillion kJ. As shown in Fig. 1, fossil fuels dominated the world’s energy consumption in 2016 leading to the increase in CO2 emissions. With the continuous use of fossil fuel reserves and their associated environmental problems,

FIGURE 1 Worldwide energy consumption in 2016. Data from Energy Information Administration US. Annual energy outlook report.https://www.eia.gov/outlooks/aeo/pdf/ 0383(2017).pdf; January 2017. p. 1e127. Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00033-0 Copyright © 2018 Elsevier Inc. All rights reserved.

583

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CHAPTER 2.21 COMPARATIVE EVALUATION OF POSSIBLE DESALINATION OPTIONS

researchers are looking to use sources of energy that are environmentally benign and sustainable like renewable and nuclear energy. Therefore, it is essential to explore these energy sources and systems to make them practical for implementation within today’s energy infrastructures. However, many renewable energy sources have intermittent problems due to their fluctuating nature. Hence, nuclear energy may provide the stable power and would also avoid the many problem associated with fossil fuels. Turkey has an increasing energy demand resulting from increasing population and a growing economy, and the current main sources of the energy generation depend on the other countries. The energy demand and the growth of the demand for Turkey are shown in Fig. 2A. According to data provided by the Ministry of Foreign Affairs of the Turkish Republic, the primary energy demand will almost double in 2023. In addition, it is expected that the total annual energy demand will be 416 TWh,

(A)

Electricity Demand and Demand Growth Rate by Year 10%

300,000

8%

250,000

6%

GWth

200,000

4% 150,000 2% 100,000

0%

50,000

-2%

0

-4% 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

(B)

Electricity Demand

Electricity Demand Growth (%)

FIGURE 2 (A and B) Yearly electricity demand and demand growth rate of Turkey. Data from EMRA, Energy Market Regulatory Authority, Turkey; 2017. Available at: http://www.emra.org.tr/EN/Documents/ ElectricityMarket/PublishmentsReports.

1. INTRODUCTION

585

FIGURE 3 Electricity generation by type. Data from EMRA, Energy Market Regulatory Authority, Turkey; 2017. Available at: http://www.emra.org.tr/EN/Documents/ ElectricityMarket/PublishmentsReports.

which was 264 TWh in 2015, according to investigations of the Ministry of Energy and Natural Resources [2]. Fig. 2B shows the yearly electricity consumption of Turkey from 1923 to 2016. Moreover, the generation of electricity is mainly based on the imported resources. The distribution of the sources for the electricity generation in Turkey in 2015 is shown in Fig. 3. Therefore, nuclear energy applications have a great role in Turkey’s future energy strategies. According to statistical data provided in several studies, 70% of Turkey’s energy supply were imported energy sources in 2010 [2]. All these future projections make the nuclear power plant (NPP) projects very important in order to satisfy increasing energy demands and energy independence for Turkey. Note that 97% of water (a type of saline water) present on the earth is in oceans while the remaining 3% is the fresh or potable water. Statistics [4] show that only 1% of water available on earth can be used by humans, leading to the clean water crisis. Water resources and its distribution to different purposes and regions have been becoming more important than in the past because of natural and economic reasons. Global warming and water usage in industry and agriculture make the availability of fresh water harder. Especially, countries that have hot climates are facing more issues with the negative outcomes of global warming, and the developing countries are facing increasing demand for water in direct and indirect consumption, namely, agriculture and industry. From this perspective, Turkey has a critical situation that can be affected by both increasing average temperature and increase in water demand, so the fresh water supply is expected to be an important issue not only for Turkey but also more than the half of the world population [5]. One of the most feasible solutions to deal with fresh water scarcity is desalination systems. Fresh water can be produced from the seawater utilizing desalination systems. The countries located in the hot climate regions use these systems in order to meet their fresh water needs. The total number of desalination plants in the world is 18,426, producing 86.8 million m3/day of fresh water; 150 countries have these plants, and more than 300 million people meet their fresh water needs partially or totally due to desalination plants (as of June 30, 2015) [6].

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CHAPTER 2.21 COMPARATIVE EVALUATION OF POSSIBLE DESALINATION OPTIONS

It is important to mention that governments are aware of the aforementioned two issues (electricity demand and fresh water) and are developing strategies. The Turkish government also has certain strategies and future plans as a potential country that can be faced with these two problems. According to the studies conducted by government institutions, nuclear power plants and water desalination systems can be two possible solutions for these issues. Turkey is currently building two NPP projects with different partners. In order to meet the expected energy demand and reduce the portion of the produced energy that is based on fuel imports, nuclear plant projects have been studied since the 1980s [7]. In addition, desalination systems for getting fresh water from seawater are been considered as a potential solution to the scarcity of fresh water. Based on this, Turkey’s Ministry of Foreign Affairs has prepared a report that sets the following specific goals: • • • •

Expanding its supplier countries and routes in terms of energy resources; Increasing the proportion of the nuclear and renewable energy sources; Working on energy efficiency; Providing something that can contribute to Europe’s energy efficiency.

For desalination processes like reverse osmosis (RO) and mechanical vapor compression (MVC), energy is required in the form of electricity, nuclear power plants are most suitable. In these type of systems, the power directly comes from the plant to meet the electrical requirement of the equipment (like high-pressure pump in RO and compressor in MVC) in these systems. Nuclear plants that are producing heat and electricity are also used for desalination purposes. In these types of nuclear plants, steam is bled at suitable location in the water circuit of the nuclear power plant and utilized for desalination. The type of desalination techniques that can be combined with these types of plants are multistage flash, multieffect distillation, etc. A great deal of research has been conducted on combining nuclear reactors with desalination plants. Recently, Khalid et al. [8] developed, studied, and compared two nuclear power plant (CANDU 6 and SFR)ebased systems for coproduction of electricity and fresh water. They conducted the exergy analyses and concluded that the SFR-based nuclear power plant performed better in terms of exergy efficiency compared to the CANDU 6-based nuclear power plant. One of the salient features of their systems is that they use preheated seawater before feeding it to the RO plant, resulting in higher efficiencies. Park and Kim [9] studied the coupling of a very high-temperature reactor with forward osmosis plant. They claimed that integration of a very high-temperature reactor with forward osmosis desalination system is more beneficial and efficient compared to multistage flash distillation integration with a very high-temperature reactor. Nissan and Dadour [10] compared costs of four different nuclear plantebased options for coproduction of fresh water and electricity. Their study suggests that reverse osmosis is the most cost effective compared to other three options. Alonso et al. [11] have also studied five different types of desalination techniques coupled with nuclear power. They found that each technique has its own merits and demerits. In the present study, five different types of desalination options, namely, multiple effect distillation (MED), RO, MSF, MSF þ RO, and MED þ RO, using nuclear reactors for the combined production of electricity and fresh water are assessed and compared. The objectives are to enhance understanding of the systems and to determine the advantages and disadvantages of each. Potential software called the Desalination Economics Evaluation Program (DEEP) is used in the assessment for the real case scenario (Akkuyu Nuclear Power Plant). For each case, unit costs for potable water and payback period are evaluated and compared.

2. SYSTEM DESCRIPTION

587

2. SYSTEM DESCRIPTION Fig. 4 shows the schematic of a nuclear power plant using MED þ RO desalination technique. Some of the desalination methods are described in the next sections.

2.1 DESALINATION METHODS Desalination is defined as the generation of fresh water from seawater by using different techniques. It has developed in the second half of the 21st century. The applications and installed capacity of the total desalination systems have been increasing. The most commonly used desalination methods can be divided into two groups: thermal desalination and membrane type. In a thermal desalination system, input seawater is heated and gets evaporated. The evaporated seawater is then condensed to obtain fresh water. Since the cycle also needs fluid flow, in addition to the heat source, a certain amount of electricity is also needed to operate the system. Thermal desalination systems can be divided into two types: MED and MSF desalination. The most common membrane type desalination is RO, and it is the most used desalination method among all types. In addition to these three types, vapor compression (VC), electrodialysis (ED), and ion exchangeebased desalination technologies are being studied but they are not widely preferred [12]. Desalination systems can be implemented in various ways. They can be built as a single plant or in a hybridized form with other desalination methods.

2.1.1 Multiple Effect Distillation MED is a desalination method in which heat and electricity are used to produce potable water. There are several chambers in this type of system. Hot steam coming out from the nuclear power plant is

FIGURE 4 RO þ MED hybrid system flow diagram from DEEP.

588

CHAPTER 2.21 COMPARATIVE EVALUATION OF POSSIBLE DESALINATION OPTIONS

carried by the pipes into the chamber and the seawater is repelled on the pipes. Heat is transferred to the seawater from the hot steam pipes, so the steam condenses and the seawater evaporates. Although the temperature difference is quite high, it is not enough to evaporate all of the water. Therefore, remaining water is carried to the second stage. Meanwhile, the hot steam loses a certain amount of temperature and pressure due to condensation. In the second stage, the resultant hot steam from stage 1 is brought in contact with the remaining water. Since the pressures of the chambers are different, the seawater can be evaporated in each stage while the steam is condensing. This cycle is repeated a few times, and at the end of the process the remaining vapor is used for preheating the feed water [13].

2.1.2 Multistage Flash MSF is the most common thermal desalination system. Like MED, it also requires both heat and electricity as inputs. The main idea is almost the same with the MED, but this time seawater flows in both directions. There are finned thin tubes for carrying the seawater over the stages. By passing the stages, the seawater is heated. In the last part, it is boiled in the brine heater. A vacuum pump is used to reduce the pressure of the first stage in order to evaporate the hot water. The vapor of the water is condensed on the cooler surface and then collected. The main difference between the MSF and MED is the flow direction in the system. In the MSF, the hot steam and the seawater flow in opposite directions. Since the condensed water is limited because of the temperature and pressure difference between the pipe and the chamber, the number of stages that can be reached is 40 in this type of desalination plant [13].

2.1.3 Reverse Osmosis The pressure between the two different fluids that are separated from each other with a semipermeable membrane is called osmotic pressure. Due to osmotic pressure, the water in the less pressurized part passes to the other side. In reverse osmosis desalination, an external pressure is applied to change the direction of this tendency. Therefore, the fresh water in the seawater can be removed without any salt or undesirable particles. To provide high pressure to the pumps, this process requires a lot of energy (electricity) [14].

2.2 DEEP SOFTWARE This study aimed to compare the possible desalination system for Akkuyu NPP. The comparison was simulated with DEEP, which was developed by the International Atomic Energy Agency (IAEA). DEEP enables users to simulate different power plant types with different desalination systems. Moreover, economic and technical parameters can also be altered by users to get more realistic cases. The program is also efficient for calculating the unit production cost for both electricity and fresh water. It can also give the payback period for the power plant and the desalination plants that are simulated. Therefore, DEEP enables us to analyze the investment alternatives in different ways. DEEP has three input categories, namely, user input data, technical parameters, and cost parameters. First, the type of the power plant and the desalination plant are chosen. DEEP provides all common power plants (see Table 1) and the three well-known desalination systems (multistage flash distillation, reverse osmosis, and multiple effect distillation). Moreover, the hybrid desalination systems such as MSF þ RO, MED þ RO, etc. (see Table 2) can also be evaluated. The capacity of the power plants, desalination plants and salinity of the feed water are also specified in the user parameters. The basic

2. SYSTEM DESCRIPTION

589

Table 1 Different Types of Power Plants Included in DEEP Software Source of Energy

Type of Plant

Nuclear

PWR, PHWR,SPWR, GTMHR, HR Superheated Rankine cycle Superheated Rankine cycle GT, Combined cycle, diesel

Coal Oil Fossil

Source: Kavvadias KC, Khamis I, The IAEA DEEP desalination economic model: a critical review. Desalination 2010; 257: 150e7.

Table 2 Desalination Techniques With Form of Energy Used Form of Energy

Desalination Technique

Electricity Heat Heat þ Electricity (Hybrid)

MVC, RO, ED, FO MSF, MED, TVC, AD, MD MSF þ RO, MED þ RO

Source: Kavvadias KC, Khamis I, The IAEA DEEP desalination economic model: a critical review. Desalination 2010; 257: 150e7.

economic parameters are also given in this part, for instance, discount and interest rates. After specifying the general features and type of the plant, details of the whole system are given in the second part. The program provides an easy guide to users in order to follow the steps. The specific details of the system such as intermediate facilities, the capacity of the feed water, the capacity ratio of the hybrid systems, the efficiency, and temperature values are important thermal units in the system. In the last section, the cost parameters are specified. Fixed and operational costs are stated separately. Construction cost, operation cost, expected lifetime of the system, and the availability of the desalination plant can be stated in this part. In order to calculate the levelized cost of water production, the capital costs and other operation costs are added to the energy cost.

2.3 AKKUYU NUCLEAR POWER PLANT Akkuyu Nuclear Power Plant is one of the two NPPs that Turkey will have in upcoming years. Akkuyu NPP is being constructed in Mersin, Turkey. It is a water-moderated water-cooled power reactor (VVER)etype NPP that was developed by Russia. The first reactor is planned to generate electricity in 2019. The project is based on the build-own-operate structure provided by the Turkish government and the lifetime is 60 years. In a specific time period, the government provides purchasing guarantees at a specified unit price for generated electricity for the firms taking part in this project as operators [7]. In Akkuyu Nuclear Power Plant, there are four reactors, each with 3200 MWt power capacity. In this study, one single reactor is simulated for the possible desalination applications. In an ordinary nuclear power plant, heated and pressurized fluid in the reactor is transferred into the turbines in order

590

CHAPTER 2.21 COMPARATIVE EVALUATION OF POSSIBLE DESALINATION OPTIONS

to rotate the turbine blades. Since the fluid loses a certain temperature and pressure while hitting the blades, turbine systems have different turbine levels for different temperature and pressure values. When the fluid hits the blades and rotates them, the turning blade shafts produce electricity. Generated electricity would be used to provide power to run the system and grid. In Fig. 4, one of the reactors of Akkuyu NPP is simulated with the hybrid plant that has both membrane-type and reverse osmosise type desalination. Fluid flows and heat flows can be visualized by the DEEP software. The program enables users to modify some of the values in that screen. For example, the portion of the desalinated water can be altered between two desalination plants or the max brine temperature can be changed. The input seawater salinity was based on the yearly average salinity of Mediterranean seawater. The hybrid system capacity of the water production was divided into two equal parts and distributed to RO and MED parts.

3. ASSUMPTIONS AND METHOD OF THE STUDY For the sake of simplicity, except for the data provided for Akkuyu NPP in literature, all other parameters were assumed to be the same as given in the DEEP database. The technical and economical input parameters used in the study are listed in Table 3. In this study, the possible application of desalination systems for Akkuyu NPP are discussed and compared with each other. When the lifetime of the plant is taken into account, the need for potable water can become one of the major problems of the Turkey. Therefore, the main goal of this study is to compare the desalination options for Akkuyu under the specified conditions. The selection of the power plant type is taken as the steam cycle, and the capacity is taken for one of the reactors of Akkuyu NPP. Since the operational starting times of the reactors are different, this is selected for simplicity and for avoiding time-dependent variables. Intermediate loop application was installed into the simulations for all cases. In the hybrid cases, for instance, the RO and MED desalination processes together, the same amount of the potable water produced is assumed. A single desalination system was assumed to have 100,000 m3/day water production capacity. In the hybrid case, this amount has been divided into two equal parts, i.e., 50,000 m3/day for each case. The air and seawater temperature were taken from the annual average of the local values. The construction cost per unit power generated was another changed value accordingly. The interest and discount rates and the financial values were modified according to studies conducted concerning Akkuyu NPP [16e19].

4. ANALYSIS OF THE STUDY In this study, the results can be interpreted in different ways. The unit costs of the fresh water production or the electricity generation cost can be compared among different desalination options. However, there are similar results for all cases, for example, the input power and the capacity values are the same, and so power costs are also the same. The quality of the desalinated water is better in thermal systems but the capacity of the fresh water generation is less (see Table 4) [20]. The transportation option was not simulated, but the DEEP also has a transportation selection for the simulations. The power loss concept of DEEP can show the benefit of the hybrid usage of the power plant and the desalination. The power credit method is used for the cost calculation. It originates from the

4. ANALYSIS OF THE STUDY

591

Table 3 Input Parameters Considered in the Study Power Plant Type Fuel Reference thermal power (MWt) Reference net efficiency (%) Cooling water temperature (K) Feed water inlet temperature for reverse osmosis (K)

Steam Cycle Nuclear 3200 37.50 296 292

Desalination Plant Capacity (m3/d) Water salinity (ppm) Lifetime of desalination system (years)

100,000 40,679 20

Economic Parameters Interest rate (%) Discount rate (%) Debt ratio (w/o financing costs) (%) Specific construction cost ($/kW(e)) Electricity selling price ($/kWh)

7 5 80 4170 0.1235

comparison between the coupled usage and the single usage of the power plant. For the desalination plant side, the heat and electricity needs are assumed to be provided by independent sources, so the cost of heat is taken as revenue because of the dual purpose. The numerical calculations of the power losses in DEEP are based on the Rankine and Carnot cycle efficiencies. The power losses are related to the heat cost or heat required for the desalination part. Therefore, the power loss in RO is zero because there is no heat transferred from the power plant to the desalination plant. Moreover, the main cost differences between the possible scenarios are heat and electricity costs. The tabulated numerical values (see Table 5) about the cost parameters for each scenario are visualized in Fig. 5. Because of the high level of the heat cost, MSF is seen as the most expensive option. Moreover, since the daily productions of the thermal desalination are lower than the desalination included in the RO part in single or hybrid form, the payback period of the investments for thermal desalination is longer than the other cases. General economic evaluation of the Akkuyu NPP with different desalinations is tabulated in Table 5. DEEP has five main parts of the unit costs for the fresh water production for each scenario.

592

CHAPTER 2.21 COMPARATIVE EVALUATION OF POSSIBLE DESALINATION OPTIONS

Table 4 Comparison of the Unit Price of the Produced Water in Different Types of Desalination Plants Output Summary Levelized Capital Cost Base Plant Overnight EPC Other Levelized Operating Costs Heat Electricity O&M Lifecycle Emissions Thermal Utilization Power Lost Power Used for Desalination Power Cost

MED

MSF

RO

MED D RO

MSF D RO

3

0.46

0.46

0.34

0.39

0.39

$/m3

0.35

0.35

0.29

0.31

0.31

$/m3 $/m3

0.11 0.63

0.11 1.14

0.06 0.48

0.08 0.55

0.08 0.79

$/m3 $/m3 $/m3 Mtn/y

0.38 0.13 0.12 191

0.84 0.18 0.12 191

0.00 0.28 0.21 191

0.18 0.2 0.17 191

0.4 0.23 0.17 191

%

33

41

26

29

33

MWe MWe

22 7

49 9

0 15

11 11

25 12

$/MWh

71

71

71

71

71

Steam Cycle Nuclear 3200

Steam Cycle Nuclear 3200

Steam Cycle

Steam Cycle

MWth

Steam Cycle Nuclear 3200

Nuclear 3200

Nuclear 3200

MWe

1024

1024

1024

1024

1024

GWh/y

6583

6583

6583

6583

6583

m3/d ppm

MED 100,000 40,679

MSF 100,000 40,679

RO 100,000 40,679

MED þ RO 100,000 40,679

MSF þ RO 100,000 40,679

29.57

19.57

32.85

31.21

31.21

Units $/m

Input Summary Power Plant Type Fuel Reference Thermal Output Reference Electricity Output Electricity Production Desalination Type Total Capacity Feed Salinity

Combined Availability Water Production

106 m3/d

The electricity generated in the base plant has a certain unit cost, so it contributes to the total water production cost. The production cost of the electricity, the heat cost produced in the power plant, the used electricity cost for the desalination plant, and operation and maintenance costs (O&M) are the four main cost contributors with the other cost effects. Depending on the type of the desalination plant,

4. ANALYSIS OF THE STUDY

593

Table 5 Cost of Different Types of Desalination Selections

Base plant overnight EPC Other Heat cost Electricity cost O&M cost Total water cost

MED

MSF

RO

MED D RO

MSF D RO

0.35

0.35

0.29

0.31

0.31

0.11 0.38 0.13 0.12 $1.093 per m3

0.11 0.84 0.18 0.12 $1.602 per m3

0.06 0.00 0.27 0.21 $0.827 per m3

0.08 0.18 0.20 0.17 $0.941 per m3

0.08 0.40 0.23 0.17 $1.181 per m3

1.80

Cost of Desalinaon ($/m3)

1.60

Base plant overnight EPC Other

0.12

1.40

0.18

Heat cost

1.20 1.00 0.80 0.60

0.12 0.13

0.17 0.84

0.17 0.21

0.38

0.40

0.11

0.11

0.20

0.35

0.35

0.27

0.20

0.23 0.40

0.06

0.18 0.08

0.08

0.29

0.31

0.31

0.00 MED

MSF RO MED RO MSF RO Desalinaon Techniques

FIGURE 5 Comparison of the costs of the different desalination options.

the ratio and the amount of the cost parameters change. For example, the heat cost covers almost half of the MSF water production cost, but RO has zero heat cost because it does not require any heat. The base plant overnight EPC cost is referred to as the construction cost of the power plant. It is calculated based on the unit cost per generated power. Site-related cost, contingencies, escalation, and interest during construction are neglected for this calculation. The additional estimated costs are calculated as a percentage of the base plant cost. These side costs can be safety cost, foundation, site leveling, or cooling water intake/outfall. For the unexpected costs there is a contingency factor that is 10% as default in the cost calculation method of the program. With the interest cost during construction and decommissioning cost, all these economic costs are named as capital costs by the program.

594

CHAPTER 2.21 COMPARATIVE EVALUATION OF POSSIBLE DESALINATION OPTIONS

In addition to the capital costs, there are several types of operation costs for the desalination systems. Operating costs includes fuel cost, operating and maintenance cost, and the taxes. Fuel cost for desalination plants are assumed to be the heat and electricity needed. Operating and maintenance costs are different for membrane and thermal systems. Since the thermal desalinations require more heat, the unit production cost of the water is relatively higher than the membrane type. However, the electricity cost of the RO system is quite high with respect to the thermal desalination system because of higher electricity requirements compared to thermal desalination plants. Hybridization of the different desalination options offers significant improvements in costeffectiveness. The thermal desalination systems have lower unit cost for potable water produced in O&M and electricity costs. On the other hand, RO is more cost effective in terms of the heat and electricity costs. Therefore, the unit cost of the water production can be balanced somehow by hybridization of the different types of the desalination plants. The total cost is still higher than the RO unit cost but the thermal utilization and the quality of water are better in thermal systems. Thus the quality and waste energy source utilization can be enhanced in the hybrid form of desalination plants. The payback year of Akkuyu NPP is found to be 9.8 years by using the DEEP simulation software. The payback period of each desalination system was also determined. The financial analysis part of DEEP software provides the total payback period for the power plants with desalination systems. It can be seen that the RO desalination application could reduce the total payback period of Akkuyu NPP by 0.2 years. However, all other desalination types would increase the payback year of the plant (see Fig. 6).

12

Payback Period (y)

10 8 6 4 2 0

MED

MSF

RO

MED RO

MSF RO

Power Plant

9.8

9.8

9.8

9.8

9.8

Desalinaon

6.3

9

5

5.5

6

Power Plant with Desalinaon

10

10.8

9.6

9.8

10.1

FIGURE 6 Payback period of Akkuyu NPP and possible desalination system.

REFERENCES

595

5. CONCLUSIONS In this study, Akkuyu NPP is simulated using the DEEP software package according to technical and economic data provided in the literature. In order to compare different desalination types, the water cost and payback period were taken as main parameters. In terms of the produced water unit cost, the RO desalination has the lowest cost, which is $0.827 per m3 and the MSF has the highest cost $1.602 per m3. When the payback periods are considered, the shortest payback period is for the power plant using RO desalination technique, i.e., 9.6 years. In the case of combination of MED and RO, the payback period of the total system does not change after desalination application. In the MED, MSF, and RO þ MSF cases, the total payback periods of the plant with desalination are increased.

NOMENCLATURE AD DEEP ED EPC FO GT HR IAEA MD MED MHR MSF MVC NPP PHWR PWR RO SPWR TVC VC VVER

Adsorption desalination Desalination Economic Evaluation Program Electrodialysis Electricity production cost Forward osmosis Gas turbine Heat reactor International Atomic Energy Agency Membrane distillation Multiple effect distillation Modular helium reactor Multistage flash Mechanical vapor compression Nuclear power plant Pressurized heavy water reactor Pressurized water reactor Reverse osmosis Small pressurized water reactor Thermal vapor compression Vapor compression Water-moderated water-cooled power reactor

REFERENCES [1] Energy Infromation Administration US. Annual energy outlook report. January 2017. p. 1e127. https:// www.eia.gov/outlooks/aeo/pdf/0383(2017).pdf. [2] EMRA, Energy Market Regulatory Authority, Turkey; 2017. Available at: http://www.emra.org.tr/EN/ Documents/ElectricityMarket/PublishmentsReports. [3] Enerji Atlasi. Electricity generation in Turkey. Turkey; 2017. Available at http://en.enerjiatlasi.com/ electricity-generation/turkey/

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CHAPTER 2.21 COMPARATIVE EVALUATION OF POSSIBLE DESALINATION OPTIONS

[4] Shiklomanov I. World fresh water resources. In: Gleick PH, editor. Water in crisis: a guide to World’s fresh water resources. Oxford (UK): Oxford University Press; 1993. p. 13e24. [5] 5th World water forum, Istanbul water guide, ministerial process. 2009. Available at: http://www.mfa.gov.tr/ data/DISPOLITIKA/SuPolitikas%C4%B1/SuForumu/IstanbulWaterGuide_Final_05-03-09.pdf. [6] Privacy I, Design W, Hide S, and Media, Desalination by the numbers. Available at: http://idadesal.org/ desalination-101/desalination-by-the-numbers/; 2016. [7] IAEA. Technical and economic evaluation of potable water production through desalination of seawater by using nuclear energy and other means. TECDOC No. 666. 1992. [8] Khalid F, Dincer I, Rosen MA. Comparative assessment of CANDU 6 and sodium-cooled fast reactors for nuclear desalination. Desalination 2016;379:182e92. [9] Park MY, Kim ES. Thermodynamic evaluation on the integrated system of VHTR and forward osmosis desalination process. Desalination 2014;337:117e26. [10] Nisan S, Dardour S. Economic evaluation of nuclear desalination systems. Desalination 2007;205:231e42. [11] Alonso G, Vargas S, del Valle E, Ramirez R. Alternatives of seawater desalination using nuclear power. Nuclear Engineering and Design 2012;245:39e48. [12] Lomonaco G, Mantero G, Marotta R. Nuclear desalination: an alternative solution to the water shortage. Global Journal of Energy Technology Research Updates 2014;1(2):57e70. [13] IAEA. IAEA toolkit on nuclear desalination: DEEP 5 user manual. Vienna: IAEA; 2013. Available at: https://www.iaea.org/NuclearPower/Downloadable/NEA_Desalination/DEEP/DEEP5_Manual.pdf. [14] Raluy G, Serra L, Uche J. Life cycle assessment of MSF, MED and RO desalination technologies. Energy 2006;31(13):2361e72. [15] Kavvadias KC, Khamis I. The IAEA DEEP desalination economic model: a critical review. Desalination 2010;257:150e7. [16] IAEA. Alternative contracting and ownership approaches for new nuclear power plants IAEA. TECDOC No. 1750. 2014. [17] Demırbas A. Energy facilities and nuclear power program by 2020 in Turkey. Energy Sources 2001;23(5): 401e15. [18] Cometto M. Financing the Akkuyu NPP in Turkey. In: OECD/NEA Workshop on “electricity price and nuclear new build”, Paris; September 19, 2013. Available at: https://www.oecd-nea.org/ndd/workshops/ wpne/presentations/docs/4_1_Cometto_Akkuyu.pdf. [19] Bashitialshaaer RAI, Persson KM, Aljaradin M. Estimated future salinity in the Arabian Gulf, the Mediterranean Sea and the Red Sea consequences of brine discharge from desalination. International Journal of Academic Research 2011;3(1):133e40. [20] Ghaffour N, Missimer TM, Amy GL. Technical review and evaluation of the economics of water desalination: current and future challenges for better water supply sustainability. Desalination 2013;309:197e207.

CHAPTER

DETERMINATION OF FLOW CHARACTERISTICS OF MULTIPLE SLOT JET IMPINGEMENT COOLING

2.22 Nuri Kayansayan1, Ersin Alptekin2

_ Near East University, Mersin, Turkey1; Dokuz Eylul University, Izmir, Turkey2

1. INTRODUCTION

1.1 A SINGLE CONFINED SLOT JET As illustrated in Fig. 1, a directed fluid coming out of a nozzle and normally or obliquely impinging on a solid wall is known as an impinging jet. Heat transfer using impinging jets is most effective in singlephase heat transfer methods owing to its large heat and/or mass transfer between the surface and the fluid. The flow required for an impinging jet device may be two orders of magnitude smaller than that required for a cooling application using a free wall-parallel flow for a given heat transfer coefficient [1]. The presence of a confinement wall makes free jet behavior coupled with the fluid behavior in a channel flow result in a more complicated flow. Impinging jets are encountered in a wide range of industrial processes as an efficient means to enhance and control localized heat and mass transfer. Applications of impinging jets include the drying of textiles, film, and paper; the cooling of gas turbine components and the outer wall surfaces of combustors; the freezing of tissue in cryosurgery; and the cooling of electronic equipment. Significant attention has been paid to impinging jets, and the high heat and mass transfer rates associated with impinging gaseous jets have been well recognized and were documented by Zhou and Lee [2] and Dewan et al. [3]. Single and normally impinging jets are efficient for localized heat transfer from the impingement location on a surface. The different regions of an impinging jet are shown in Fig. 1. The different zones are the potential core, developing, fully developed, stagnation, and wall jet regions. Maurel and Solliec [4] developed a test bench with variable geometry; they used laser Doppler velocimetry and particle image velocimetry to analyze the development of the jet for different geometrical configurations. They concluded that the characteristic height of the impinging zone remained close to 12% to 13% of the jet-to-plate spacing irrespective of the Reynolds number (Re) and the jet width. The flow field of plane-impinging jets at moderate Re was computed using large-eddy simulation (LES) with a dynamic Smagorinsky model by Beaubert and Viazzo [5]. They studied the mean velocity and the turbulence statistics along the jet axis and at different vertical locations. In a numerical study of a plane turbulent-impinging jet in a confined space using direct numerical simulation (DNS), Hattori and Nagano [6] noticed that for low nozzle-to-plate distances, a second peak appears in the local Nusselt number and skin friction coefficient distribution Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00034-2 Copyright © 2018 Elsevier Inc. All rights reserved.

597

598

CHAPTER 2.22 DETERMINATION OF FLOW CHARACTERISTICS

(A)

rectangular slot zone flow moves laterally over target

target flow direction may vary at endwalls

(B)

FIGURE 1 Impinging confined slot jet [27]. (A) Schematic of single slot jet and (B) flow regions of confined jet.

along the impingement surface. This trend of the secondary peak vanishes with an increase in the distance of the nozzle to the plate. The mechanism for the occurrence of the second peak in the local Nusselt number is the development of the wallenormal heat flux near the wall. A small number of studies are available in the literature in which several types of turbulence models were used to check the accuracy of results compared with available experimental results and to find the suitability of the turbulence models used. Craft et al. [7] employed four turbulence models comprising one k-ε eddy viscosity model and three second-moment closures for the numerical simulation of turbulent impinging circular jets. The k-ε model and one of the Reynolds stress models gave too-large levels of turbulence near the stagnation point that resulted in high heat transfer coefficients and turbulent mixing with surrounding fluid. For the numerical simulation of a two-dimensional flow field and heat transfer impingement resulting from to a turbulent single-heated slot jet discharging normally into a confined channel, Seyedein et al. [8] used both low- and high-Re versions of k-ε turbulence models. From the low-Re model study, they found that models presented by Lam-Bremhorst and Launder-Sharma showed good agreement with the available experimental data. Hosseinalipour and Mujumdar [9] compared the performances of the standard high Re 2 equation k-ε with the standard wall function approach and five low-Re versions of the k-ε model. They compared their results of Nusselt number

1. INTRODUCTION

599

distribution with the experimental data of Ichimiya and Hosaka [10] and obtained better results by including Yap correction [11] in some of the low-Re models. Angioletti et al. [12] extensively investigated flow field behavior in the vicinity of the stagnation region. Later, using a commercial computational fluid dynamics (CFD) package, they evaluated the suitability of three different turbulence models by comparing the numerical results with the experimentally obtained ones. They found that the k-u shear-stress transport (SST) model gave good results for a lower Re and k-ε renormalization group (RNG) or Reynolds stress model performed better for a high Re . Zuckerman and Lior [13] compared the relative strengths and drawbacks of k-ε, k-u, the Reynolds stress model, algebraic stress models, shear stress transport, and the v2-f turbulence models for impinging jet flow and heat transfer. In their findings, they highlighted that although the computational costs for k-ε, k-u, realizable k-ε and other k-ε variations, and the algebraic stress model are low, the impingement jet transfer coefficient prediction was poor. On the other hand, they concluded that shear stress transport, v2-f, and DNS/LES time-variant models had a moderate to high computational cost giving fair to excellent prediction for the impingement jet heat transfer coefficient. Many researchers considered shear-stress distribution, pressure distribution, the mean velocity profile, turbulent fluctuations for fluid flow problems, and the local Nusselt number and average Nusselt number for the heat transfer problem to check the performance of different models used compared with the available experimental data. As a result, researchers have found varying degrees of accuracy using different turbulence models to predict the fluid flow and heat transfer in an impinging jet. Because the fluid flow in an impinging jet is complex in nature owing to the presence of stagnation, recirculation, and wall jet regions, different models have resulted in different degrees of accuracy at different locations of the flow domain.

1.2 ARRAY OF SLOT JETS For distributed cooling (or heating) of an extended surface, multiple impinging jets can be used. In fact, impingement jet arrays have been more employed compared with other methods in industrial applications owing to the higher-removal heat flux with the lower energy consumption rate. Ebadian and Lin [14] compared the different methods of higheheat flux heat removal including microchannels, jet impingements, sprays, wettability effects, and piezo-electrically driven droplets. They found that jet impingement had higher heat flux removal than other cooling technologies. However, the flow structure for multiple and confined jet impingements is complicated because the spent fluid flow from upstream moves along the surface as a wall jet and then interacts with the downstream impinging jet flow. Fluid recirculates and degrades the heat transfer efficiency of the downstream jet. Experimental procedures and numerical analyses are two usual approaches to investigating the effective parameters of impingement jet arrays on the heat transfer of a heated surface. Gao [15] conducted an experimental investigation into multiple jet impingement and showed that the stagnation point of the Nusselt number for the downstream jet decreased by about 30%. Ozmen [16] performed an experimental study to investigate the effect of nozzle-to-plate spacing, jet-to-jet spacing, and the Re on pressure distribution for a confined twin impinging jet at high Re. It was found that pressure distribution was a function of nozzle-to-plate spacing and jet-to-jet spacing. Although multiple impinging cooling is effective for achieving distributed heat transfer, designing and analyzing these systems is much more complicated than for a single jet impingement system. The preceding studies did not consider the effect of air impingement jet arrays with nonidentical jet-to-jet spacing and slot jet widths on heat transfer from a heated plate. Shariatmadar et al. [17] carried out experiments and numerical

600

CHAPTER 2.22 DETERMINATION OF FLOW CHARACTERISTICS

analyses to investigate the effects of a number of slot jets with identical slot width and jet-to-jet spacing on the heat transfer mechanism for laminar flow. Average and stagnation Nusselt numbers were correlated as a function of independent dimensionless parameters for single jets and three different jet arrays tested with different jet-to-jet spacing and width values. This indicated that although the average Nusselt numbers are substantially independent of jet-to-jet spacing, they increase considerably with increments of the Re as well as jet width. In another study, Forouzanmehr et al. [18] developed a numerical algorithm to obtain the optimal configuration for four planar impinging slot jets to produce uniform heat flux along an isothermal heated flat plate; the results were verified experiments performed using a Mache-Zehnder interferometer. Afroz and Sharif [19] investigated convective heat transfer from an isothermally heated flat surface resulting from two-dimensional turbulent twin oblique confined slot jet impingement. The results showed that the SST k-u turbulence model agreed notably better with the experimental data. In that study, the flow characteristics and flow distribution patterns of a single slot jet as well as a multiple slot jet located at the upper wall of a twodimensional channel were analyzed numerically. The pressure distribution of the channel and the variation in skin friction coefficients along the impingement surface plate were also presented.

2. MATERIALS AND METHOD

2.1 DEFINITION OF THE PROBLEM The flow characteristics of single and multiple two-dimensional confined slot jet impingement on a plane surface were investigated numerically according to various flow and geometric parameters. Depending on the number of slot jet injections, the problem is schematically described in Fig. 2 as a single slot jet (Fig. 2A) or multiple slot jet (Fig. 2B) injection. For both configurations, flow characteristics were analyzed at various air flow rates ðRe ¼ Vinj Dh =nÞ, and at channel height ratios (H/L). In a flow analysis of multiple slot jets, however, the ratio of jet spacing to jet width (S/L) was kept constant at a value of 3.

2.2 GOVERNING EQUATION AND SOLUTION METHOD In determining the flow characteristics of confined slot jet impingement, the mass, momentum, and energy conservation equations for the steady incompressible flow, neglecting the viscous dissipation, are given as: v ðui Þ ¼ 0 vxi y

(A)

(1)

y

(B)

L

L H

Vinj symmetry

H x

symmetry

Vinj s

x

FIGURE 2 Schematic illustration of single slot jet and multiple slot jet flows. (A) Single slot jet and (B) multiple slot jet.

2. MATERIALS AND METHOD

601

" ! # v vp v vui vuj 0 0 ðui uj Þ ¼  þ þ m  rui uj vxj vxi vxj vxj vxi " # vT v m vT 0 0 ¼  rT uj ruj vxj vxj Pr vxj

(2)

(3) 0

0

where p, T, and uj are the mean pressure, temperature, and velocity components, respectively; T and uj are the fluctuating temperature and velocity components, respectively; xj is the coordinate direction; and r, m, and Pr are the fluid density, dynamic viscosity, and Prandtl number, respectively. The turbulent Reynolds stresses rui uj in Eq. (2) are calculated by an appropriate turbulence model for closure. The availability of the suitable turbulence model is an impediment in successfully predicting jet impingement flow and heat transfer. Several studies were published evaluating the performance of turbulence models, including the eddy viscosity, Reynolds stress transport, and LES models in the computation of turbulent jet impingement flow and heat transfer. Although many models represent the apparent turbulent stresses in Eq. (2), many authors have used turbulence modeling employing SST k-u for such confined flow problems [19]. The k-u model solves for turbulent kinetic energy (k) and energy dissipation rate per unit of turbulent kinetic energy (u), where u is determined through a conservation equation including experimentally determined functions, rather than direct calculation from the velocity field. The equations for u treat it as a vorticity level or vortex fluctuation frequency. The model then produces turbulent viscosity as a function of k and u. The k-u model typically produces Nu profiles with a local error of up to 30% of the experimental Nu value. It can produce better predictions of the turbulent length scale than the k-3 model. The k-u model can generate good predictions of flow properties in the wall jet in both the sublayer and logarithmic region without the need  for damping functions. The value of u at or near the wall-adjacent cell may be set proportional to n y2 , meaning that the user can fully specify the turbulence conditions at the wall, unlike in the k-3 model. Unfortunately, the k-u model is sensitive to far-field boundary conditions, much more so than the k-3 model. The low-Re k-u model gave good results by matching the shape of the experimental curves, but alternate formulations of the impinging jet CFD model using k-u with wall functions gave poor results: They replaced the k-u model with a cruder approximation in the very region where it gives the best results, overpredicting wall jet Nu by as much as 40%. Chen and Modi [20] successfully applied the k-u model for mass transfer at a high Schmidt number, and claimed agreement within 10% of experimental results, given very high grid densities. The addition of cross-diffusion terms in various k-u models succeeded in reducing its sensitivity to far-field u boundary conditions, a problem known to arise during use of the k-u model for unconfined or partially confined flows. With the inaccurate free-jet modeling, dense wall grid requirement, and undesirable sensitivity to unknown far-field conditions, one may conclude the k-u model is only moderately better than the k-3 it offers for better predictions of Nu, with a higher computational cost. In short, the standard k-u model can estimate near-wall flows well. Moreover, the standard k-ε model represents flow behavior better far from the wall. Hence, Menter [21] coupled these two turbulence models and generated the SST k-u model. Thus, the SST k-u model is more accurate and reliable for a wider class of flows that include adverse pressure gradient flows and flow over airfoils. Turbulence kinetic energy, k, and specific dissipation rate u, are obtained from the following transport equations: ! v v v vk fk  Yk þ Sk ðrkÞ þ ðrkui Þ ¼ (4) Gk þG vt vxi vxj vxj

602

CHAPTER 2.22 DETERMINATION OF FLOW CHARACTERISTICS

v v v ðruÞ þ ðruuj Þ ¼ vt vxj vxj

vu Gu vxj

! þ Gu  Yu þ Du þ Su

(5)

where model constants and source terms of the right-hand side of Eqs. (4) and (5) can be reached in the ANSYS Fluent User Manual [22]. Eqs. (1)e(5) are solved with the aid of ANSYS Fluent software. The software is based on the control volume approach of Patankar [23]. The QUICK scheme developed by Leonard [24] is applied for discretization of convective terms and the SIMPLE algorithm [25] is adapted to solve momentum and continuity equations. The enhanced wall treatment is adopted. Convergence criteria for all conservation equations are taken to be 1  106 in the analysis.

2.3 BOUNDARY CONDITIONS AND MESH INDEPENDENCY Because of the symmetry of the flow, the gradients of all transport properties have to be zero at the symmetry surface, vf=vxjx¼X=2 ¼ 0. No slip condition at the walls is satisfied by (u ¼ v)wall ¼ 0. The velocity (Vinj) profiles at the exit surfaces of slot sections in the computational domain are assumed to be uniform. The injection velocity (Vinj) depends on the Re [Vinj ¼ f(Re)]. The turbulence intensity of jet flow is assumed to be 2% in the analysis. At the outlet section, the pressure is specified to be at atmospheric pressure. In addition, the mass flow rate evaluated at the channel outlet has to be compared with the total flow rate through the injection slots at the upper wall. A deviation of less than 1% is allowed in the computations. Table 1 provides details on the boundary conditions used for the analysis. To demonstrate that the numerical results are free of the mesh size, a single slot jet impingement at a geometry of H/L ¼ 2 and jet Re ¼ 31,600 are studied for four different mesh densities as follows: Case A (fine): 1364  220, Case B (medium): 1111  180, Case C (coarse): 781  128 and Case D (crude): 543  92 (Table 2). As shown in Fig. 3, the computational domain is divided into nonuniform quadrilateral grids. To capture the velocity and pressure gradients at a region close to the stagnation point, fine grids are generated. In addition, the occurrence of secondary humps between two adjacent jets requires a fine grid distribution of a multiple jet impingement in that region. Wall functions based on some empirical formulas are used to bridge the wall and the logarithmic region without providing grids in between. As indicated in the following section, Case B provides results with negligibly small discrepancy with respect to Case A. Therefore, Case B type mesh distribution is determined to be applicable for the analysis.

Table 1 Boundary Conditions for the Numerical Analysis Boundary Type

Velocity

Upper wall at jet injection sections Outflow (pressure outlet) Walls (no slip) Symmetry line

u ¼ 0; v ¼ Vinj vu vx

¼ 0;

Pressure

vv vy

¼0

u ¼ 0; v ¼ 0 vu vx

¼ 0;

vv vy

¼0

vp vx

¼ 0;

vp vy

Mass Conservation

¼0

m_ outflow ¼

P i

m_ jet

 i

3. RESULTS AND DISCUSSIONS

603

Table 2 Mesh Size Distribution for Single Jet Cases

Horizontal (x) Direction

Vertical (y) Direction

Total Number of Meshes

A B C D

1364 1111 781 543

220 180 128 92

300,080 199,980 99,968 49,956

(A)

(B) 2

y/L

y/L 1

0

L

L/2

L/2 2

1

0

1

2

3

x/L

4

0

0

1

2

3

x/L

4

FIGURE 3 Computational domain grid distribution. (A) Single slot and (B) multiple slot.

3. RESULTS AND DISCUSSIONS 3.1 VALIDATION OF METHODOLOGY

Because of similar geometry and flow conditions, the work of Afroz and Sharif [5] was used to determine the most appropriate turbulence model and wall function for the current study. Five different turbulence model and wall function pairs including the SST k-u model, realizable k-ε, and RNG k-ε models were examined and tested. In studying the realizable k-ε and RNG k-ε turbulence models, both standard and enhanced wall functions were considered to capture near-wall effects. In comparing the models, variations in heat transfer coefficients along the heated surface were analyzed for two different Reynolds numbers of injection. In the analysis, the mesh distribution for Case A was determined to be appropriate. As depicted in Fig. 4, the SST k-u turbulence model predicted the results of the reference work more accurately than did the other models and was used for the current analysis. As shown in Fig. 5, the previously decided four cases of mesh size were compared in terms of nondimensional pressure p ¼ p=p0 and skin friction coefficient distributions, cf ¼ rVs2w 2, along the inj = impingement plate using the selected SST k-u turbulence model. In comparing the pressure distributions, no essential difference existed among the cases studied. However, in the skin friction coefficient, deviations were noticed in results, especially at a region close to the stagnation point. For identifying and locating the peak value of skin friction, Cases A and B performed better than the other cases. Because the discrepancy between the results of Cases A and B were negligibly small, Case B is

604

CHAPTER 2.22 DETERMINATION OF FLOW CHARACTERISTICS

(A)

(B)

200

300 Afroz and Sharif (2013) SST k-w RNG k-e / Standart RNG k-e / Enhanced Realizable k-e / Standart Realizable k-e / Enhanced

200

Nu

Nu

150

Afroz and Sharif (2013) SST k-w RNG k-e / Standart RNG k-e / Enhanced Realizable k-e / Standart Realizable k-e / Enhanced

100

100 50

0 0

5

10 X

15

0

20

0

5

10 X

15

20

FIGURE 4 Effect of turbulence models on Nusselt number of a heated surface for free jet impingement at two different Reynolds numbers (Re). (A) Re ¼ 23,000 and (B) Re ¼ 50,000. RNG, renormalization group; SST, shear-stress transport.

(A)

(B)

1.2

0.02 Case A Case B Case C Case D

0.8

Case A Case B Case C Case D

0.015

Cf

P*

0.4 0.01

0 0.005

-0.4 -0.8

0 0

5

10 X

15

20

0

5

10 X

15

20

FIGURE 5 Comparing the pressure drop and the skin friction results in different mesh sizes. (A) Nondimensional pressure distribution and (B) variation in skin friction coefficient.

preferred for parametric studies. After determining the optimum mesh density, meshes were generated for all of the geometric configurations studied. Depending on the number of slots and the jet aspect ratio (H/L), the mesh number at each particular flow geometry is provided in Table 3.

3.2 PARAMETRIC RESULTS To evaluate and assess the effect of jet velocity on flow behavior, the flow Re was defined with respect to the hydraulic diameter of slot-jet as Re ¼ Vinj Dh =n, where Dh ¼ 2L for a two-dimensional slot jet configuration. The comparison of pressure distribution, span-wise velocity distribution, span-wise

3. RESULTS AND DISCUSSIONS

605

Table 3 Mesh Details for All Geometric Configurations Studied Slot Type Single slot jet Multiple slot jet

H/ L

Horizontal (x) Direction

Vertical (y) Direction

Total Number of Meshes

2 4 6 2 4 6

1111 1111 1111 1305 1305 1305

180 360 540 180 360 540

199,980 399,960 599,940 234,900 469,800 704,700

turbulence profiles, shear stress distribution, and the law of the wall in terms of flow behavior comprised the first part of the study. In the analysis, to reflect the effect of jet velocity, the Re assumed values of 5900, 21,000, and 31,600. In singleeslot jet analysis, Fig. 6 represents the flow patterns of three different jet aspect ratios at a constant Re of 5900. A recirculating bubble developed in the flow domain. This bubble was encompassed by the top adiabatic wall and main jet stream, and by the deflected wall jet at the bottom. As in Fig. 6, increasing the aspect ratio, H/L, increased the size of the recirculation bubble. The fluid lost the axial velocity as it approached the impingement plate and came to rest at the impingement point. The flow then proceeded parallel to the wall where the pressure gradient caused the axial velocity to accelerate and attain a maximum at the edge of the stagnation region. Beyond this point, the axial velocity gradually decreased in the downstream direction. The reattachment length and position of the counter-rotating vortex in the recirculation zone are the two important characteristics of the flow field of an impinging jet. As the jet impinges on the impingement wall, a counter-rotating vortex is generated adjacent to the jet because of the dual effect of jet entrainment and the confinement wall. The vortex is sustained in the recirculation region by extracting kinetic energy from the jet.

(A) (B)

(C)

FIGURE 6 Effect of height ratio on the size of recirculation zone for single jet flow at Reynolds number (Re) ¼ 5900. (A) H/ L ¼ 2, (B) H/L ¼ 4, and (C) H/L ¼ 6.

606

CHAPTER 2.22 DETERMINATION OF FLOW CHARACTERISTICS

FIGURE 7 Streamlines for multiple slot jet flow for H/L ¼ 6, S/L ¼ 3 and Reynolds number (Re) ¼ 5900.

In studying the multiple slot jet configurations, the jet spacing parameter, S/L, is kept constant at 3. However, the effect of jet aspect ratio, H/L, is varied by considering the aspect ratios of 2, 4, and 6. The flow patterns for the triple slot jet impingement case is shown in Fig. 7, in which the jet Re ¼ 5900 and the geometric parameters of the channel are taken to be H/L ¼ 6 and S/L ¼ 3. The flow structure given in Fig. 7 is due to identical flow rates of injection at each slot of the upper wall. It can be seen that the multiple slot jet flow structure is much more complicated owing to the interaction of the spent flow of the upstream jet with the downstream jet. The main recirculation bubble still exists at the downstream region after the second injection slot. However, because of the interaction of the wall jet with the impinging jet, the flow between two adjacent jets becomes complicated and recirculation bubbles are generated. Fig. 8 illustrates the skin friction coefficient distribution over the lower surface of the channel resulting from a single slot jet located at the symmetry line of the upper surface. In this figure, both the effect of the flow Re and the jet aspect ratio on surface friction are analyzed. At a particular height ratio of (H/L), an increase in the Re decreases the peak value of the friction coefficient that occurs in one slot-width distance from the symmetry line and then monotonically decreases. As expected, an increase in the height ratio at a specified flow Re results in a decrease in the peak value of the friction coefficient. A typical skin friction variation on the lower surface of the channel with three slots located at the upper wall is illustrated in Fig. 9 at the same geometric conditions of H/L ¼ 6 and S/L ¼ 3. In this figure, the air injection velocity at the inlet of each slot is taken to be identical. Because of the interaction of the wall jet with the downstream impinging jet, a secondary peak takes place at the downstream section. The magnitude of the secondary peak is always less than the peak generated by the first slot, and in fact it becomes flattened as the Re increases. The increase in the Re does not change the location of the secondary hump, but it decreases its intensity. For a single slot jet impingement, Fig. 10 shows the pressure distribution profile along the channel, starting from the channel symmetry (stagnation line) and ending at the channel exit. As mentioned, the slot jet is located at the symmetry line of the channel, and then the effects of the slot jet flow rate and the channel aspect ratio on pressure distribution are explained in Fig. 10. The flow structure affects the pressure distribution along the impingement surface. The jet velocity rapidly decreases in the region near the impingement plate otherwise known as the deflection zone, with a corresponding rise in the static pressure. The velocity at the stagnation point becomes zero, giving rise to the maximum static pressure. Then the pressure decreases along the streamwise direction as the flow accelerates along the impingement surface. The pressure is normalized by the maximum pressure on the surface that is at the stagnation point. The normalized pressure follows a Gaussian distribution, as mentioned in the experimental work of Tu and Wood [26]. This is evident from the fact that the maximum value of p/pmax is 1 at the stagnation point (X ¼ 0). All of the computational results have a close trend with the

3. RESULTS AND DISCUSSIONS

(A)

607

(B)

0.03

0.03

Re = 5900 Re = 21000 Re = 31600

Re = 5900 Re = 21000 Re = 31600

0.02

Cf

Cf

0.02

0.01

0.01

0

0 0

5

10 X

(C)

15

20

0

5

10 X

15

0.03 Re = 5900 Re = 21000 Re = 31600

Cf

0.02

0.01

0 0

5

10 X

15

20

FIGURE 8 Effect of Reynolds number (Re) and height ratio on skin friction coefficient for confined single jet injection. (A) H/L ¼ 2, (B) H/L ¼ 4, and (C) H/L ¼ 6. 0.05 Re = 5900 Re = 31600

0.04

Cf

0.03 0.02 0.01 0 0

5

10 X

15

20

FIGURE 9 Variations in lower surface skin friction for a channel with multiple jets, H/L ¼ 6 and S/L ¼ 3, and at two different Reynolds numbers (Re).

20

608

CHAPTER 2.22 DETERMINATION OF FLOW CHARACTERISTICS

(A)

(B)

1.2

1.2 H/L=2 H/L=4

0.8

H/L=6

0.4

H/L=6

0.4

P*

P*

H/L=2 H/L=4

0.8

0

-0.4

0

-0.4

-0.8

-0.8 0

5

10 X

(C)

15

20

0

5

10 X

15

20

1.2 H/L=2 H/L=4

0.8

H/L=6

P*

0.4 0

-0.4 -0.8 0

5

10 X

15

20

FIGURE 10 Effect of height ratio on pressure variation for a single jet configuration at various Reynolds numbers (Re). (A) Re ¼ 5900, (B) Re ¼ 21,000, and (C) Re ¼ 31,600.

experimental results for the case of H/L ¼ 4, up to a downstream location of X ¼ 8, beyond which the computational results deviate from the experimental values and give some overprediction. Compared with the overall pressure distributions in Fig. 10AeC, variation in the flow Re does not have an influence on the pressure distribution for the range of Re studied. In a range extending a few slot widths from the stagnation line, the drop in pressure to negative values reflects typical single jet characteristics. Moreover, the occurrence of a positive pressure gradient after the minimum supports the existence of a recirculation zone. The variation in the channel height ratio certainly affects the pressure distribution. As the height ratio increases, the negative pressure zone extends in the downstream direction and the size of recirculation zone enlarges. The variation in pressure in the channel for triple slot jet impingement is shown in Fig. 11. In this figure, two aspect ratios, H/L ¼ 2 and 6, are considered to determine the effect of the height ratio on pressure, but the slot spacing is kept constant at S/L ¼ 3. Fig. 11 shows that the flow Re modifies the pressure profile in multiple slot jet impingements. As the flow rate increases, the slopes at several

4. CONCLUSIONS

(A)

609

(B) 1.2

1.2 Re = 5900 Re = 31600

0.8

Re = 5900 Re = 31600

0.8

0.4

P*

P*

0.4 0

0

-0.4 -0.4

-0.8

-0.8

-1.2 0

5

10 X

15

20

0

5

10 X

15

20

FIGURE 11 Effect of Reynolds number (Re) on pressure variation of a channel with multiple slot jets, S/L ¼ 3, and at two different height ratios. (A) H/L ¼ 2 and (B) H/L ¼ 6.

sections of the distribution curve become steeper. The existence of a secondary peak in the pressure profile is solely due to injection through the adjacent jet. As indicated in Fig. 11B, the discrepancy due to the effect of the Re becomes less effective as the height ratio increases.

4. CONCLUSIONS Research on the impinging jet specifically needs a turbulence model and associated wall treatment that reliably and efficiently provides time-averaged velocity and pressure distribution for impinging jet flow fields. Apparently, the SST k-u model offers good results for the least amount of computation time. The improved turbulence model must correctly predict jet spreading, turbulent flow effects in the stagnation region, and turbulent flow properties along the wall. Under these considerations, the flow characteristics of a channel with three equally spaced and identical slots located at the upper wall were investigated numerically using ANSYS Fluent CFD code. The jet velocity at each slot exit was taken to be identical for all cases studied. Hence the flow is symmetric with respect to the centerline of the mid slot and flow symmetry is taken into account in the analysis. The main objective of this study was to investigate the effect of multiple slot jet impingement on channel flow characteristics. In the case of a single normal impinging jet flow, the major pressure drop is concentrated near the stagnation region. However, in multiple jet flows, pressure drop is distributed along the channel. In the analysis, two parameters, the injection flow rate through the slots (Re) and the channel height ratio (H/L), were altered so that the resulting effect on the flow behavior was recorded by the considering the flow streamlines, the friction factor at the bottom surface of the channel, and the nondimensional pressure distribution. Close examination of the local friction coefficient distribution and the pressure distribution plots for the multiple injection case revealed that a secondary hump took place at the downstream section after the second injection slot. Hence, in addition to recirculation bubble caused by a single-slot jet, a circulatory zone existed between two adjacent slots of the channel.

610

CHAPTER 2.22 DETERMINATION OF FLOW CHARACTERISTICS

NOMENCLATURE cf Dh H L k p Re S Vinj u,v X Y x,y

Skin friction coefficient, dimensionless Hydraulic diameter of the slot jet (m) Channel height (m) Width of a slot jet (m) Kinetic energy of turbulence (m2/s2) Pressure (Pa) Reynolds number ðVinj Dh =nÞ Slot jet spacing (m) Velocity of air at the slot inlet (m/s) Velocity components (m/s) Horizontal distance, dimensionless (X ¼ x/L) Vertical distance, dimensionless (Y ¼ y/L) Cartesian axis directions

Greek Letters

r sw n m G u

Density of the fluid (kg/m3) Shear stress on the wall (kg/ms2) Kinematic viscosity (m2/s) Viscosity (Pas) Effective diffusivity (m2/s) Specific dissipation rate

Superscripts 

Dimensionless

Subscripts inj o

Jet injection Stagnation line, x ¼ 0

REFERENCES [1] Zuckerman N, Lior N. Impingement heat transfer: correlations and numerical modeling. Journal of Heat Transfer. ASME Transactions May 2005;127:544e52. [2] Zhou DW, Lee SJ. Heat transfer enhancement of impinging jets using mesh screens. International Journal of Heat and Mass Transfer 2004;47(10e11):2097e108. [3] Dewan A, Dutta R, Srinivasan B. Recent trends in computation of turbulent jet impingement heat transfer. Heat Transfer Engineering 2012;33:447e60. [4] Maurel S, Solliec C. A turbulent plane jet impinging nearby and far from a flat plate. Experiments in Fluids 2001;31:687e96. [5] Beaubert F, Viazzo S. Large eddy simulations of plane turbulent impinging jets at moderate Reynolds numbers. International Journal of Heat and Fluid Flow 2003;24:512e9. [6] Hattori H, Nagano Y. Direct numerical simulation of turbulent heat transfer in plane impinging jet. International Journal of Heat and Fluid Flow 2004;25:749e58.

REFERENCES

611

[7] Craft TJ, Graham LJW, Launder BE. Impinging jet studies for turbulence model assessment II, an examination of the performance of four turbulence models. International Journal of Heat and Mass Transfer 1993; 36(10):2685e97. [8] Seyedein SH, Hasan M. Modeling of a single confined turbulent slot jet impingement using various k-ε turbulence models. Applied Mathematical Modelling 1994;18:526e37. [9] Hosseinalipour SM, Mujumdar AS. Comparative evaluation of different turbulence models for confined impinging and opposing jet flows. Numerical Heat Transfer: Part A 1995;28:647e66. [10] Ichimiya K, Hosaka N. Experimental study of heat transfer characteristics due to confined impinging two-dimensional jets (heat transfer experiment for three slot jets). The Japan Society of Mechanical Engineers: Part B 1989;55:3210e5. [11] Yap CR. Turbulent heat and momentum transfer in recirculating and impinging flows. Faculty of Technology, University of Manchester; 1987 [PhD thesis]. [12] Angioletti M, Nino E, Ruocco G. CFD turbulent modeling of jet impingement and its validation by particle image velocimetry and mass transfer measurements. International Journal of Thermal Sciences 2005;44(4): 349e56. [13] Zuckerman N, Lior N. Jet impingement heat transfer: physics, correlations, and numerical modeling. Advances in Heat Transfer 2006;39:565e631. [14] Ebadian MA, Lin CX. A review of high-heat-flux heat removal technologies. Journal of Heat Transfer 2011; 133:110801. [15] Gao X. Experimental investigation of the heat transfer characteristics of confined impinging slot jets. Experimental Heat Transfer 2003;16:1e18. [16] Ozmen Y. Confined impinging twin air jets at high Reynolds numbers. Experimental Thermal and Fluid Science 2011;35:355e63. [17] Shariatmadar H, Momeni A, Karimi A, Ashjaee M. Heat transfer characteristics of laminar slot jet arrays impinging on a constant target surface temperature. Applied Thermal Engineering 2015;76:252e76. [18] Forouzanmehr M, Shariatmadar H, Kowsary F, Ashjaee M. Achieving heat flux uniformity using an optimal arrangement of impinging jet arrays. Journal of Heat Transfer 2015;137. [19] Afroz F, Sharif MAR. Numerical study of heat transfer from an isothermally heated flat surface due to turbulent twin oblique confined slot-jet impingement. International Journal of Thermal Sciences 2013;74: 1e13. [20] Chen Q, Modi V. Mass transfer in turbulent impinging slot jets. International Journal of Heat and Mass Transfer 1999;42:873e87. [21] Menter FR. Two-equation eddy-viscosity turbulence models for engineering applications. AIAA Journal 1994;32:1598e605. [22] ANSYS-fluent 14.0 user guide. ANSYS Inc.; 2011. [23] Patankar SV. Numerical heat transfer and fluid flow. New York: Taylor & Francis; 1982. [24] Leonard BP. Order of accuracy of QUICK and related convection diffusion schemes. Applied Mathematical Modelling 1995;19:640e53. [25] Patankar SV, Spalding DV. A calculation procedure for heat, mass and momentum transfer in threedimensional parabolic flows. International Journal of Heat and Mass Transfer 1972;15:1787e806. [26] Tu CV, Wood DH. Wall pressure and shear stress measurements beneath an impinging jet. Experimental Thermal and Fluid Science 1996;13:364e73. [27] Kayansayan N. An experimental study of two-dimensional impingement cooling. College of Engineering, The Ohio State University; 1978 [PhD thesis].

CHAPTER

A NUMERICAL STUDY ON PHASE CHANGE INSIDE A SPHERICAL CAPSULE

2.23

Ersin Alptekin, Muhammet O¨zer, Murat Top, Fazıl Erinc¸ Yavuz, Mehmet A. Ezan

_ Dokuz Eylul University, Izmir, Turkey

1. INTRODUCTION The intensity of solar radiation varies throughout the daytime and is unavailable during the night. The transient nature of renewable energy resources such as the wind and sun makes it impossible to build a continuous power generation system without an additional storage unit. Thermal energy storage (TES) systems can be integrated into systems such as solar heating, cooling, and power generation to store (charge) excess energy while the energy input is available, and then release (discharge) the stored energy when the energy resource is not accessible. Implementation of TES units into solar systems maintains a continuous heat supply so that problems that may arise from intermittent natural, renewable energy resources can be resolved. TES simply means storing (or releasing) thermal energy into (or from) a medium. It is well known from thermodynamics that energy storage in a medium is directly related to the variation in internal energy of a material. Internal energy consists of sensible, latent, chemical, and nuclear forms of energy [1]. Fig. 1 compares the required volume of materials to store 10 MJ of thermal energy within sensible heat, latent heat, thermochemical sorption, and thermochemical reaction TES units [2]. It is clear that the medium with the highest amount of storage is used in the case of sensible heat TES. The most attractive TES method regarding dedicated space, on the other hand, is the thermochemical reaction. However, as stated by Pintaldi et al. [2], thermochemical energy storage materials are currently under research and development. Among the others, sensible heat and latent heat TES (LHTES) applications are widely used and relatively mature technologies. From Fig. 1, it is clear that in an LHTES system, a higher amount of thermal energy could be stored in a small to medium TES compared with a sensible heat TES. The underlying reason is that the energy storage in an LHTES is provided by the phase change of the storage medium. The storage materials used in the LHTES system are known as phase-change material (PCM) because they change phase in the process. phase-change material a practical application because it requires reinforced storage tanks that can resist high-pressure variations. Instead, solid to liquid phase change is widely used to store or release thermal energy in a medium with a small change in volume. There are two main challenges in the field of LHTES systems. The first is in designing a suitable heat exchanger that can provide a higher heat transfer rate between the heat transfer fluid (HTF) and Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00035-4 Copyright © 2018 Elsevier Inc. All rights reserved.

613

614

CHAPTER 2.23 PHASE CHANGE INSIDE A SPHERICAL CAPSULE

FIGURE 1 Comparison of different thermal energy storage methods regarding the required volume. Reproduced from Pintaldi S, Perfumo C, Sethuvenkatraman S, White S, Rosengarten, G. A review of thermal energy storage technologies and control approaches for solar cooling. Renewable and Sustainable Energy Reviews 2015;41:975e95.

the PCM. The second is to develop a proper PCM that has enhanced thermal properties, to reduce the required cycle durations for charge or discharge. Numerous studies have been conducted in the literature related to the design of heat exchangers, investigating the influence of working conditions of HTF and developing or characterizing PCMs. Erek and colleagues have worked on LHTES systems and the development and characterization of PCM candidates. In earlier work, in 2005, Erek et al. [3] developed a numerical model to predict the solidification process of water for bare and finned tubes. They validated their code with the results of experimental findings. Further parametric study was been carried out to discover the effect of working parameters and the spacing between fins on the phase change process. Erek and Ezan [4] considered a real-size LHTES system in which water was used as the PCM. They developed a numerical code in FORTRAN language and validated their predictions regarding the experimental measurements. Erek and Dincer [5,6] proposed a new numerical approach for entropy- and exergybased analyses for LHTES systems. On the other hand, Ezan et al. [7] represented the experimental findings of a shell and tubeetype LHTES system regarding the energetic and exergetic aspects. Ekren et al. [8] built an experimental unit that included a water tank and a chiller as a real-size LHTES system. They investigated the effect of control schemes on the thermal stability and performance (coefficient of performance) of the unit. Ezan and Erek [9] experimentally studied solidification and melting periods in a real-size LHTES system. Internal and external melting scenarios were compared under various heating load conditions. Ezan et al. [10] developed a numerical code to simulate transient heat transfer including phase change in a real-size LHTES system. They validated the code by comparing predictions against their experiments. Further numerical analyses were

1. INTRODUCTION

615

conducted to reveal the energetic and exergetic aspects of the LHTES system. Ezan et al. [11] proposed a numerical scheme in ANSYS-Fluent software to predict natural convection-driven phase change inside a rectangular cavity. They concluded that the effect of natural convection becomes dominant in the early stages of the process. Ezan et al. [12] extended their previous model and applied it in cylindrical geometry. They simulated the natural convection-driven solidification of water around a tube. The predicted results were compared against the experimental measurements. The time-wise variations of the interface position and local and average Nusselt numbers were represented for various boundary conditions. Other researchers focused on the enhancement of thermal properties of PCMs. Seki et al. [13] developed a eutectic PCM consisting of adipic acid and sebacic acid. The melting temperature of the proposed PCM was 116
C. The thermal conductivity of the eutectic mixture was improved by loading graphene nano platelets (GNPs). On the other hand, _ Seki et al. [14] and Ince et al. [15] prepared nano-enhanced PCMs using arachidic acid (AA) and myristic acid (MA), respectively. Results revealed that the thermal conductivity of AA increased by 45% by incorporating 2% of GNP. The thermal conductivity of MA improved by 38% by loading 2% of GNP. PCMs are placed into reservoirs that have Cartesian, cylindrical, or spherical geometries. Bedecarrats et al. [16] claimed that spherical capsulation has the best performance among other geometries because it is easy to use and has a greater effective surface area compared with the PCM and the HTF. Be´de´carrats et al. [17] experimentally investigated the performance of an encapsulated energy storage unit during the solidification and melting periods under varying working conditions. Tan et al. [18] developed a numerical model in ANSYS-Fluent software to simulate natural convection-driven phase change. The formation of conduction- and convection-dominated zones were discussed, and predicted temperature variations were compared with the experimental findings. Although solving coupled governing equations, continuity, momentum, and energy gives a better understanding and more realistic outcomes, it is a time-consuming procedure. Ismail et al. [19] developed a numerical code in which they included the effect of natural convection as enhanced thermal conductivity. It was proven that with the definition of effective thermal conductivity, the total computational time was significantly reduced without a loss of accuracy regarding the total time for complete solidification. Veerappan et al. [20] developed a one-dimensional numerical model to simulate phase change inside a spherical capsule. They showed that the definition of enhanced thermal conductivity increased the accuracy of the model, and the predictions became closer to experimental ones. Ezan et al. [21] developed a correlation for the enhanced thermal conductivity of water inside a spherical capsule regarding the temperature difference and the position of the interface. They implemented the relationship into a onedimensional numerical model and compared the results of the simulation with the experimental measurements. The accuracy of the one-dimensional model improved using enhanced thermal conductivity. This chapter primarily aims to implement the definition of enhanced thermal conductivity into the commercial computational fluid dynamics solver ANSYS-Fluent. Moreover, a numerical survey was conducted to discuss the influence of the free stream temperature and convective heat transfer coefficient value on the time-wise variation of melting inside a spherical capsule with or without considering the definition of enhanced thermal conductivity. For this purpose, a two-dimensional model is considered, and the numerical approach is validated by comparing the predictions against the results from the literature.

616

CHAPTER 2.23 PHASE CHANGE INSIDE A SPHERICAL CAPSULE

2. MATERIALS AND METHODS

2.1 CHARACTERIZATION OF THE PHASE-CHANGE MATERIAL In the numerical analyses, a commercial paraffin wax is considered as the PCM. Thermal characterization analysis of the PCM is conducted with a differential scanning calorimeter (DSC) to determine the melting temperature, and the heat of the fusion (latent heat) of the material is analyzed with a Perkin Elmer Diamond DSC; the results are examined with Pyris 7.0 software. Six milligrams of paraffin sample is encapsulated in an aluminum pan and placed in the furnace. Experiments are conducted in a nitrogen atmosphere. The sample is heated from 0
C to 100
C at a rate of 10
C/min and held at 100
C for 1 min. The sample is then cooled to 0
C at a rate of 10
C/min. The results for heating and cooling cycles are given in Fig. 2A and B, respectively. Two endothermic peaks are observed during the melting process: between 24.8
C and 32.7
C, and between 47.45
C and 53.50
C. The former is relatively small and is probably observed

FIGURE 2 Thermograms for paraffin sample (A) heating cycle (B) cooling cycle.

2. MATERIALS AND METHODS

617

Table 1 Thermophysical Properties of Paraffin Property

Value

r (kg/m ) k (W/m K) c (J/kg K) hsf (J/kg)

772 0.148 2160 130.87 kJ/kg

3

because of impurities in the commercial material. The latter, on the other hand, corresponds the melting range of the material. The area underneath the peak is calculated to evaluate the heat of fusion. Similarly, two exothermic peaks occur during the solidification process. The solidification range is obtained to be 49.83
C to 42.03
C. The values for the heat of fusion for the melting and solidification processes are evaluated as 130.87 and 127.31 kJ/kg, respectively. The remaining properties of the material, which are necessary for the numerical model, are obtained from the literature and are given in Table 1.

2.2 DEFINITION OF THE PROBLEM In the current problem, solar thermal energy storage inside a spherical container is considered. During the daytime, the heat transfer fluid passes around the spheres at a temperature that is higher than the melting temperature of the PCM; thus an inward melting process takes place. During the nighttime, on the other hand, relatively cold HTF at a temperature lower than the phase-change temperature passes around the spheres and causes inward solidification. The schematic of the system is given in Fig. 3. The working and design parameters of the process should be specified in such a way that the durations of charge and discharge meet the requirements. Only a single spherical capsule is considered to understand the transient heat transfer phenomenon inside the LHTES unit. The problem is reduced into an axisymmetric two-dimensional geometry, as

FIGURE 3 Schematic of a solar thermal energy storage unit. PCM, phase-change material.

618

CHAPTER 2.23 PHASE CHANGE INSIDE A SPHERICAL CAPSULE

FIGURE 4 Two-dimensional mathematical model. PCM, phase-change material.

given in Fig. 4. On the outer wall, a convective heat transfer boundary condition is defined. The mathematical expressions of the boundary conditions are: vT r ¼ 0/  k ¼0 (1) vr r¼0 vT r ¼ ro /  k ¼ hðT  TN Þ (2) vr r¼ro In the current model, the inner radius of the sphere is 0.03 m with a wall thickness of 2 mm. The wall material is given as Pyrex glass.

2.3 SOLUTION METHOD It is assumed that natural convection inside the sphere is neglected. The effect of natural convection is implemented into the model using enhanced thermal conductivity. ANSYS-Fluent software solves the following energy equation for a spherical domain:     v 1 v vT 1 v vT ðrcTÞ ¼ 2 kr 2 þ 2 k sin q (3) vt r vr vr r sin q vq vq The thermophysical properties of the PCM are defined to be identical in each phase (solid and liquid) of the PCM (Table 1). The enthalpy-porosity method of Voller and Swaminathan [22] is used to incorporate a phase-change effect in the energy equation. The two-dimensional and axisymmetric computational domain is divided into 18,400 quadrilateral cells. After a preliminary survey on the time-step size sensitivity analysis, the optimum time step is obtained as 1 s. The convergence criterion is defined as 108.

3. RESULTS AND DISCUSSION

619

Neglecting the natural convection inside the sphere may cause unrealistic results. Enhanced thermal conductivity is a simple way to include the effect of natural convection in a conduction-based analysis. Two different approaches are followed in this study: (1) conduction-based studies, and (2) enhanced thermal conductivity studies. In conduction-based studies, thermal conductivity is assumed to be constant during the process. In an enhanced thermal conductivity approach, thermal conductivity is defined as:  0:252 keff 0:228 Dr ¼ 0:202RaDr Pr0:029 (4) ro kl where kl is the thermal conductivity of the liquid phase without convection and keff is the enhanced (effective) thermal conductivity. The Rayleigh number (Ra) is defined regarding the liquid spacing (Dr) and the temperature difference between the interface and the inner wall as: RaDr ¼ gb

DTDr 3 va

(5)

The liquid spacing (Dr) is the difference between the inner radius and the equivalent interface position (req). Three subroutines are coded in Cþþ language and interpreted into ANSYS-Fluent software to calculate enhanced thermal conductivity. At the end of each time step, the volume-averaged liquid fraction is computed to obtain the spacing that is filled with the liquid PCM (Dr). An additional function calculates the area weighted average of the inner wall temperature. Two subroutines share the related information to the property function in which enhanced thermal conductivity is evaluated according to Eq. (4). Because the Rayleigh number varies over time, the thermal conductivity of the liquid phase can change with time.

2.4 VALIDATION OF THE MODEL

_ The work of Bilir and Ilken [23] is reproduced to validate the numerical solution method. In that model, a spherical capsule with a diameter of 0.06 m is filled with water, initially at 25
C. The capsule is then dropped into a cold liquid bath and inward solidification is observed. It is assumed that the liquid temperature and the convective heat transfer coefficient between the liquid and the outer wall of the sphere are both constant. The liquid temperature is at 10
C and convective heat transfer coefficient is 218.7 W/m2 K. The properties of water are defined according to the data given in Bilir [24]. In _ Fig. 5, current predictions are compared with results given in Bilir and Ilken [23]. The solid red curve represents the results of the reference work, and the dashed line is the current predictions. The current results match with the reference work. In the reference work, some temperature fluctuations may arise during the initial period because of the mesh size; they subsequently disappear. In the case of the current model, an almost smooth variation in temperature is obtained.

3. RESULTS AND DISCUSSION A total of 12 parametric analyses were conducted to discuss the influence of the free stream temperature and convective heat transfer coefficient, and the definition of the enhanced thermal conductivity of the PCM on transient heat transfer inside a spherical capsule.

620

CHAPTER 2.23 PHASE CHANGE INSIDE A SPHERICAL CAPSULE

FIGURE 5 Comparison of the current results with the reference work.

3.1 EFFECT OF FREE STREAM TEMPERATURE Fig. 6 shows the influence of free stream temperature on the time-wise variations of the surface temperature and the liquid fraction inside the PCM domain. In the current analyses, the convective heat transfer coefficient is defined as 100 W/m2 K. In the figures, the solid curves represent the conduction mode and the dashed ones correspond to analyses in which an effective (enhanced) thermal conductivity approach is implemented. One can infer that increasing the free stream temperature improves heat transfer and reduces the time for complete melting, as expected. Fig. 6A shows that the wall temperature of the sphere tends to decrease the conduction-dominated analyses. In contrast, it is clear that the definition of keff enhances the heat transfer and the curves have positive slopes. Enhanced thermal conductivity is directly proportional to the temperature difference between the wall and the interface. That is, the slope of the curves increases as the temperature difference increases. The differences between the constant and enhanced conductivity definitions become apparent when the temperature difference between the free stream and melting temperatures is increased. It is evident that for higher free stream temperatures, the errors that may arise by neglecting the convection effects inside the sphere become significant. In Fig. 6B, on the other hand, the time-wise variations of the liquid fraction values are given. The required time to complete melting is reduced by almost one-half for Tm þ 30
C and Tm þ 20
C when enhanced thermal conductivity is implemented. It is clear that neglecting the convection effects causes significant underestimations regarding the liquid fraction even for Tm þ 10
C.

3. RESULTS AND DISCUSSION

FIGURE 6 Effect of free-stream temperature on phase change inside the sphere: (A) surface temperature and (B) liquid fraction.

621

622

CHAPTER 2.23 PHASE CHANGE INSIDE A SPHERICAL CAPSULE

FIGURE 7 Effect of convective heat transfer coefficient on phase change inside the sphere: (A) surface temperature and (B) liquid fraction.

NOMENCLATURE

623

3.2 EFFECT OF HEAT TRANSFER COEFFICIENT Fig. 7 represents the effect of the convective heat transfer coefficient on the surface temperature of the sphere and the liquid fraction of the PCM. Increasing the heat transfer coefficient reduces thermal resistance between the outer wall and the free stream so that the heat transfer is enhanced. Fig. 7A shows the variations in surface temperature for constant and enhanced thermal conduction definitions. Raising the convection from h ¼ 10 to 50 W/m2 K by five times, the surface temperature increases from 55
C to 66
C at 50 min. However, at relatively higher values, i.e., 100 W/m2 K, the change in the convective heat transfer coefficient slightly affects the surface temperature. At lower convection coefficients, the slope of the curves becomes smaller. The definition of enhanced thermal conductivity enhances the heat transfer and increases the slope of the curves significantly. During the early periods of the process, the definition of the improved thermal coefficient reduces the surface temperature. As time advances, the wall temperature rapidly increases and reaches the free stream temperature in a short period. Fig. 7B represents the time-wise variation in liquid fraction values. The required time to complete melting is significantly reduced when the convection coefficient increases from h ¼ 10 to 50 W/m2 K. Beyond these values, increments cause no significant changes regarding the liquid fraction. For instance, at t ¼ 100 min, the liquid fraction values are 0.45, 0.83, 0.87, and 0.90 for h ¼ 10, 50, 100, and 400 W/m2 K, respectively. On the other hand, the definition of enhanced thermal conductivity becomes effective when the liquid fraction reaches 0.4. The slope of the liquid fraction is improved by defining improved thermal conductivity. The implementation of enhanced thermal conductivity reduced the complete time for melting by almost one-fourth.

4. CONCLUSIONS The current work focuses on investigating the effect of enhanced thermal conductivity on the melting process of PCM inside a spherical capsule. A two-dimensional axisymmetric mathematical model is developed using ANSYS-Fluent software, and improved thermal conductivity is incorporated into the software employing user-defined-functions. The primary outcomes of the current work are thus: • •

Increasing the free stream temperature and the convective heat transfer coefficient improves heat transfer inside the sphere and decreases the time required for complete melting. The definition of effective thermal conductivity significantly affects the phase-change process and enhances the rate of heat transfer.

NOMENCLATURE c g h k Pr r Ra t T

Specific heat (kJ/kg K) Gravitational acceleration (m2/s) Heat transfer coefficient (W/m2 K) Thermal conductivity (W/m K) Prandtl number (e) Radial axis direction (m) Raleigh number (e) Time (s) Temperature (K,
C)

624

CHAPTER 2.23 PHASE CHANGE INSIDE A SPHERICAL CAPSULE

Greek Symbols

a b Dr DT q n r

Thermal diffusivity (m2/s) Thermal expansion coefficient (1/K) Liquid spacing (m) Temperature differences (K,
C) Angular position (
) Kinematic viscosity (m2/s) Density (kg/m3)

Subscripts eff eq N l m o

Effective Equivalent Ambient Liquid Melting Outer

Abbreviations AA CFD DSC GNP HTF LHTES MA PCM TES

Arachidic acid Computational fluid dynamics Differential scanning calorimeter Graphene nano platelets Heat transfer fluid Latent heat thermal energy storage Myristic acid Phase-change material Thermal energy storage

ACKNOWLEDGMENTS The authors wish to thank Nuriye Bozkurt and Mu¨ru¨vvet Zengino glu for their support of this work.

REFERENCES [1] C¸engel YA, Boles MA. In: Kanoglu M, editor. Thermodynamics: an engineering approach. McGraw-Hill Education; 2015. [2] Pintaldi S, Perfumo C, Sethuvenkatraman S, White S, Rosengarten G. A review of thermal energy storage technologies and control approaches for solar cooling. Renewable and Sustainable Energy Reviews 2015;41: 975e95. [3] Erek A, Ilken Z, Acar MA. Experimental and numerical investigation of thermal energy storage with a finned tube. International Journal of Energy Research 2005;29(4):283e301. [4] Erek A, Ezan MA. Experimental and numerical study on charging processes of an ice-on-coil thermal energy storage system. International Journal of Energy Research 2007;31(2):158e76. [5] Erek A, Dincer I. An approach to entropy analysis of a latent heat storage module. International Journal of Thermal Sciences 2008;47(8):1077e85.

REFERENCES

625

[6] Erek A, Dincer I. A new approach to energy and exergy analyses of latent heat storage unit. Heat Transfer Engineering 2009;30(6):506e15. [7] Ezan MA, Ozdogan M, Gunerhan H, Erek A, Hepbasli A. Energetic and exergetic analysis and assessment of a thermal energy storage (TES) unit for building applications. Energy and Buildings 2010;42(10):1896e901. [8] Ekren O, Ezan MA, Erek A. Experimental assessment of energy storage via variable speed compressor. International Journal of Refrigeration 2011;34(6):1424e35. [9] Ezan MA, Erek A. Solidification and melting periods of an ice-on-coil latent heat thermal energy storage system. Journal of Heat Transfer 2012;134(6), 062301. [10] Ezan MA, Erek A, Dincer I. Energy and exergy analyses of an ice-on-coil thermal energy storage system. Energy 2011;36(11):6375e86. [11] Ezan MA, Erek A, Dincer I. A study on the importance of natural convection during solidification in rectangular geometry. Journal of Heat Transfer 2011;133(10):102301. [12] Ezan MA, Erek A, Dincer I. Numerical study on solidification process inside annulus in presence of natural convection. International Journal of Exergy 2013;12(4):423e50. _ [13] Seki Y, Ince S¸, Ezan MA, Turgut A, Erek A. Graphite nanoplates loading into eutectic mixture of adipic acid and sebacic acid as phase change material. Solar Energy Materials and Solar Cells 2015;140:457e63. [14] Seki Y, Ince S, Ezan MA, Turgut A, Erek A. Development and evaluation of graphite nanoplate (GNP) e based phase change material for energy storage applications. International Journal of Energy Research 2015; 39(5):696e708. _ [15] Ince S¸, Seki Y, Ezan MA, Turgut A, Erek A. Thermal properties of myristic acid/graphite nanoplates composite phase change materials. Renewable Energy 2015;75:243e8. [16] Bedecarrats JP, Strub F, Falcon B, Dumas JP. Phase-change thermal energy storage using spherical capsules: performance of a test plant. International Journal of Refrigeration 1996;19(3):187e96. [17] Be´de´carrats JP, Castaing-Lasvignottes J, Strub F, Dumas JP. Study of a phase change energy storage using spherical capsules. Part I: experimental results. Energy Conversion and Management 2009;50(10):2527e36. [18] Tan FL, Hosseinizadeh SF, Khodadadi JM, Fan L. Experimental and computational study of constrained melting of phase change materials (PCM) inside a spherical capsule. International Journal of Heat and Mass Transfer 2009;52(15):3464e72. [19] Ismail KAR, Henrı´quez JR, da Silva TM. A parametric study on ice formation inside a spherical capsule. International Journal of Thermal Sciences 2003;42:881e7. [20] Veerappan M, Kalaiselvam S, Iniyan S, Goic R. Phase change characteristic study of spherical PCMs in solar energy storage. Solar Energy 2009;83(8):1245e52. [21] Ezan MA, Uzun M, Erek A. A study on evaluation of effective thermal conductivity for spherical capsules. International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics. 2014. [22] Voller VR, Swaminathan CR. ERAL Source-based method for solidification phase change. Numerical Heat Transfer, B Fundamentals 1991;19(2):175e89. [23] Bilir L, Ilken Z. Total solidification time of a liquid phase change material enclosed in cylindrical/spherical containers. Applied Thermal Engineering 2005;25(10):1488e502. [24] Bilir L. Estimation of the total solidification time of a liquid phase change material enclosed in cylindrical _ _ and spherical containers (Master thesis). Izmir: Izmir Institute of Technology, Mechanical Engineering; 2003.

CHAPTER

ENERGY AND EXERGY ANALYSES OF NITROGEN LIQUEFACTION PROCESS

2.24

Arif Karabu
ga, Re¸sat Selba¸s, Ahmet Kabul Suleyman Demirel University, Isparta, Turkey

1. INTRODUCTION The earth is surrounded by air. The components of air are nitrogen, oxygen, and argon. There is a virtually unlimited supply of nitrogen, oxygen, and argon because of their natural occurrence within the atmosphere. Currently several methods are known for air separation. Two processes exist to separate air: cryogenic distillation and noncryogenic distillation. Cryogenics is the science and technology of very low temperatures, usually below 120K [1]. Noncryogenic methods include pressure swing adsorption and membrane separation. The choice of process to be used is based on the desired products. Cryogenic air separation is used when a high-purity product is needed. It is also advantageous when products are required in a liquid form [2]. Table 2 shows purity values obtained according to different liquefaction processes [3]. Cryogenic systems have the ability to deliver the largest capacities for products and for very high purities. Noncryogenics systems are employed at the lower end of the production scale and generally for lower-purity products [4]. Table 1 compares different air separation processes. The largest markets for oxygen are in primary metals production, chemicals and gasification, clay, glass and concrete products, petroleum refineries, and welding. The use of medical oxygen is an increasing market. Gaseous nitrogen is used in the chemical and petroleum industries and is also used extensively by the electronic and metal industries for its inert properties. Liquid nitrogen is used in applications ranging from cryogenic grinding of plastics to frozen foods. Argon, the third major component of air, is used as an inert material primarily in for welding steel, treating heat, and in manufacturing processes for electronics [5,6]. Otherwise liquid nitrogen is used in physics applications, particle accelerators, colliders, and synchrotrons [7]. In this study, the values were taken from the Linde Gas air separation facility at Gebze [8]. In the literature, Cornelissen and Hırs carried out an exergy analysis to determine the possibilities of saving fuel in the cryogenic distillation process. The results of the analysis showed that more than half of the loss of exergy takes place in the liquefaction unit and almost one-third in the air compression unit. Exergy loss in the compressor was reduced by improvement [9]. Amin et al. simulated nitrogen separation from air. In that study, liquefaction processes were predicated on the LindeeHampson method as a thermodynamic cycle. The degree of liquefaction was Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00036-6 Copyright © 2018 Elsevier Inc. All rights reserved.

627

628

CHAPTER 2.24 ENERGY AND EXERGY ANALYSES

Table 1 Comparison of Processes of Air Separation [9] Process

Advantages

Disadvantages

Cryogenic

Low amount of electricity per unit nitrogen Produces very high purity nitrogen Can generate liquid nitrogen for storage on-site Low to moderate capital cost Cost-effective nitrogen production of relatively high purities Quick installation and start-up Low capital cost Production output is very flexible Quick installation and start-up Easy to vary purity and flow rate

Large site space and utility requirements High capital cost Limited scalability in production Long start-up and shutdown High maintenance equipment Noisy operation Limited scalability

Pressure swing adsorption

Membrane

Uneconomical for high purity requirements Uneconomical for large outputs Requires relatively large amount of electricity per unit nitrogen

Table 2 Comparison of Purity Values of Air Separation Unit [10] Process

Purity (%)

Cryogenic Pressure swing adsorption Membrane

N: 95e99 O2: 90e95 N: 99.9 O2: 85e99.7 N: 10 parts per billion

taken to be
200 C under maintenance and affective parameters. Using nitrogen from simulated air, the HYSYS program was employed and the purity rate of nitrogen was determined to be 91.75% as a result [10]. Rizk et al. presented a simulation of three types of cryogenic process column and calculated the exergy losses of the different columns. For each column, an accurate analysis was defined. An exergy analysis comparing the distillation columns determined the double diabetic column’s exergy efficiency to be 23% more efficient than the traditional adiabatic double column [2]. Van der Ham and Kjelstrup conducted an exergy analysis of two different air separation units: one of the units studied had three columns and the other had two. The three-column design had 12% less exergy loss than the two-column design [11]. Li et al. used an optimization methodology to obtain a thermodynamic design for a large-scale liquefaction system. Exergy efficiency was been taken into consideration as an evaluation index in the study. Three different gases were liquefied in the system. In the case of nitrogen liquefaction, the efficiency of the system was 58% [12].

2. SYSTEM DESCRIPTION

629

Sadaghiani and Mehrpooya conducted energy and exergy analyses of a hydrogen liquefaction system. They produced 300 tons of liquid per day using different mixture refrigerants in independent cooling cycles. In the first refrigeration cycle, the hydrogen gas was cooled to
195 C; the second cycle was reduced to
253 C. The energy analysis of the system was calculated to be 0.1797. According to the results of the exergy analysis, the exergy efficiency of the first and second refrigeration cycles and the whole liquefaction process were 67.53%, 52.24%, and 55.47%, respectively [13]. The aims of this study were to find the exergy efficiency of the nitrogen liquefaction unit and to determine the parameters affecting the exergy efficiency.

2. SYSTEM DESCRIPTION An integrated system was examined in this study. A nitrogen liquefaction unit was integrated into an air separation system. The air separation unit consisted of three parts. The first part was the air supply, the second was purification of the air, and the third was separation of the air in a cold box. The air entered the air supply section at atmospheric pressure and ambient temperature. The air first passed through the air filter (F-10). Particles the size of 2 mm in air were trapped in this filter. Particulate-free air was compressed to working pressure in a three-stage compressor (CP-11). Air from the compressor entered the air cooler (R-15). The air was then cooled to 278K and entered a water separator (SP-169) in the air purification part. In SP-169, moisture in the air was separated and entered the dryer (D-16). Carbon dioxide in the air was separated at D-16. Air from here passed through the last filter (F-162) and entered the cold box. In the meantime, air leaving the purification part was called dry air. This process is shown in Fig. 1.

FIGURE 1 Atmospheric section.

630

CHAPTER 2.24 ENERGY AND EXERGY ANALYSES

The cold box consisted of various equipment, including the main heat exchanger blocks and distillation columns. There were also three different columns in the cold box: high pressure (HP), low pressure (LP) , and argon. There were 50 separation trays in the HP column and 78 in the LP column. In the system, high and LP columns were stacked atop each other. Fig. 2 shows the distillation columns. In this figure, the lower part that is the HP column has a half single column with a condenser on top and a dry air feed at the bottom. The upper part is the LP column with a condenser outside but with a reboiler. The condenser in the HP column acted as the reboiler for the LP column. Dry air entered the bottom of the HP column at temperatures close to the liquefaction temperature. Vapor roses up the column to the condenser and formed a reflux. Air could not be fed in liquid form to this column because it did not contain a reboiler, which is required to create vapor. It already had that at the top of the column; there was pure nitrogen because it had a lower boiling point than oxygen. That bottom product was not be pure, compared with the air that was fed in it, however; it is was oxygen rich because nitrogen had been taken out as the top product. The bottom product known as rich liquid contained less than 40%. The outlet dry air from the purification unit entered the cold box, the third part of the air separation unit. After that dry air entered the heat exchanger and left it in a temperature close to liquefaction and

FIGURE 2 Distillation column in cold box.

2. SYSTEM DESCRIPTION

631

then the dry air entered the HP column. As the dry air rose in the HP column, the oxygen level dropped below 1 part per million. The dry air was separated as oxygen, nitrogen, and argon, according to differences in their boiling temperatures. In the distillation column, nitrogen was separated from the other components and transferred into the liquefaction unit. The nitrogen liquefaction unit consisted of nitrogen recycle compression CP-77, booster compressor-turbine CE-77, booster compressor turbine last cooler HE-771, nitrogen chiller R-60, and three exchangers. When it entered the nitrogen liquefaction unit at nearly 5 bar pressure, nitrogen rose to nearly 32 bar pressure in recycle compression. Nitrogen left booster the compressor-turbine at nearly 45 bar pressure. The compressor enabled this pressure to work from the turbine through the booster compressor’s last cooler and enter the first heat exchanger block HE-1. It left HE-1 with a temperature of 251K. When it entered the nitrogen chiller cooler, heat was removed. After that, nitrogen entered theHE-2 heat exchanger and left at a temperature of 182K. Nitrogen’s three-quarters liquid mass left the HE-2 heat exchanger for the booster compressor turbine and enabled the necessary work for pressure in the compressor. Liquid from the turbine combines with average-pressure nitrogen and passed through the heat exchanger blocks in the liquefaction unit, combining with average nitrogen from the main heat exchanger of the cold box. Finally, it entered the nitrogen recycle compressor one-quarter of nitrogen from the HE-2 heat exchanger. After that, it entered the HE-3 heat exchanger and left it at a temperature of 112K and 45 bar pressure in the liquid phase. This process is shown in Fig. 3.

FIGURE 3 Nitrogen liquefaction unit [8].

632

CHAPTER 2.24 ENERGY AND EXERGY ANALYSES

3. ENERGY AND EXERGY ANALYSES To make an exergy analysis of the nitrogen liquefaction unit, it is necessary to define two cooling effects in the liquid and gas phases. The refrigeration effect per unit mass of the gas in the cycle is given as [14]: qL; gas ¼ h4
h2

(1)

where the h4 value defines the enthalpy leaving the compressor and the h2 value defines enthalpy entering the compressor. For energy balance in the cycle, the refrigerant effect per unit mass of the liquefied gas is given as [14]: qL;liquid ¼ h2
hliquid

(2)

where hliquid defines the enthalpy value of liquid nitrogen leaving the cycle. If energy balance in the compressor is written for gases per mass according to compression [14]: win ¼ RT0 lnðP2 =P1 Þ

(3)

where R is the nitrogen gas constant, T0 is ambient temperature, and the P values are the entering and exit pressures (T0 ¼ 298.15K). To find the liquefaction rate of the gases in the cycle, the fraction of Eqs. (2) to (1) was calculated [14]: y¼

qL;gas qL;liquid

(4)

When actual work in the cycle was written for nitrogen per mass [14]: wactual ¼

win y

(5)

When the actual coefficient of performance (COP) in the cycle was written for gases per mass [14]: COPactual ¼

qL;gas win

(6)

For the COP value of liquid per mass in the liquefaction unit, Eq. (2) is calculated as reversible work [14]: COPrev ¼

qL;liquid wrev

(7)

Reversible work in Eq. (7) is defined in Eq. (8) [14]: wrev ¼ h17
h2
T0 ðs17
s2 Þ

(8)

To finding exergy efficiency in the cycle, the COPactual value rate of COPrev values were calculated: hex ¼

COPactual COPrev

(9)

4. RESULTS AND DISCUSSION

633

Table 3 General Equations of System Components System Component

Mass Balance

Energy Balance

Exergy Balance

CP-70 compressor CE-77 compressor HE-771 cooling after compressor HE-71 heat exchanger R-60 nitrogen chiller HE-72 heat exchanger CE-77 turbine HE-73 heat exchanger

_2 ¼m _3 m

_ CP
70 ¼ m _ 3 h3
m _ 2 h2 W

_ cp
70 ¼ m _ 3 ε3 þ Icp
70 _ 2 ε2 þ W m

_3 ¼m _4 m

_ CE
77 ¼ m _ 4 h4
m _ 3 h3 W

_ ce
77 ¼ m _ 4 ε4 þ Ice
77 _ 3 ε3 þ W m

_5 _4 ¼m m

_ 4 h4
m _ 5 h5 Q_ HE
771 ¼ m

_ 5 ε5 þ Q_ HE
771 þ IHE
771 _ 4 ε4 ¼ m m

_5 ¼m _6 m _ 15 _ 14 ¼ m m

_ 15 h15 ¼ m _ 5 h5 þ m _ 14 h14 _ 6 h6 þ m m

_ 14 ε14 ¼ m _ 6 ε6 þ m _ 15 ε15 þ IHE
71 _ 5 ε5 þ m m

_6 ¼m _7 m

_ 6 h6
m _ 7 h7 Q_ R
60 ¼ m

_ 7 ε7 þ Q_ R
60 þ IR
60 _ 6 ε6 ¼ m m

_7 ¼m _8 m _ 15 _ 14 ¼ m m

_ 14 h14 ¼ m _ 7 h7 þ m _ 13 h13 _ 8 h8 þ m m

_ 13 ε13 ¼ m _ 8 ε8 þ m _ 14 ε14 þ IHE
72 _ 7 ε7 þ m m

_9 ¼m _ 10 m _ 16 ¼ m _ 17 m _ 13 _ 12 ¼ m m

_ CE
77 ¼ m _ 9 h9
m _ 10 h10 W _ 13 h13 ¼ m _ 16 h16 þ m _ 12 h12 _ 17 h17 þ m m

_ ce
77 þ Ice
77 _ 10 ε10 þ W _ 9 ε9 ¼ m m _ 12 ε12 ¼ m _ 17 ε17 þ m _ 13 ε13 þ IHE
73 _ 16 ε16 þ m m

To find the exergy efficiency in the heat exchanger of the nitrogen liquefaction cycle [7]: hex
HE ¼

_ HP ðexheatout
exheatin Þ m _ LP ðexcoldin
excoldout Þ m

(10)

where m is the rate of mass flow through the heat exchanger and ex is defined as hot and cold exergy. As shown in Table 3, mass, energy, and exergy balance equations for each component in the system are derived by depending on the first and second laws of thermodynamics.

4. RESULTS AND DISCUSSION A thermodynamic analysis of the nitrogen liquefaction unit was performed. As a result of the analysis, the COPactual and COPrev values were found. In addition, the exergy efficiency of heat exchangers HE1, HE-2, and HE-3, in the liquefaction unit and the exergy efficiency of the whole liquefaction system were calculated. The enthalpy and entropy values of each point found in the nitrogen liquefaction unit are given in Table 4. The results of the analyses are given in Table 5. Figs. 4 and 5 show the temperature-entropy and pressure-enthalpy diagrams of the whole liquefaction system, respectively. Results for the COP analyses are given in Fig. 6. The COPactual and COPrev were 0.2801 and 0.7708, respectively. The parameter affecting the change in COP values was the ambient temperature, and so the effects on COP values for changes in ambient temperature are

634

CHAPTER 2.24 ENERGY AND EXERGY ANALYSES

Table 4 Enthalpy and Entropy Values in Nitrogen Liquefaction Cycle Reference Point Values

Enthalpy (kJ/kg)

Entropy (kJ/kg)

Reference Point Values

Enthalpy (kJ/kg)

Entropy (kJ/kg)

1 2 3 4 5 6 7 8 9

285.4 309 311 361.3 308.5 246.5 227.7 160.9 161.6

6.237 6.319 5.81 5.868 5.706 5.483 5.406 5.084 5.86

10 11 12 13 14 15 16 17

103.3 87.37 101.6 161.5 240 313 161.8
43.42

5.203 5.049 5.191 5.649 6.056 6.333 5.088 3.603

Table 5 Calculated Results Calculated Values

Result

Calculated Values

Result

qL; gas qL; liquid y

52.3 kJ/kg 352.42 kJ/kg 0.148 186.69 kJ/kg 1261.4 kJ/kg 456.58 kJ/kg

COPactual COPrev hex hex
HE
1 hex
HE
2 hex
HE
3

0.2801 0.7708 0.36 0.55 0.81 0.89

wactual;gas wactual;liquid wrev

COP, coefficient of performance; qL; gas , refrigeration effect per unit mass of gas (kJ/kg); qL; liquid , refrigeration effect per unit mass of liquefaction (kJ/kg); wactual, actual work (kJ/kg); y, fraction of gas in the cycle that is liquefied.

Nitrogen

400 350

4 15 2

150 17

100 50 2.0

0,2

2.5

3.0

3.5

23,32 bar 9,68 bar 3,011 bar 0,4 0,5596 bar 0,6

Temperature-entropy diagram of nitrogen liquefaction unit.

1,09 m

13

10 11

12

0,8

4.0 4.5 5.0 Entropy (kJ/kg-K)

FIGURE 4

0,42

9 16 8

14 3

0,024

200

6 0,06

7

0,16

250

3/kg

1 0,003 6

Temperature (K)

3

5

300

5.5

6.0

6.5

7.0

4. RESULTS AND DISCUSSION

Nitrogen

5x102 3,7

4,3

4

4,6 4,9

102 16

17

Pressure (bar)

635

5,2

8

123,1 K

101

9

152,3 K

10

99,5 K

11

6

5

7 188,4 K

13

12

K

kg-

kJ/

233,2 K

14

4

3

1

2

15

80,42 K

100

0,2

10-1 -150 -100

0,4

-50

0,6

0,8

0

50

100

150

200

250

300

350

400

Enthalpy (kJ/kg)

FIGURE 5 Pressure-enthalpy diagram of nitrogen liquefaction unit.

FIGURE 6 Results of actual coefficient of performance (COPactual) and reversible coefficient of performance (COPrev).

given in Fig. 7. In this study, the ambient temperature (dead state) was variable and there was a parametric change in COP values. This shows the importance of taking ambient temperature (dead state) into account in the calculation. COP values are an available efficiency that is connected with the reference environment of the system. Also, the exergy efficiency of HE-1, HE-2, and HE-3 heat exchangers in the liquefaction unit was 0.5533, 0.8129, and 0.8984, respectively.

CHAPTER 2.24 ENERGY AND EXERGY ANALYSES

0.3

0.95 COPactual

COPrev

0.9

0.29

0.85

0.285

0.8

0.28

0.75

COPactual

0.295

0.275 270

275

280 285 290 295 Ambient temperature (K)

300

COPrev

636

0.7 305

FIGURE 7 Coefficient of performance values change graphics depending on ambient temperature. COPactual, actual coefficient of performance; COPrev, reversible coefficient of performance.

When the ambient temperature was 293 and 298K, the increase in the compressor inlet temperature caused a decrease in exergy efficiency, as shown in Fig. 8. The change in COPactual and exergy efficiency depended on the compressor outlet enthalpy values, as shown in Fig. 9. The increase in this enthalpy value led directly to an increase in the exergy efficiency of the system. If the enthalpy value increased further to 40 kJ/kg at the compressor outlet, the exergy of the system would increase to about 46%. 0.45 exergy efficiency T0=293 (K) exergy efficiency T0=298 (K) COPactual T0=298 (K) COPactual T0=293 (K)

Exergy efficiency

0.4 0.35 0.3 0.25 0.2 0.15 280

290

300 310 320 Compressor inlet temperature (K)

FIGURE 8 Exergy efficiency change depending on compressor inlet temperature.

330

5. CONCLUSIONS

0.45

0.55 exergy efficiency

0.4

0.5

0.35

0.45

0.3

0.4

360 370 380 390 Compressor outlet enthalpy (kJ/kg)

400

Exergy efficiency

COPactual

COPactual

0.25 350

637

0.35 410

FIGURE 9 Actual coefficient of performance (COPactual) and exergy efficiency change graphic depending on compressor outlet enthalpy value.

In addition, the mass, energy, and exergy balances of each component in the system are given in Table 3. The values in Table 4 were used in formulas to obtain the results in Table 5.

5. CONCLUSIONS In this study, real air separation and nitrogen liquefaction units were examined. The following main results may be extracted from the study: • • • • • • •

The mass, energy, and exergy balances of each component in the nitrogen liquefaction unit were written. The effects of ambient temperature on the COP values are shown graphically. The effect of the compressor inlet temperature on the exergy of the system is shown diagrammatically. The energy and exergy analyses were performed according to the input and output values of the equipment in the nitrogen liquefaction unit. The COPactual and COPrev values of the liquefaction unit were calculated to be 0.2801 and 0.7708, respectively. Moreover, the exergy efficiencies of HE-1, HE-2, and HE-3 heat exchangers were calculated to be 0.55, 0.81, and 0.89, respectively. An exergy analysis was performed and the exergy efficiency was calculated to be 36%. When the values in Table 4 are examined, the work done by the nitrogen recycle compressor was too little and the work of the compressor affected the exergy efficiency of the system. Developments in compressor technology will increase the efficiency of liquefaction systems.

638

CHAPTER 2.24 ENERGY AND EXERGY ANALYSES

NOMENCLATURE FL10 CPL11 RL15 SPL169 DL16 FL162 CPL77 CEL77 HEL771 RL60 HE qL; gas qL; liquid win R T0 P y wactual wrev COP COPactual COPrev s h hliquid hex hexLHE _ m HP LP exheatout exheatin excoldin excoldout

Air filter Three-stage compressor Air cooler Water separator Dryer The last filter Nitrogen recycle compression Booster compressor turbine The last cooler Nitrogen chiller Heat exchanger Refrigeration effect per unit mass of gas (kJ/kg) Refrigeration effect per unit mass of liquefaction (kJ/kg) Specific work input (kJ/kg) Ideal gas constant (J/mol K) Ambient temperature (K) Pressure (bar) Fraction of gas in the cycle that is liquefied Actual work (kJ/kg) Reversible work (kJ/kg) Coefficient of performance Actual coefficient of performance Reversible coefficient of performance Entropy (kJ/kg) Enthalpy (kJ/kg) Enthalpy of liquid nitrogen (kJ/kg) Exergy efficiency Exergy efficiency of heat exchanger Mass rate (kg/s) High pressure (bar) Low pressure (bar) Exergy of outlet heat fluid (kJ/kg) Exergy of inlet heat fluid (kJ/kg) Exergy of inlet cold fluid (kJ/kg) Exergy of outlet cold fluid (kJ/kg)

REFERENCES [1] Weisend II JG. Handbook of cryogenic engineering. USA: Taylor & Francis; 1998. p. 504. [2] Rizk J, Nemer M, Clodic D. A real column design exergy optimization of a cryogenic air separation unit. Energy 2012;37:417e29. [3] KLM Technology group. Air separation units. 2013. [4] Castle WF. Air separation and liquefaction: recent developments and prospects for the beginning of the new millennium. International Journal of Refrigeration 2002;25:158e72.

REFERENCES

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[5] Vinson DR. Air separation control technology. Computers and Chemical Engineering 2006;30:1436e46. [6] Campestrini M. Thermodynamic study of solid-liquid-vapour equilibrium: application to cryogenizs and air separation unit [Doctoral thesis]. 2014. p. 147. [7] Thomas RJ, Ghosh P, Chowdhury K. Exergy analysis of helium liquefaction systems based on modified Claude cycle with two-expanders. Cryogenics 2011;51:287e94. [8] The Linde Group. About air separation units. 2009. [9] Cornelissen RL, Hırs GG. Exergy analysis of cryogenic air separation. Energy Conversion Management 1998;39(16e18):1821e6. [10] Amin R, Islam A, Islam R, Islam S. Simulation of N2 gas separation process from air. IOSR Journal of Applied Chemistry 2014;6(5):09e13. [11] van der Ham LV, Kjelstrup S. Exergy analysis of two cryogenic air separation processes. Energy 2010;35: 4731e9. [12] Li Y, Wang X, Ding Y. An optimal design methodology for large-scale gas liquefaction. Applied Energy 2012;99:484e90. [13] Sadaghiani MS, Mehrpooya M. Introducing and energy analysis of a novel cryogenic hydrogen liquefaction process configuration. International Journal of Hydrogen Energy 2017;42:6033e50. _ Rose MR. Exergy: energy, environment and sustainable development. Canada: Elsevier; 2007. [14] Dinc¸er I, p. 454.

CHAPTER

THERMODYNAMIC PERFORMANCE ANALYSIS OF A RAW MILL SYSTEM IN A CEMENT PLANT

2.25

Mehmet Altinkaynak, Murat Ozturk, Ali K. Yakut Suleyman Demirel University, Isparta, Turkey

1. INTRODUCTION Cement production facilities are energy-extensive plants that make every effort related to power consumption, performance, and generation. The cement production process has different steps, including (1) grinding and blending raw materials, (2) heating these materials to very high temperatures in the kiln subsystem, (3) cooling and mixing these materials with gypsum, and finally (4) grinding the mixture to form a cement powder. An exergy analysis presents the system design as close as is allowable to the maximum theoretical limit. The development a technique for raw mill components to have increased performance is a vital task. The transfer of heat between the inlet layer of the raw mill and the environment is the most generally encountered operation in the component design process. Numerous theoretical and experimental analyses for evaluating the raw mill system in cement plant have been given in the open literature. Sogut et al. [1] analyzed heat recovery modeling from the rotary kiln process in the cement industry to the environment using the viewpoints of energetic and exergetic analyses. The authors also investigated the energetic and exergetic performances and exergy destruction rates of the rotary kiln subsystem for cement production. Madlool et al. [2] defined the mass, energy and exergy balance conversions, and energetic and exergetic performances of the components in a cement facility for cement production. In addition, Ahamed [3] investigated the energetic efficiency, exergetic performance, and recovery efficiency of a cooling process by optimization its working indicators, such as (1) the mass flow rate of the working fluid and clinker, (2) the cooling working fluid temperature, and (3) the grate speed. Also, they defined the thermodynamic performance analysis to investigate the working indicators of the clinker cooling process and heat recovery from hot exhaust gases. Atmaca and Kanoglu [4] performed energetic and exergetic analyses of a raw mill. They gave specific measures to reduce the quantity of power consumption in the system. They calculated the energetic and exergetic efficiency to be 61.5% and 16.4%, respectively. Gutierrez et al. [5] investigated the power consumption and exergy destruction rate of calcination in vertical shaft kilns to identify Exergetic, Energetic and Environmental Dimensions. http://dx.doi.org/10.1016/B978-0-12-813734-5.00037-8 Copyright © 2018 Elsevier Inc. All rights reserved.

641

642

CHAPTER 2.25 THERMODYNAMIC PERFORMANCE ANALYSIS

indicators affecting energy consumption. They determined that the largest exergy destruction rate occurred as a result of fuel combustion, internal heat, and momentum transfer taking place in the kiln process. Altinkaynak et al. [6] analyzed the thermodynamic assessment of a cement plant in Isparta, Turkey. They performed the parametric analyses to investigate the system design indicators of the process’s efficiency. In this chapter, methods to determine the magnitudes and causes of the exergy destruction rate for the raw mill process in the cement industry were investigated in detail using a thermodynamic analysis. Furthermore, the impact of design indicators on system efficiency were evaluated under different operating conditions, such as ambient temperature, the mass flow rate of materials, and the temperature of system components for to design the process better. The specific objectives of this chapter were to perform a thermodynamic analysis of the raw mill process, increase the efficiency of the process, and decrease the exergy destruction rate. Other main subobjectives of this study were: • • • •

to code for an analysis of the raw system using Engineering Equation Solver (EES) software to determine the exergy contents for each stream of the raw mill system to calculate the exergy efficiencies and destructions for the system components and the whole system to perform a complete parametric study to analyze the impacts of some significant parameters on the process performance

2. SYSTEM DESCRIPTION The raw mill system is an important component among other parts of the cement plant. Because the raw mill system is used to grain the crude inputs into the farine output, which is the partial product of clinker output. The farine production processes consist of two parts. The input substances after being mixed in the drying chamber goes to the grinding component. After this grinding process, the combination changes into farine. The combination is then, continuously turned with steel winglet until it owns the desired properties and it is sent to the separator with the impact of vacuum pressure from the raw mill subsystem. A schematic diagram of the raw mill system in a cement plant is illustrated in Fig. 1. In this process, raw materials, such as CaCO2, SiO2, Al2O3, Fe2O3, MgO, K2O, SO3, and Na2O at the reference temperature and pressure enter the raw mill system to produce farine. The farine that is produced, which consists of CaO, CO2, SiO2, Al2O3, Fe2O3, MgO, K2O, SO3, and Na2O, enters the farine silo at point 2. Also, the farine dust goes into the filter at point 3. The addition of stack gases for farine production is a significant indicator. Therefore, heated gases such as N2, O2, CO2, CO, and SO2 are input into the raw mill system at point 4 to create heat for the raw materials.

3. THERMODYNAMIC ASSESSMENT A thermodynamic analysis based on the first and second laws of thermodynamics was used to examine the system performance, energy loss rate, and exergy destruction rate to increase the efficiency of the process and its components. The mass and energy and exergy balance equations were given to investigate detailed information about the exergy destruction rate and the energy and exergy content of any stream, and the energy efficiency and exergy efficiency of the process. Generally, based on the usual principle, the thermodynamic balance equation for a quantity in a system can be defined as [7]: Inp þ Gen  Out  Con ¼ Acc

(1)

3. THERMODYNAMIC ASSESSMENT

643

Cyclone

6

9

14

8 Filter

Cooling tower

7

Filter ventilation

3 10

1

13

5 4

Raw mill 2

Abgas ventilation

Farine silo Airlift compressor 11

12

FIGURE 1 Schematic diagram of a raw mill system.

where Inp, Gen, Out, Con, and Acc are the input, generation, output, consumption, and accumulation, respectively. Also, under the steady-state conditions, the accumulated indicator in Eq. (1) is equal to zero because all properties in the system do not change with time.

3.1 MASS BALANCE The conservation of mass is a fundamental procedure for thermodynamic analysis. The mass balance equation can be defined as: X X m_ i ¼ m_ e (2) where m_ is the mass flow rate and subscripts i and e are the inlet and outlet flows, respectively.

3.2 ENERGY BALANCE The energy analysis of the control volume deals with all energy parts of the chosen control volume. The energy balance equation, which is given as the first law of thermodynamics, can be given as: X X Q_ þ m_ i hi ¼ W_ þ m_ e he (3) _ W, _ and h are the heat transfer rate, power, and specific enthalpy, respectively. where Q,

644

CHAPTER 2.25 THERMODYNAMIC PERFORMANCE ANALYSIS

3.3 EXERGY BALANCE Exergy can be defined as the maximum work that should be provided from the process at a chosen state. To evaluate the exergy analysis, first the reversible work must be defined. The reversible work can be described as the maximum useful work that can be provided as the system goes through a process between two given states. The general exergy balance rate can be written as: X X X _ Qþ _ Wþ _ D Ex m_ i exi ¼ Ex m_ e exe þ Ex (4) _ Q and Ex _ W are the exergy _ D is the exergy destruction rate. Ex where ex is the specific exergy and Ex transfer rate by heat and work, respectively, and can be defined as:   _ Q ¼ 1  To Q_ Ex (5) T _ W ¼ W_ Ex

(6)

where To is the reference temperature and T is the temperature at which heat transfer takes place. The specific exergy can be written as: ex ¼ exke þ expe þ exph þ exch

(7)

where exke , expe , exph , and exch are the kinetic, potential, physical, and chemical exergies, respectively. In this chapter, kinetic and physical exergy are accepted as negligible. Physical exergy or specific flow exergy can be written as: exph ¼ ðh  ho Þ  To ðs  so Þ where s is the specific entropy. The chemical exergy of the gas mixture can be given as: X X xi lnðxi Þ exch ¼ xi exoch þ RTo

(8)

(9)

where exoch is the standard chemical exergy of an element in kJ/mol, xi is the mass fraction of an element i, and subscript o stands for the dead state. The total exergy rate can be given as: _ ¼ mex _ Ex

(10)

3.4 THERMODYNAMIC ANALYSIS OF SYSTEM COMPONENTS 3.4.1 Raw Mill In this section, energy and exergy analyses of a raw mill system in the cement plant were performed. To achieve this, the mass and energy and exergy balance equations for the input and output flows of the raw mill process were evaluated. The mass balance equation of the raw mill process can be written as: m_ 1 þ m_ 4 ¼ m_ 2 þ m_ 3

(11)

Based on the general energy balance equation, which given in Eq. (3), the energy balance equation for the raw mill can be defined as: RM m_ 1 h1 þ m_ 4 h4 þ Q_loss ¼ m_ 2 h2 þ m_ 3 h3

(12)

3. THERMODYNAMIC ASSESSMENT

645

The exergy balance equation of the raw mill is written as: _ RM _ RM m_ 1 ex1 þ m_ 4 ex4 þ Ex Q; loss ¼ m_ 2 ex2 þ m_ 3 ex3 þ ExD

(13)

The raw materials enter the raw mill at point 1, as seen in Fig. 1. The chemical compositions of the raw materials are given in Table 1. The specific exergy of flow at state 1 is written as: ch ch ch ex1 ¼ YCaO MCaO exch CaO þ YCO2 MCO2 exCO2 þ YSiO2 MSiO2 exSiO2 þ YAl2 O3 MAl2 O3 exAl2 O3 ch ch ch þ YFe2 O3 MFe2 O3 exch Fe2 O3 þ YMgO MMgO exMgO þ YK2 OMK2 OexK2 O þ YSO3 MSO3 exSO3

þ YNa2 OMNa2 Oexch Na2 O

(14)

where the chemical exergies of CaO, CO2 , SiO2 , Al2 O3 , Fe2 O3 , MgO, K2 O, SO3 , and Na2 O are given as, respectively:    h i 0 0 0 0 0 0 ch exch ¼ h  h þ 0:5h s  s þ 0:5s (15)  T þ exch 0 CaO CaO Ca O2 CaO Ca O2 Ca þ 0:5exO2    h i 0 0 0 0 0 0 ch exch (16) þ exch CO2 ¼ hCO2  hC þ hO2  T0 sCO2  sC þ sO2 C þ exO2    h i 0 0 0 0 0 0 ch exch (17) þ exch SiO2 ¼ hSiO2  hSi þ hO2  T0 sSiO2  sSi þ sO2 Si þ exO2    h i 0 0 0 0 0 0 ch exch (18) þ exch Al2 O3 ¼ hAl2 O3  hAl2 þ 1:5hO2  T0 sAl2 O3  sAl2 þ 1:5sO2 Al2 þ 1:5exO2    h i 0 0 0 0 0 0 ch exch (19) þ exch Fe2 O3 ¼ hFe2 O3  hFe2 þ 1:5hO2  T0 sFe2 O3  sFe2 þ 1:5sO2 Fe2 þ 1:5exO2

Table 1 Chemical Composition of Raw Materials at Point 1 Raw Materials CaCO2

Molar Mass (M) (kg/kmol)

Mass Concentration (Y) (wt%)

_ Mass Flow Rate (m) (kg/s)

CaO CO2

0.792

32.05

0.1345 0.0304 0.0203 0.0125 0.0055 0.0028 0.002 1

5.44 1.23 0.83 0.51 0.22 0.11 0.08 40.47

SiO2 Al2O3 Fe2O3 MgO K2O SO3 Na2O Total

56.077 44.01 60.084 101.961 159.69 40.304 94.196 80.064 61.979

646

CHAPTER 2.25 THERMODYNAMIC PERFORMANCE ANALYSIS

   h i 0 0 0 0 0 0 ch exch þ exch MgO ¼ hMgO  hMg þ 0:5hO2  T0 sMgO  sMg þ 0:5sO2 Mg þ 0:5exO2    h i 0 0 0 0 0 0 ch exch ¼ h  h þ 0:5h s  s þ 0:5s  T þ exch 0 K2 O K2 O2 K2 O K2 O K2 O2 K2 þ 0:5exO2  h i   0 0 0 0 0 0 ch þ exch exch SO3 ¼ hSO3  hS þ 1:5hO2  T0 sSO3  sS þ sO3 S þ 1:5exO2    h i 0 0 0 0 0 0 ch exch þ exch Na2 O ¼ hNa2 O  hNa2 þ 0:5hO2  T0 sNa2 O  sNa2 þ 0:5sO2 Na2 þ 0:5exO2

(20) (21) (22) (23)

where Mi is the molar mass (kg/kmol) of the ith substance and Yi is the mass concentration (wt%) of the ith substance. Mi and Yi are also given in Table 1. The stack gases enter the raw mill at point 4. The chemical compositions of the stack gases are written in Table 2. The specific exergy of the flow at state 4 can be calculated as follows: ch ch ch ch ex4 ¼ YN2 MN2 exch N2 þ YO2 MO2 exO2 þ YCO2 MCO2 exCO2 þ YCO MCO exCO þ YSO2 MSO2 exSO2

where the chemical exergy equations of CO and SO2 are given as:    h i 0 0 0 0 0 0 ch exch þ exch CO ¼ hCO  hC þ 0:5hO2  T0 sCO  sC þ 0:5sO2 C þ 0:5exO2    h i 0 0 0 0 0 0 ch exch þ exch SO2 ¼ hSO2  hS þ hO2  T0 sSO2  sS þ sO2 S þ exO2

(24)

(25) (26)

The raw materials exit the raw mill. They are called farine and are stored in a farine silo at point 2. The chemical composition of farine at point 2 is given in Table 3. The specific exergy of flow at point 2 is given as: ch ch ch ex2 ¼ YCaO MCaO exch CaO þ YCO2 MCO2 exCO2 þ YSiO2 MSiO2 exSiO2 þ YAl2 O3 MAl2 O3 exAl2 O3 ch ch ch þ YFe2 O3 MFe2 O3 exch Fe2 O3 þ YMgO MMgO exMgO þ YK2 OMK2 OexK2 O þ YSO3 MSO3 exSO3

þ YNa2 OMNa2 Oexch Na2 O

(27)

Stack gases plus farine dust exit the raw mill and go to the electro-filter at point 3. The chemical composition of the flowing materials at point 3 is given in Table 4.

Table 2 Chemical Composition of Stack Gases at Point 4 Stack Gases

Molar Mass (M) (kg/kmol)

Mass Concentration (Y) (wt%)

_ Mass Flow Rate (m) (kg/s)

N2 O2 CO2 CO SO2

28.013 31.999 44.010 28.0104 64.065 Total

0.1022 0.0401 0.8406 0.0096 0.0075 1

7.39 2.90 60.78 0.69 0.54 72.30

3. THERMODYNAMIC ASSESSMENT

647

Table 3 Chemical Composition of Farine at Point 2

Farine CaO CO2 SiO2 Al2O3 Fe2O3 MgO K2O SO3 Na2O

Molar Mass (M) (kg/kmol) 56.077 44.010 60.084 101.961 159.691 40.304 94.196 80.064 61.979 Total

Mass Concentration (Y) (wt%)

Mass Flow Rate _ (kg/s) (m)

0.4366 0.3554 0.1345 0.0304 0.0203 0.0125 0.0055 0.0028 0.002 1

16.78 13.66 5.17 1.17 0.78 0.48 0.21 0.11 0.08 38.44

Table 4 Chemical Composition of Flowing Materials at Point 3 Flowing Materials CaO CO2 SiO2 Al2O3 Fe2O3 MgO K2O SO3 Na2O N2 O2 CO SO2

Molar Mass (M) (kg/kmol) 56,077 44,010 60,084 101,961 159,69 40,304 94,196 80,064 61,979 28,013 31,999 28,0104 64,065 Total

Mass Concentration (Y) (wt%)

Mass Flow Rate _ (kg/s) (m)

0.01188 0.8274 0.0036 0.0008 0.0005 0.0003 0.00015