Renewable Energy Sources: Engineering, Technology, Innovation: ICORES 2018 [1st ed.] 978-3-030-13887-5;978-3-030-13888-2

Table of contents :
Front Matter ....Pages i-xvii
Front Matter ....Pages 1-1
Analysis of the Possibilities of Using a Hybrid Heating System in the Process of Anaerobic Biomass Decomposition in Mesophilic Conditions (Mariusz Adamski, Marcin Herkowiak, Natalia Mioduszewska, Ewa Osuch, Andrzej Osuch, Gniewko Niedbała et al.)....Pages 3-15
Possibilities of Using Biomass from Nutshells for Energy Purposes (Andrzej Bryś, Magdalena Sokalska, Szymon Głowacki, Weronika Tulej, Joanna Bryś, Mariusz Sojak)....Pages 17-26
Study of PAR Intensity Distribution in Cylindrical Photobioreactors (Beata Brzychczyk, Tomasz Hebda, Jan Giełżecki)....Pages 27-36
Drying Kinetics of Selected Waste Biomass from the Food Industry (Beata Brzychczyk, Bogusława Łapczyńska-Kordon, Tomasz Hebda, Jan Giełżecki)....Pages 37-48
Process of Gradual Dysfunction of a Diesel Engine Caused by Formation of PM Deposits of FAME Origin (Bogusław Cieślikowski)....Pages 49-58
Selective Catalytic Dehydration of Bioethanol (Vitaliy E. Diyuk, Vladyslav V. Lisnyak, Ruslan Mariychuk)....Pages 59-66
Technical Options of Pruned Biomass Harvesting in the Apple Orchards Applying Baling Technology and Its Conversion to Energy (Arkadiusz Dyjakon)....Pages 67-78
Analysis of Physical Properties of Pellet Produced from Different Types of Dendromass (Szymon Głowacki, Weronika Tulej, Mariusz Sojak, Andrzej Bryś, Ewa Golisz, Jakub Kaczmarczyk)....Pages 79-88
Ultrasonic Impact on the Drying Process of Wood Biomass (Szymon Głowacki, Weronika Tulej, Mariusz Sojak, Andrzej Bryś, Małgorzata Jaros, Daniel Szulc)....Pages 89-98
Analysis of Technical Solutions of Planting Machines, Which Can Be Used in Planting Energy Willow (Taras Hutsol, Serhii Yermakov, Jurii Firman, Vasyl Duganets, Alla Bodnar)....Pages 99-111
Efficiency of Industrial Drying of Apple Pomace (Małgorzata Jaros, Albert Gniado, Ewa Golisz, Szymon Głowacki, Weronika Tulej)....Pages 113-122
Characteristics of Commercially Available Charcoal and Charcoal Briquettes in the Light of Petrographic Studies (Zbigniew Jelonek)....Pages 123-137
Physical and Chemical Analysis of Biomass Pellets in Terms of the Existing Standards (Dorota Koruba, Jerzy Zbigniew Piotrowski)....Pages 139-148
Study of Physical Properties of Rice and Corn Used for Energy Purposes (Weronika Kruszelnicka)....Pages 149-162
Potential of Soybean Straw in Ukraine and Solid Biofuel Production (Veronika Khomina, Ivan Trach, Iryna Semenyshyna, Olena Koberniuk, Krzysztof Mudryk, Marcin Jewiarz et al.)....Pages 163-170
Energy Efficiency of Biomass Production from Selected Energy Plants (Dariusz Kwaśniewski, Urszula Malaga-Toboła, Maciej Kuboń)....Pages 171-182
The Influence of Compost Fertilization on Wood Yield of SRC Willow in Second Rotation (Teodor Kitczak, Marek Bury, Małgorzata Szuleta)....Pages 183-191
Modeling of the Dynamic Modes of the Bioreactor, as an Object of Automatic Control (Boris Kotov, Taras Hutsol, Yuriy Pantsyr, Ihor Garasymchuk, Ivan Gordiychuk, Michael Torchuk)....Pages 193-198
Innovative Methods of Obtaining Substrates and Pre-treatment in the Production of Biogas (Sławomir Kurpaska, Paweł Kiełbasa, Zygmunt Sobol)....Pages 199-207
Marketing Concepts in the Formation of the Biomass Market in Ukraine (Mykola Misiuk, Oleg Kucher, Maryna Zakhodym, Yulia Ievstafieva)....Pages 209-218
Analysis of Methane Efficiency of Sugar Beets Used as Co-substrate in Biogas Production (Natalia Mioduszewska, Jacek Przybył, Anna Smurzyńska, Mariusz Adamski, Ewa Osuch, Hubert Latała et al.)....Pages 219-228
Numerical Analysis of the Combustion Process in the Wood Stove (Przemysław Motyl, Marcin Wikło, Krzysztof Olejarczyk, Krzysztof Kołodziejczyk, Rafał Kalbarczyk, Bartosz Piechnik et al.)....Pages 229-237
Analysis of the Flue Gas Produced During the Coal and Biomass Co-combustion in a Solid Fuel Boiler (Natalia Maciejończyk, Grzegorz Pełka, Wojciech Luboń, Daniel Malik)....Pages 239-246
The Preliminary Studies on the Wood Pellets Combustion in Pellet-Fired Domestic Boilers (Adam Nocoń, Marta Jach-Nocoń, Iwona Jelonek)....Pages 247-255
The Estimation of Above- and Below-Ground Biomass Residues and Carbon Sequestration Potential in Soil on Commercial Willow Plantation (Dariusz Niksa, Michał Krzyżaniak, Mariusz J. Stolarski)....Pages 257-266
Evaluation of the Fertilizing Potential of Products Based on Torrefied Biomass and Valorized with Mineral Additives (Marcin Niemiec, Monika Komorowska, Krzysztof Mudryk, Marcin Jewiarz, Jakub Sikora, Anna Szeląg-Sikora et al.)....Pages 267-275
The Possibility of Using Potamogeton Crispus for Energy Purposes (Ewa Osuch, Andrzej Osuch, Stanisław Podsiadłowski, Piotr Rybacki, Mariusz Adamski)....Pages 277-283
Prospects for the Production of Biofuels from Crop Residues Bean and Its Environmental and Technological Characteristics (Vasyl Ovcharuk, Oleg Boyko, Olesya Horodyska, Olena Vasulyeva, Krzysztof Mudryk, Marcin Jewiarz et al.)....Pages 285-292
Prospects of Use of Nutrient Remains of Corn Plants on Biofuels and Production Technology of Pellets (Oleh Ovcharuk, Taras Hutsol, Olena Ovcharuk, Vadym Rudskyi, Krzysztof Mudryk, Marcin Jewiarz et al.)....Pages 293-300
Emissivity of Biomass Mixtures and Temperature Distribution in the Combustion Chamber in the Process of Thermal Energy Production (Joanna Pasternak, Paweł Purgał, Jolanta Latosińska)....Pages 301-310
The Use of Fertilizer Produced from Coal Combustion By-Products as a Part of Sustainable Management of Waste Materials (Łukasz Paluch, Marcin Niemiec, Krzysztof Mudryk, Maciej Chowaniak, Monika Komorowska)....Pages 311-322
Straw of Buckwheat as an Alternative Source of Biofuels (Havrylianchyk Ruslan, Tetiana Bilyk, Taras Hutsol, Oleksiu Osadchuk, Krzysztof Mudryk, Marcin Jewiarz et al.)....Pages 323-329
The Usefulness of Nano-Organic-Mineral Fertilizer Stymjod in Intensification of Growth, Physiological Activity and Yield of the Jerusalem Artichoke Biomass (Zdzisława Romanowska-Duda, Mieczysław Grzesik, Regina Janas)....Pages 331-339
Stimulating Effect of Ash from Sorghum on the Growth of Lemnaceae—A New Source of Energy Biomass (Zdzisława Romanowska-Duda, Krzysztof Piotrowski, Barbara Wolska, Marcin Debowski, Marcin Zielinski, Piotr Dziugan et al.)....Pages 341-349
The Physical-Mechanical Properties of Fuel Briquettes Made from RDF and Wheat Straw Blends (Karolina Słomka-Polonis, Bogusława Łapczyńska-Kordon, Jarosław Frączek, Jakub Styks, Jakub Fitas, Bożena Gładyszewska et al.)....Pages 351-361
Perspectives of Fennel (Foeniculum Vulgare Mill.) Use for Energy Purposes (Vasyl Stroyanovsky, Veronika Khomina, Taras Hutsol, Kolosiuk Iryna, Krzysztof Mudryk, Marcin Jewiarz et al.)....Pages 363-369
Torrefaction Process of Millet and Cane Using Batch Reactor (Szymon Szufa, Łukasz Adrian, Piotr Piersa, Zdzisława Romanowska-Duda, Marta Marczak, Joanna Ratajczyk-Szufa)....Pages 371-379
Experimental Data Collection for Numerical Model Verification for Wood Stove (Marcin Wikło, Przemysław Motyl, Krzysztof Olejarczyk, Krzysztof Kołodziejczyk, Rafał Kalbarczyk, Bartosz Piechnik et al.)....Pages 381-389
Direct Electricity Production from Linseed Oil (Paweł P. Włodarczyk, Barbara Włodarczyk)....Pages 391-398
The Main Factors Determining the Porosity of Granular Materials of Biological Origin (Artur Wójcik, Sławomir Francik, Adrian Knapczyk)....Pages 399-410
Assessment of Agglomeration Properties of Biomass—Preliminary Study (Marek Wróbel)....Pages 411-418
Possibility of Using Automation Tools for Planting of the Energy Willow Cuttings (Serhii Yermakov, Taras Hutsol, Sergii Slobodian, Serhii Komarnitskyi, Myroslav Tysh)....Pages 419-429
New Indicators for Determination of Acid Number in Diesel Fuel Containing Biodiesel (Yuliya Zhukova, Yaroslav Studenyak, Ruslan Mariychuk)....Pages 431-443
Front Matter ....Pages 445-445
The Analysis of Geothermal Well Constructions Depending on Expected Pressure Conditions (Anna Chmielowska, Barbara Tomaszewska, Anna Sowiżdżał)....Pages 447-457
Recycling Expired Photovoltaic Panels in Poland (Joanna Hałacz, Maciej Neugebauer, Piotr Sołowiej, Krzysztof Nalepa, Maciej Wesołowski)....Pages 459-470
Photovoltaic Panels in a Single-Family House (Arkadiusz Kępa)....Pages 471-482
Influence of the Size of the PV Power Plant on Operating Parameters and Its Efficiency (Jarosław Knaga, Krzysztof Nęcka, Tomasz Szul, Bogusława Łapczyńska-Kordon, Robert Bernacik)....Pages 483-492
Modeling and Calculating the Double Channel Helio-Collector for Drying Agricultural Plant Materials (Boris Kotov, Yuriy Pantsyr, Ihor Garasymchuk, Iryna Semenyschyna, Pavel Potapsky, Taras Hutsol)....Pages 493-500
Theoretical and Real Efficiency of the Solar Power Plant in a 2-Year Cycle (Hubert Latała, Krzysztof Nęcka, Sławomir Kurpaska, Anna Karbowniczak, Natalia Mioduszewska)....Pages 501-510
Cost Comparison of Heating a Detached House by Means of a Heat Pump and Solid-Fuel Boiler (Wojciech Luboń, Grzegorz Pełka, Natalia Fiut)....Pages 511-519
Potential and Prospects of Hydroelectric Objects of the River Smotrych and Ecological-Economic Situation Within Kamianets-Podilskyi District (Ukraine) (Lyudmyla Mykhailova, Oleh Ovcharuk, Viktor Dubik, Oleksandr Kozak, Dariya Vilchynska)....Pages 521-532
Data Acquisition System for a Ground Heat Exchanger Simulator (Krzysztof Nalepa, Piotr Sołowiej, Maciej Neugebauer, Wojciech Miąskowski)....Pages 533-539
Fuzzy Model of Wind Turbine Control (Maciej Neugebauer, Piotr Sołowiej, Maciej Wesołowski, Krzysztof Nalepa, Joanna Hałacz)....Pages 541-550
Use of Wind Energy in the Process of Lake Restoration (Ewa Osuch, Andrzej Osuch, Stanisław Podsiadłowski, Piotr Rybacki, Natalia Mioduszewska)....Pages 551-559
Analysis of Shallow Geothermal System Utilization in the AGH-UST Educational and Research Laboratory of Renewable Energy Sources and Energy Saving in Miękinia (Grzegorz Pełka, Wojciech Luboń, Anna Sowiżdżał)....Pages 561-569
Research on Development of the New Refractory Material Called OXITEC (Bartosz Piechnik, Rafał Kalbarczyk, Julita Bukalska, Przemysław Motyl, Krzysztof Olejarczyk, Marcin Wikło)....Pages 571-578
The Use of Heat Pumps for Heating Purposes in the Region of Warmia and Mazury in North-Eastern Poland (Janusz Piechocki, Piotr Sołowiej, Maciej Neugebauer, Krzysztof Nalepa, Maciej Wesołowski)....Pages 579-585
Analysis of a Vertical Ground Heat Exchanger Operation Cooperating with a Heat Pump (Joanna Piotrowska-Woroniak)....Pages 587-601
An Analysis of Electricity Gains from Various Photovoltaic Installations Under The Real-World Conditions of North-Eastern Poland (Aldona Skotnicka-Siepsiak, Maciej Wesołowski, Janusz Piechocki, Piotr Sołowiej, Maciej Neugebauer, Marcin Tejszerski)....Pages 603-609
Geological, Hydrogeological and Technological Conditions of the Use of Production-Injection Systems in the Lower Jurassic (Liassic) Reservoir Horizons of the Polish Lowland (Jan Adam Soboń)....Pages 611-624
Analysis of the Efficiency of a Photovoltaic Microsystem in North-Eastern Poland (Piotr Sołowiej, Maciej Neugebauer, Krzysztof Nalepa, Janusz Piechocki, Maciej Wesołowski)....Pages 625-632
The Use of the Solar Radiation to Lower Consumption of the Electric Power for Lighting in Buildings (Sławomir Sowa)....Pages 633-641
Application of Electromagnetic Methods in Recognizing of Hydrogeothermal Conditions Inside Crystalline Massifs (Michał Stefaniuk)....Pages 643-652
Development of Stable Perovskite Solar Cell (Dávid Strachala, Matouš Kratochvíl, Josef Hylský, Adam Gajdoš, Ladislav Chladil, Jiří Vaněk et al.)....Pages 653-665
Preliminary Assessment of the Local Solar Energy Conditions in the Health Resort of Rabka-Zdrój—As a Potential for Using Photovoltaic Micro-Installations (Aleksandra Szulc, Barbara Tomaszewska)....Pages 667-676
Assessment of Wind Energy Resources Using Data Mining Techniques (Jędrzej Trajer, Rafał Korupczyński, Marcin Wandel)....Pages 677-688
Assessment of the Impact of the Local Geological Structure on the Efficiency of Ground-Source Heat Pump (Magdalena Tyszer, Barbara Raczyńska, Barbara Tomaszewska)....Pages 689-700
Front Matter ....Pages 701-701
Possibilities of Applying the Gasification Process in Coffee Grounds Treatment (Stanisław Famielec, Wojciech Kępka)....Pages 703-713
The Simulation of the Temperature Distribution in the Compost Using the Autodesk CFD Simulation Program (Jan Giełżecki, Tomasz Jakubowski)....Pages 715-725
Hazardous Waste Solidification from Chemical Technological Process (Maciej Gliniak, Anna Lis, Anna Łoś, Dariusz Mikołajek, Ziemowit Kapłański)....Pages 727-734
The Use of Compost Produced with the Addition of Wastes from a Poultry Farm in Potato-Growing (Tomasz Jakubowski, Jan Giełżecki)....Pages 735-741
The Possibility of Using Composted Biowaste with the Addition of Biochar for Energy Purposes (Mateusz Malinowski, Katarzyna Wolny-Koładka, Magdalena D. Vaverková, Dana Adamcová, Jan Zloch, Maria Łukasiewicz et al.)....Pages 743-751
A Comparative Assessment of Municipal Waste Accumulation in Selected Rural Communes (Grzegorz Przydatek, Katarzyna Gancarczyk)....Pages 753-762
Analysis of Properties and Possibilities of Environmental Use of Municipal Sewage Sludge—A Case Study (Grzegorz Przydatek, Agata Szymańska-Pulikowska)....Pages 763-774
Assessment of the Variability of the Landfill Gas Composition Captured on a Used Landfill (Grzegorz Przydatek, Klaudia Ciągło)....Pages 775-785
Benefits of the Utilization of Waste Packaging Materials in the Pyrolysis Process (Dariusz Urbaniak, Agnieszka Bala-Litwiniak, Tomasz Wyleciał, Paweł Wawrzyniak)....Pages 787-795
Front Matter ....Pages 797-797
Thermographic Analysis and Experimental Work Using Laboratory Installation of Heat Transfer Processes in a Heat Pipe Heat Exchanger Utilizing as a Working Fluid R404A and R407C (Łukasz Adrian, Szymon Szufa, Piotr Piersa, Artur Cebula, Sebastian Kowalczyk, Zdzisława Romanowska-Duda et al.)....Pages 799-807
Modelling of Heat Storage Using Phase Change Material Tank (Tomasz Bakoń, Paweł Obstawski, Anna Kozikowska)....Pages 809-816
Assessment of the Potential and Use of Renewable Energy Sources in the Municipality of Września (Weronika Bojarska, Jacek Leśny, Monika Panfil)....Pages 817-826
Electric Cars as a Future Energy Accumulation System (Józef Flizikowski, Andrzej Tomporowski, Weronika Kruszelnicka, Izabela Piasecka, Adam Mroziński, Robert Kasner)....Pages 827-839
Optimisation Methods in Renewable Energy Sources Systems—Current Research Trends (Sławomir Francik, Adrian Knapczyk, Artur Wójcik, Zbigniew Ślipek)....Pages 841-852
An Attempt to Use Kohonen Networks to Find Similarities in the Process of Convective Drying of Wood Biomass (Szymon Głowacki, Weronika Tulej, Mariusz Sojak, Andrzej Bryś, Bartłomiej Pokojski)....Pages 853-862
Application of Methods for Scheduling Tasks in the Production of Biofuels (Adrian Knapczyk, Sławomir Francik, Artur Wójcik, Zbigniew Ślipek)....Pages 863-873
Laboratory-Teaching Building Energis as the Example of Intelligent Building (Dorota Koruba, Robert Piekoszewski)....Pages 875-884
Calculation of Thermal Energy Storage System Capacity Dependent on Climate and Building Structure (Anna Kozikowska, Tomasz Bakoń, Paweł Obstawski)....Pages 885-893
Substantiation of the Working Surface Parameters of the Screw Press Drawing Block of Plant Materials (Dmytro Kuzenko, Oleh Krupych, Stepan Levko, Krzysztof Mudryk)....Pages 895-905
Development of Renewable Energy Sources in Big Cities in Poland in the Context of Urban Policy (Aleksandra Lewandowska, Justyna Chodkowska-Miszczuk, Krzysztof Rogatka)....Pages 907-918
Economic Analysis of Domestic Hot Water Preparation Using Air-Source Heat Pump (Wojciech Luboń, Grzegorz Pełka, Beata Krężołek)....Pages 919-927
Effectiveness of Capital and Energy Expenditures in Organic Production (Urszula Malaga-Toboła, Maciej Kuboń, Dariusz Kwaśniewski, Pavol Findura)....Pages 929-937
Financial Condition of the Development of the Market of Renewable Energy Sources (Oleksandra Mandych, Arkadii Mykytas, Mariia Melnyk, Olga Girzheva, Sergiy Kalinichenko)....Pages 939-951
The Influence of Pre-processing of Input Data on the Quality of Energy Yield Forecasts from a Photovoltaic Plant (Krzysztof Nęcka, Anna Karbowniczak, Hubert Latała, Marek Wróbel, Natalia Mioduszewska)....Pages 953-960
An Adaptive Monitoring System of Heat Storage Using Phase Change Materials (Paweł Obstawski, Tomasz Bakoń, Anna Kozikowska)....Pages 961-969
Test and Implementation of Control Algorithm in Hybrid Energy System with Phase Change Material Storage Tank in State Flow Matlab Toolbox (Paweł Obstawski, Tomasz Bakoń, Anna Kozikowska)....Pages 971-979
Optimization of the Parameters for the Process of Grain Cooling (Igor Palamarchuk, Sergey Kiurchev, Valentyna Verkholantseva, Nadiia Palianychka, Olena Hryhorenko)....Pages 981-988
Study of the Effect of Grain Pipe Variations on the Supply of Grain in Coulter Space (Anatolii Rud, Yurii Pavelchuk, Lyudmyla Mykhailova, Oleksandr Dumanskyi, Ruslana Semenyshyna, Taras Hutsol)....Pages 989-998
Furnace Waste in Relation to Existing Legal Regulations and Basic Physicochemical Tests (Wojciech Szulik)....Pages 999-1012
Assessment Worksheets—Practical Tool in Visual Impact Assessment Procedures for Renewable Energy Investments (Hanna Szumilas-Kowalczyk)....Pages 1013-1024
Multi-dimensional Comparative Analysis of Renewable Energy Sources Development (Małgorzata Trojanowska, Krzysztof Nęcka)....Pages 1025-1033
An Influence of Cross-Linking Agent on Electrochemical Properties of Gel Polymer Electrolyte (Iuliia Veselkova, Michal Jahn, Marie Sedlaříková, Jiří Vondrák)....Pages 1035-1042
Analysis of Energy Storage Capabilities in Hydrated Sodium Acetate Using the Phase Transitions of the First Kind (Robert Szczepaniak, Grzegorz Woroniak, Radosław Rudzki)....Pages 1043-1055
Comparison of Cu-B Alloy and Stainless Steel as Electrode Material for Microbial Fuel Cell (Barbara Włodarczyk, Paweł P. Włodarczyk)....Pages 1057-1063
Use of Exhaust Waste Energy as Essential Element of Heat Economy in Furnaces Heating Steel Charge (Tomasz Wyleciał, Jarosław Boryca, Dariusz Urbaniak)....Pages 1065-1076
Dynamics of Changes in Total Consumption of Most Important Renewable Energy Sources in Poland (Daniel Zbroński, Henryk Otwinowski)....Pages 1077-1089
Back Matter ....Pages 1091-1094

Citation preview

Springer Proceedings in Energy

Marek Wróbel Marcin Jewiarz Andrzej Szlęk   Editors

Renewable Energy Sources: Engineering, Technology, Innovation ICORES 2018

Springer Proceedings in Energy

The series Springer Proceedings in Energy covers a broad range of multidisciplinary subjects in those research fields closely related to present and future forms of energy as a resource for human societies. Typically based on material presented at conferences, workshops and similar scientific meetings, volumes published in this series will constitute comprehensive state-of-the-art references on energy-related science and technology studies. The subjects of these conferences will fall typically within these broad categories: – – – – – –

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Marek Wróbel Marcin Jewiarz Andrzej Szlęk •

•

Editors

Renewable Energy Sources: Engineering, Technology, Innovation ICORES 2018

123

Editors Marek Wróbel Faculty of Production and Power Engineering University of Agriculture in Krakow Kraków, Poland

Marcin Jewiarz Faculty of Production and Power Engineering University of Agriculture in Krakow Kraków, Poland

Andrzej Szlęk Institute of Thermal Technology Silesian University of Technology Gliwice, Poland

ISSN 2352-2534 ISSN 2352-2542 (electronic) Springer Proceedings in Energy ISBN 978-3-030-13887-5 ISBN 978-3-030-13888-2 (eBook) https://doi.org/10.1007/978-3-030-13888-2 Library of Congress Control Number: 2019933184 © Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Organization

Program Chairs Marek Wróbel, University of Agriculture in Krakow, Poland Marcin Jewiarz, University of Agriculture in Krakow, Poland Andrzej Szlęk, Silesian University of Technology, Poland

Program Committee Krzysztof Dziedzic, University of Agriculture in Krakow, Poland Jarosław Frączek, University of Agriculture in Krakow, Poland Adrian Knapczyk, University of Agriculture in Krakow, Poland Wojciech Luboń, AGH University of Science and Technology in Krakow, Poland Krzysztof Mudryk, University of Agriculture in Krakow, Poland Grzegorz Pełka, AGH University of Science and Technology in Krakow, Poland Artur Wójcik, University of Agriculture in Krakow, Poland

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Contents

Part I

Biomass, Liquid Biofuels and Biochar

Analysis of the Possibilities of Using a Hybrid Heating System in the Process of Anaerobic Biomass Decomposition in Mesophilic Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mariusz Adamski, Marcin Herkowiak, Natalia Mioduszewska, Ewa Osuch, Andrzej Osuch, Gniewko Niedbała, Magdalena Piekutowska and Przemysław Przygodziński Possibilities of Using Biomass from Nutshells for Energy Purposes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Andrzej Bryś, Magdalena Sokalska, Szymon Głowacki, Weronika Tulej, Joanna Bryś and Mariusz Sojak Study of PAR Intensity Distribution in Cylindrical Photobioreactors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Beata Brzychczyk, Tomasz Hebda and Jan Giełżecki Drying Kinetics of Selected Waste Biomass from the Food Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Beata Brzychczyk, Bogusława Łapczyńska-Kordon, Tomasz Hebda and Jan Giełżecki Process of Gradual Dysfunction of a Diesel Engine Caused by Formation of PM Deposits of FAME Origin . . . . . . . . . . . . . . . . . . Bogusław Cieślikowski Selective Catalytic Dehydration of Bioethanol . . . . . . . . . . . . . . . . . . . Vitaliy E. Diyuk, Vladyslav V. Lisnyak and Ruslan Mariychuk Technical Options of Pruned Biomass Harvesting in the Apple Orchards Applying Baling Technology and Its Conversion to Energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Arkadiusz Dyjakon

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Contents

Analysis of Physical Properties of Pellet Produced from Different Types of Dendromass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Szymon Głowacki, Weronika Tulej, Mariusz Sojak, Andrzej Bryś, Ewa Golisz and Jakub Kaczmarczyk Ultrasonic Impact on the Drying Process of Wood Biomass . . . . . . . . . Szymon Głowacki, Weronika Tulej, Mariusz Sojak, Andrzej Bryś, Małgorzata Jaros and Daniel Szulc Analysis of Technical Solutions of Planting Machines, Which Can Be Used in Planting Energy Willow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Taras Hutsol, Serhii Yermakov, Jurii Firman, Vasyl Duganets and Alla Bodnar Efficiency of Industrial Drying of Apple Pomace . . . . . . . . . . . . . . . . . Małgorzata Jaros, Albert Gniado, Ewa Golisz, Szymon Głowacki and Weronika Tulej

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113

Characteristics of Commercially Available Charcoal and Charcoal Briquettes in the Light of Petrographic Studies . . . . . . . . . . . . . . . . . . Zbigniew Jelonek

123

Physical and Chemical Analysis of Biomass Pellets in Terms of the Existing Standards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dorota Koruba and Jerzy Zbigniew Piotrowski

139

Study of Physical Properties of Rice and Corn Used for Energy Purposes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Weronika Kruszelnicka

149

Potential of Soybean Straw in Ukraine and Solid Biofuel Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Veronika Khomina, Ivan Trach, Iryna Semenyshyna, Olena Koberniuk, Krzysztof Mudryk, Marcin Jewiarz, Marek Wróbel and Jakub Styks

163

Energy Efficiency of Biomass Production from Selected Energy Plants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dariusz Kwaśniewski, Urszula Malaga-Toboła and Maciej Kuboń

171

The Influence of Compost Fertilization on Wood Yield of SRC Willow in Second Rotation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Teodor Kitczak, Marek Bury and Małgorzata Szuleta

183

Modeling of the Dynamic Modes of the Bioreactor, as an Object of Automatic Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Boris Kotov, Taras Hutsol, Yuriy Pantsyr, Ihor Garasymchuk, Ivan Gordiychuk and Michael Torchuk

193

Contents

Innovative Methods of Obtaining Substrates and Pre-treatment in the Production of Biogas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sławomir Kurpaska, Paweł Kiełbasa and Zygmunt Sobol Marketing Concepts in the Formation of the Biomass Market in Ukraine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mykola Misiuk, Oleg Kucher, Maryna Zakhodym and Yulia Ievstafieva Analysis of Methane Efficiency of Sugar Beets Used as Co-substrate in Biogas Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Natalia Mioduszewska, Jacek Przybył, Anna Smurzyńska, Mariusz Adamski, Ewa Osuch, Hubert Latała, Anna Karbowniczak and Krzysztof Nęcka Numerical Analysis of the Combustion Process in the Wood Stove . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Przemysław Motyl, Marcin Wikło, Krzysztof Olejarczyk, Krzysztof Kołodziejczyk, Rafał Kalbarczyk, Bartosz Piechnik and Julita Bukalska

ix

199

209

219

229

Analysis of the Flue Gas Produced During the Coal and Biomass Co-combustion in a Solid Fuel Boiler . . . . . . . . . . . . . . . . . . . . . . . . . . Natalia Maciejończyk, Grzegorz Pełka, Wojciech Luboń and Daniel Malik

239

The Preliminary Studies on the Wood Pellets Combustion in Pellet-Fired Domestic Boilers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Adam Nocoń, Marta Jach-Nocoń and Iwona Jelonek

247

The Estimation of Above- and Below-Ground Biomass Residues and Carbon Sequestration Potential in Soil on Commercial Willow Plantation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dariusz Niksa, Michał Krzyżaniak and Mariusz J. Stolarski Evaluation of the Fertilizing Potential of Products Based on Torrefied Biomass and Valorized with Mineral Additives . . . . . . . . . . . . . . . . . . Marcin Niemiec, Monika Komorowska, Krzysztof Mudryk, Marcin Jewiarz, Jakub Sikora, Anna Szeląg-Sikora and Anna Rozkosz The Possibility of Using Potamogeton Crispus for Energy Purposes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ewa Osuch, Andrzej Osuch, Stanisław Podsiadłowski, Piotr Rybacki and Mariusz Adamski Prospects for the Production of Biofuels from Crop Residues Bean and Its Environmental and Technological Characteristics . . . . . . . . . . Vasyl Ovcharuk, Oleg Boyko, Olesya Horodyska, Olena Vasulyeva, Krzysztof Mudryk, Marcin Jewiarz, Marek Wróbel and Jakub Styks

257

267

277

285

x

Contents

Prospects of Use of Nutrient Remains of Corn Plants on Biofuels and Production Technology of Pellets . . . . . . . . . . . . . . . . . . . . . . . . . . Oleh Ovcharuk, Taras Hutsol, Olena Ovcharuk, Vadym Rudskyi, Krzysztof Mudryk, Marcin Jewiarz, Marek Wróbel and Jakub Styks Emissivity of Biomass Mixtures and Temperature Distribution in the Combustion Chamber in the Process of Thermal Energy Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Joanna Pasternak, Paweł Purgał and Jolanta Latosińska The Use of Fertilizer Produced from Coal Combustion By-Products as a Part of Sustainable Management of Waste Materials . . . . . . . . . . Łukasz Paluch, Marcin Niemiec, Krzysztof Mudryk, Maciej Chowaniak and Monika Komorowska Straw of Buckwheat as an Alternative Source of Biofuels . . . . . . . . . . Havrylianchyk Ruslan, Tetiana Bilyk, Taras Hutsol, Oleksiu Osadchuk, Krzysztof Mudryk, Marcin Jewiarz, Marek Wróbel and Krzysztof Dziedzic The Usefulness of Nano-Organic-Mineral Fertilizer Stymjod in Intensification of Growth, Physiological Activity and Yield of the Jerusalem Artichoke Biomass . . . . . . . . . . . . . . . . . . . . . . . . . . . Zdzisława Romanowska-Duda, Mieczysław Grzesik and Regina Janas Stimulating Effect of Ash from Sorghum on the Growth of Lemnaceae—A New Source of Energy Biomass . . . . . . . . . . . . . . . . Zdzisława Romanowska-Duda, Krzysztof Piotrowski, Barbara Wolska, Marcin Debowski, Marcin Zielinski, Piotr Dziugan and Szymon Szufa The Physical-Mechanical Properties of Fuel Briquettes Made from RDF and Wheat Straw Blends . . . . . . . . . . . . . . . . . . . . . . . . . . . Karolina Słomka-Polonis, Bogusława Łapczyńska-Kordon, Jarosław Frączek, Jakub Styks, Jakub Fitas, Bożena Gładyszewska, Dariusz Chocyk and Grzegorz Gładyszewski Perspectives of Fennel (Foeniculum Vulgare Mill.) Use for Energy Purposes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vasyl Stroyanovsky, Veronika Khomina, Taras Hutsol, Kolosiuk Iryna, Krzysztof Mudryk, Marcin Jewiarz, Marek Wróbel and Adrian Knapczyk Torrefaction Process of Millet and Cane Using Batch Reactor . . . . . . . Szymon Szufa, Łukasz Adrian, Piotr Piersa, Zdzisława Romanowska-Duda, Marta Marczak and Joanna Ratajczyk-Szufa

293

301

311

323

331

341

351

363

371

Contents

xi

Experimental Data Collection for Numerical Model Verification for Wood Stove . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Marcin Wikło, Przemysław Motyl, Krzysztof Olejarczyk, Krzysztof Kołodziejczyk, Rafał Kalbarczyk, Bartosz Piechnik and Julita Bukalska Direct Electricity Production from Linseed Oil . . . . . . . . . . . . . . . . . . Paweł P. Włodarczyk and Barbara Włodarczyk

381

391

The Main Factors Determining the Porosity of Granular Materials of Biological Origin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Artur Wójcik, Sławomir Francik and Adrian Knapczyk

399

Assessment of Agglomeration Properties of Biomass—Preliminary Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Marek Wróbel

411

Possibility of Using Automation Tools for Planting of the Energy Willow Cuttings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Serhii Yermakov, Taras Hutsol, Sergii Slobodian, Serhii Komarnitskyi and Myroslav Tysh New Indicators for Determination of Acid Number in Diesel Fuel Containing Biodiesel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yuliya Zhukova, Yaroslav Studenyak and Ruslan Mariychuk Part II

419

431

Solar, Wind and Geothermal Energy

The Analysis of Geothermal Well Constructions Depending on Expected Pressure Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anna Chmielowska, Barbara Tomaszewska and Anna Sowiżdżał

447

Recycling Expired Photovoltaic Panels in Poland . . . . . . . . . . . . . . . . . Joanna Hałacz, Maciej Neugebauer, Piotr Sołowiej, Krzysztof Nalepa and Maciej Wesołowski

459

Photovoltaic Panels in a Single-Family House . . . . . . . . . . . . . . . . . . . Arkadiusz Kępa

471

Influence of the Size of the PV Power Plant on Operating Parameters and Its Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jarosław Knaga, Krzysztof Nęcka, Tomasz Szul, Bogusława Łapczyńska-Kordon and Robert Bernacik

483

xii

Contents

Modeling and Calculating the Double Channel Helio-Collector for Drying Agricultural Plant Materials . . . . . . . . . . . . . . . . . . . . . . . . Boris Kotov, Yuriy Pantsyr, Ihor Garasymchuk, Iryna Semenyschyna, Pavel Potapsky and Taras Hutsol Theoretical and Real Efficiency of the Solar Power Plant in a 2-Year Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hubert Latała, Krzysztof Nęcka, Sławomir Kurpaska, Anna Karbowniczak and Natalia Mioduszewska

493

501

Cost Comparison of Heating a Detached House by Means of a Heat Pump and Solid-Fuel Boiler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wojciech Luboń, Grzegorz Pełka and Natalia Fiut

511

Potential and Prospects of Hydroelectric Objects of the River Smotrych and Ecological-Economic Situation Within Kamianets-Podilskyi District (Ukraine) . . . . . . . . . . . . . . . . . . . . . . . . . Lyudmyla Mykhailova, Oleh Ovcharuk, Viktor Dubik, Oleksandr Kozak and Dariya Vilchynska

521

Data Acquisition System for a Ground Heat Exchanger Simulator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Krzysztof Nalepa, Piotr Sołowiej, Maciej Neugebauer and Wojciech Miąskowski

533

Fuzzy Model of Wind Turbine Control . . . . . . . . . . . . . . . . . . . . . . . . Maciej Neugebauer, Piotr Sołowiej, Maciej Wesołowski, Krzysztof Nalepa and Joanna Hałacz

541

Use of Wind Energy in the Process of Lake Restoration . . . . . . . . . . . Ewa Osuch, Andrzej Osuch, Stanisław Podsiadłowski, Piotr Rybacki and Natalia Mioduszewska

551

Analysis of Shallow Geothermal System Utilization in the AGH-UST Educational and Research Laboratory of Renewable Energy Sources and Energy Saving in Miękinia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Grzegorz Pełka, Wojciech Luboń and Anna Sowiżdżał Research on Development of the New Refractory Material Called OXITEC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bartosz Piechnik, Rafał Kalbarczyk, Julita Bukalska, Przemysław Motyl, Krzysztof Olejarczyk and Marcin Wikło The Use of Heat Pumps for Heating Purposes in the Region of Warmia and Mazury in North-Eastern Poland . . . . . . . . . . . . . . . . . . . . . . . . . Janusz Piechocki, Piotr Sołowiej, Maciej Neugebauer, Krzysztof Nalepa and Maciej Wesołowski

561

571

579

Contents

xiii

Analysis of a Vertical Ground Heat Exchanger Operation Cooperating with a Heat Pump . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Joanna Piotrowska-Woroniak

587

An Analysis of Electricity Gains from Various Photovoltaic Installations Under The Real-World Conditions of North-Eastern Poland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Aldona Skotnicka-Siepsiak, Maciej Wesołowski, Janusz Piechocki, Piotr Sołowiej, Maciej Neugebauer and Marcin Tejszerski

603

Geological, Hydrogeological and Technological Conditions of the Use of Production-Injection Systems in the Lower Jurassic (Liassic) Reservoir Horizons of the Polish Lowland . . . . . . . . . . . . . . . . . . . . . . Jan Adam Soboń Analysis of the Efficiency of a Photovoltaic Microsystem in North-Eastern Poland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Piotr Sołowiej, Maciej Neugebauer, Krzysztof Nalepa, Janusz Piechocki and Maciej Wesołowski

611

625

The Use of the Solar Radiation to Lower Consumption of the Electric Power for Lighting in Buildings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sławomir Sowa

633

Application of Electromagnetic Methods in Recognizing of Hydrogeothermal Conditions Inside Crystalline Massifs . . . . . . . . . Michał Stefaniuk

643

Development of Stable Perovskite Solar Cell . . . . . . . . . . . . . . . . . . . . Dávid Strachala, Matouš Kratochvíl, Josef Hylský, Adam Gajdoš, Ladislav Chladil, Jiří Vaněk and Pavel Čudek Preliminary Assessment of the Local Solar Energy Conditions in the Health Resort of Rabka-Zdrój—As a Potential for Using Photovoltaic Micro-Installations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Aleksandra Szulc and Barbara Tomaszewska

653

667

Assessment of Wind Energy Resources Using Data Mining Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jędrzej Trajer, Rafał Korupczyński and Marcin Wandel

677

Assessment of the Impact of the Local Geological Structure on the Efficiency of Ground-Source Heat Pump . . . . . . . . . . . . . . . . . . . . . . . Magdalena Tyszer, Barbara Raczyńska and Barbara Tomaszewska

689

xiv

Part III

Contents

Waste Managment

Possibilities of Applying the Gasification Process in Coffee Grounds Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Stanisław Famielec and Wojciech Kępka

703

The Simulation of the Temperature Distribution in the Compost Using the Autodesk CFD Simulation Program . . . . . . . . . . . . . . . . . . . Jan Giełżecki and Tomasz Jakubowski

715

Hazardous Waste Solidification from Chemical Technological Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Maciej Gliniak, Anna Lis, Anna Łoś, Dariusz Mikołajek and Ziemowit Kapłański The Use of Compost Produced with the Addition of Wastes from a Poultry Farm in Potato-Growing . . . . . . . . . . . . . . . . . . . . . . . Tomasz Jakubowski and Jan Giełżecki The Possibility of Using Composted Biowaste with the Addition of Biochar for Energy Purposes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mateusz Malinowski, Katarzyna Wolny-Koładka, Magdalena D. Vaverková, Dana Adamcová, Jan Zloch, Maria Łukasiewicz and Agnieszka Sikora

727

735

743

A Comparative Assessment of Municipal Waste Accumulation in Selected Rural Communes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Grzegorz Przydatek and Katarzyna Gancarczyk

753

Analysis of Properties and Possibilities of Environmental Use of Municipal Sewage Sludge—A Case Study . . . . . . . . . . . . . . . . . Grzegorz Przydatek and Agata Szymańska-Pulikowska

763

Assessment of the Variability of the Landfill Gas Composition Captured on a Used Landfill . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Grzegorz Przydatek and Klaudia Ciągło

775

Benefits of the Utilization of Waste Packaging Materials in the Pyrolysis Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dariusz Urbaniak, Agnieszka Bala-Litwiniak, Tomasz Wyleciał and Paweł Wawrzyniak

787

Contents

Part IV

xv

Energy Systems and Analysis

Thermographic Analysis and Experimental Work Using Laboratory Installation of Heat Transfer Processes in a Heat Pipe Heat Exchanger Utilizing as a Working Fluid R404A and R407C . . . . . . . . . . . . . . . . . Łukasz Adrian, Szymon Szufa, Piotr Piersa, Artur Cebula, Sebastian Kowalczyk, Zdzisława Romanowska-Duda, Mieczysław Grzesik and Joanna Ratajczyk-Szufa Modelling of Heat Storage Using Phase Change Material Tank . . . . . . Tomasz Bakoń, Paweł Obstawski and Anna Kozikowska Assessment of the Potential and Use of Renewable Energy Sources in the Municipality of Września . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Weronika Bojarska, Jacek Leśny and Monika Panfil Electric Cars as a Future Energy Accumulation System . . . . . . . . . . . Józef Flizikowski, Andrzej Tomporowski, Weronika Kruszelnicka, Izabela Piasecka, Adam Mroziński and Robert Kasner Optimisation Methods in Renewable Energy Sources Systems—Current Research Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . Sławomir Francik, Adrian Knapczyk, Artur Wójcik and Zbigniew Ślipek An Attempt to Use Kohonen Networks to Find Similarities in the Process of Convective Drying of Wood Biomass . . . . . . . . . . . . . . . . . . Szymon Głowacki, Weronika Tulej, Mariusz Sojak, Andrzej Bryś and Bartłomiej Pokojski

799

809

817 827

841

853

Application of Methods for Scheduling Tasks in the Production of Biofuels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Adrian Knapczyk, Sławomir Francik, Artur Wójcik and Zbigniew Ślipek

863

Laboratory-Teaching Building Energis as the Example of Intelligent Building . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dorota Koruba and Robert Piekoszewski

875

Calculation of Thermal Energy Storage System Capacity Dependent on Climate and Building Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anna Kozikowska, Tomasz Bakoń and Paweł Obstawski

885

Substantiation of the Working Surface Parameters of the Screw Press Drawing Block of Plant Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dmytro Kuzenko, Oleh Krupych, Stepan Levko and Krzysztof Mudryk

895

Development of Renewable Energy Sources in Big Cities in Poland in the Context of Urban Policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Aleksandra Lewandowska, Justyna Chodkowska-Miszczuk and Krzysztof Rogatka

907

xvi

Contents

Economic Analysis of Domestic Hot Water Preparation Using Air-Source Heat Pump . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wojciech Luboń, Grzegorz Pełka and Beata Krężołek Effectiveness of Capital and Energy Expenditures in Organic Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Urszula Malaga-Toboła, Maciej Kuboń, Dariusz Kwaśniewski and Pavol Findura Financial Condition of the Development of the Market of Renewable Energy Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Oleksandra Mandych, Arkadii Mykytas, Mariia Melnyk, Olga Girzheva and Sergiy Kalinichenko The Influence of Pre-processing of Input Data on the Quality of Energy Yield Forecasts from a Photovoltaic Plant . . . . . . . . . . . . . . Krzysztof Nęcka, Anna Karbowniczak, Hubert Latała, Marek Wróbel and Natalia Mioduszewska An Adaptive Monitoring System of Heat Storage Using Phase Change Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Paweł Obstawski, Tomasz Bakoń and Anna Kozikowska Test and Implementation of Control Algorithm in Hybrid Energy System with Phase Change Material Storage Tank in State Flow Matlab Toolbox . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Paweł Obstawski, Tomasz Bakoń and Anna Kozikowska Optimization of the Parameters for the Process of Grain Cooling . . . . Igor Palamarchuk, Sergey Kiurchev, Valentyna Verkholantseva, Nadiia Palianychka and Olena Hryhorenko Study of the Effect of Grain Pipe Variations on the Supply of Grain in Coulter Space . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anatolii Rud, Yurii Pavelchuk, Lyudmyla Mykhailova, Oleksandr Dumanskyi, Ruslana Semenyshyna and Taras Hutsol Furnace Waste in Relation to Existing Legal Regulations and Basic Physicochemical Tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wojciech Szulik

919

929

939

953

961

971 981

989

999

Assessment Worksheets—Practical Tool in Visual Impact Assessment Procedures for Renewable Energy Investments . . . . . . . . . . . . . . . . . . 1013 Hanna Szumilas-Kowalczyk Multi-dimensional Comparative Analysis of Renewable Energy Sources Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1025 Małgorzata Trojanowska and Krzysztof Nęcka

Contents

xvii

An Influence of Cross-Linking Agent on Electrochemical Properties of Gel Polymer Electrolyte . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1035 Iuliia Veselkova, Michal Jahn, Marie Sedlaříková and Jiří Vondrák Analysis of Energy Storage Capabilities in Hydrated Sodium Acetate Using the Phase Transitions of the First Kind . . . . . . . . . . . . . . . . . . . 1043 Robert Szczepaniak, Grzegorz Woroniak and Radosław Rudzki Comparison of Cu-B Alloy and Stainless Steel as Electrode Material for Microbial Fuel Cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1057 Barbara Włodarczyk and Paweł P. Włodarczyk Use of Exhaust Waste Energy as Essential Element of Heat Economy in Furnaces Heating Steel Charge . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1065 Tomasz Wyleciał, Jarosław Boryca and Dariusz Urbaniak Dynamics of Changes in Total Consumption of Most Important Renewable Energy Sources in Poland . . . . . . . . . . . . . . . . . . . . . . . . . . 1077 Daniel Zbroński and Henryk Otwinowski Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1091

Part I

Biomass, Liquid Biofuels and Biochar

Analysis of the Possibilities of Using a Hybrid Heating System in the Process of Anaerobic Biomass Decomposition in Mesophilic Conditions Mariusz Adamski, Marcin Herkowiak, Natalia Mioduszewska, Ewa Osuch, Andrzej Osuch, Gniewko Niedbała, Magdalena Piekutowska and Przemysław Przygodziński

Abstract The subject of the work concerns the design of a hybrid solar system to maintain mesophilic conditions in the process of anaerobic biomass decomposition. The main purpose of the work was to design a hybrid heating installation for a biomass utilizer. It was assumed to simulate the use of three energy sources: photovoltaic panels, solar collector and heat from biogas combustion. It was assumed that the results of the analysis will be supported by evaluation of biogas yield for substrates containing food and feed ingredients. The quasi-continuous and periodic operation of the rendering chamber was tested in relation to the energy demand for maintaining the mesophilic conditions in the fermentation process. As a result of the objective of the work, biogas productivity tests of the selected substrate mixture were carried out. A general design of the utilization plant (microbiogas plant) was also carried out, including thermal insulation and the design of the heating system. In order to determine the heat losses of the digester, the methodology based on the heat transfer coefficient by individual partitions was used. The level of biogas production was determined using a test stand complying with the requirements of DIN 38 414 S.8. On the basis of the volume of biogas production, thermal deficiencies resulting from its combustion were determined. Biogas deficiencies constituted more than 30% in the worst computing conditions for the periodic system and about 6% for the quasi-continuous system. The designed heating installation, which uses additional solar energy, will allow, in the case of a periodic system, to cover 100% of the summer heat demand. In winter, the coverage of heat demand was around 90% for average

M. Adamski (&)
M. Herkowiak
N. Mioduszewska
E. Osuch
A. Osuch
G. Niedbała
P. Przygodziński Poznan University of Life Sciences, Wojska Polskiego 28, 60-637 Poznan, Poland e-mail: [email protected] N. Mioduszewska e-mail: [email protected] M. Piekutowska Koszalin University of Technology, Śniadeckich 2, 75-453 Koszalin, Poland © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_1

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monthly temperatures in December and January and 80% for the worst computing conditions. Identified energy shortages can be limited by optimizing the control of the biological process and optimizing the parameters of thermally insulating layers. Keywords Methane fermentation Hybrid heating system


Waste processing
Container utilizer


1 Introduction Biomass can be characterized as waste generated as a result of agricultural and forestry activities, as well as substances originating from industrial activity, constituting a link in the processing of biodegradable waste from other sources [1]. The solution that affects the reduction of energy needs of the utilization process is the use of various renewable energy sources, including adequately cooperating technical devices that create the so-called hybrid systems. The biomass consists mainly of carbon, oxygen and hydrogen, and arises due to the ability of plant organisms to accumulate solar energy as a result of their biochemical photosynthesis process. The photosynthesis process leads to the production of carbohydrates from carbon dioxide and water under the influence of solar radiation. Biomass is therefore an organic mass that is part of plants and animals [2]. Biomase can be utilized in the following processes: aerobic stabilization, anaerobic stabilization, thermal decomposition and storage. Methane fermentation is the biochemical process under the influence of anaerobic microorganisms (fermentation bacteria), during which organic substances with a multimolecular structure (carbohydrates, proteins and fats) are reduced to simple chemical compounds: methane, alcohols, carbon dioxide and water [3–6]. Substrates with high moisture content and crude fiber, polysaccharides such as cellulose and hemicellulose, and monomers like lignin are difficult to digest for anaerobic bacteria. For processes that improve the enzymatic hydrolysis may include alcaline leaching or alcaline pretreatment [7, 8]. Competent methane fermentation process can be divided into four stages: hydrolysis, acidogenesis, acetogenesis and methanogenesis [9]. So far, the fermentation process is associated with the scale of the process, which defines the profitability of the investment. Micro biogas installations (micro biogas plants) characterize the barrier of non-mobile installations. This fact results from each preparation of the installation for a known amount of waste subjected to the process of development. The aim of the work was to analyze the possibilities of using a hybrid heating system that uses biogas energy and solar energy to sustain the process of waste biomass decomposition in mesophilic conditions on a micro scale. For the realization of the work was performed the following range of activities:

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– implementation of a functional waste biomass utilization project and determination of the system’s efficiency (scale), – selection of waste substrates, – testing of biogas yield of organic waste mix, – indication of thermal losses and energy efficiency of the container system, – energy balance—indication of energy shortages of the hybrid heating system.

2 Materials and Methods The quasi-continuous mode will most closely approximate the system of the chamber stabilizing organic waste to the function of a biogas plant. The periodic mode is similar to composting technologies. In the periodic mode, the waste is decomposed with the separation of biogas, however, the energy needs of the system should prevail over energy self-sufficiency [10, 11]. Fermentation modes (periodic and quasi-continuous) require mixing of fermenting substrates. Among the main available mixing methods (mechanical, hydraulic, pneumatic, hybrid), mechanical mixing was selected. Mechanical mixing, most often carried out by helical stirrers (propellers), is the most prevalent among biogas installations [12, 13]. Methane Fermentation. Biogas efficiency tests (biogas productivity) were carried out in accordance with DIN 38 414-S8 in a multi-chamber fermenter (Fig. 1.). The capacity of a single fermentation chamber is 1000 ml. The produced biogas is stored in eudiometer tanks. The capacity of each biogas tank is 1200 ml according to KTBL-Heft-84 2009.

Fig. 1 Research stand for the study of biogas productivity of substrates according to DIN 38414 S.8 (left), inoculum station for quasi continuous fermentation work (right) Source own work

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Measurement of methane, carbon dioxide, hydrogen sulphide, oxygen, ammonia, nitric oxide and nitrogen dioxide concentrations was performed with the tester of concentration of constituent gases in biogas, Alter Bio MSMR 16. For the preparation of inoculum was used methanogenic thermostated biostat with a capacity of 1650 ml. The fermentation test stand has been equipped with a thermostated tank that maintains the assumed thermal parameters (35 °C) of the process in the fermentation chambers. Biogas storage tanks are equipped with valves and connectors. This enables the removal of stored biogas and the transfer to the analyzer, Alter Bio MSMR 16 according to norm DIN 38414 S.8. The measurements of the concentration of constituent gases and the volume of produced biogas were carried out at 24-h intervals. Mixtures with an identical substrate composition were in each case in three fermenters to confirm the validity of the results. To measure the concentrations of constituent gases of biogas has been used measuring heads, MG-72 and MG-73, with a measuring range of 0–100% by volume and the measurement resolution of the order 0,1 ppm to 1% by volume. Based on laboratory tests and analysis of the literature [14, 15] indicated the critical factors which characterize the methane fermentation process. Factors that can have a significant impact on the biogas production process are primarily: the dry substance content, organic matter content, sample mass, reaction speed, percentage of individual components in the fermenting mix, and time of the experiment. The following standards were used: PN-74/C-04540/00, PN-75/C-04616/01 04, PN-90 C-04540/01, PN-75/C-04616/04. Visualization of the Digester and Hydraulic and Electric Scheme. In order to visualize the components of the digester used AutoCAD 2017 and AutoCAD Plant 3D 2017. The components of the container utilizer have been included in the determination of its thermal parameters. CAD programs have also been used for creating the hydraulic and electric diagrams. Methodological Guidelines for Determining the Thermal Parameters of a Container Utilizer. To calculate the heat losses, the following factors were used: heat transfer coefficient through structural partitions, material constants and indicators concerning construction materials of the digester, indicators of insulating materials and external housing of the designed container system. The values of thermal parameters were obtained from the technical guide [16]. The work uses selected principles for calculating the design heat load in accordance with PN-EN 12831. The calculation methods used relate to the heat transfer coefficient of the partitions. The ambient temperature range typical for the temperate zone of Central-Eastern Europe was used in the calculations. Methodology of Selecting Elements of a Hybrid Installation. The calculations related to the selection of individual components of the hydraulic system and the appropriate safeguards were used: information from the Office of Technical Inspection along with the methods developed by Immergas [17] and thematic publications [18–21]. In the case of a photovoltaic installation, in order to select individual system components and to optimize system operation, the calculations were carried out according to published guidelines for the design of photovoltaic installations [22, 23].

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3 Results To analyze the hybrid heating system of the digester, the following assumptions regarding the utilizer were specified: – – – –

the size of the fermentation chamber 9.5 m3, cylindrical shape of the fermentation chamber, use of thermal insulation materials, building the fermentation chamber with a container of typical dimensions.

In order to determine the biogas productivity, and thus the possibility of producing heat from biogas combustion, the following assumptions were made: – fermentation substrate composed of organic agri-food waste, – mesophilic conditions of the methane fermentation process, – operation of the system in a periodic filling system (waste biomass utilization) and quasi-continuous (microbiogas plant), – work in a one-stage system. Table 1 The composition of the fermentation mixture

No.

Type of substrate

Mass share [%]

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

Roman salad Tomato Cucumber Carrot Parsley root Parsley Leek Celery Onion Potato Pear Apple Plum Peach Banana Rancid butter Cream cheese Sausage Cat food Bread roll Biscuits

8.16 7.71 6.93 11.47 1.98 2.63 4.23 4.17 4.12 4.35 8.00 8.50 1.37 5.88 5.93 0.45 4.45 1.98 4.45 2.53 0.71 100.00

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Table 2 Output parameters of the M4 substrate mix Cattle slurry Inoculation Substrates mix. Mixture M4

Mass (g)

Part (%)

DM (%)

DM (g)

350.800 100.000 110.000 560.800

62.553 17.832 19.615 100.000

1.487

6.705

ODM (%) 98.513

ODM (g) 6.606

15.403 4.217

16.943 23.649

94.025 95.297

15.931 22.536

Table 3 Output parameters of the M10 reference substrate mix Cattle slurry Inoculation Mixture M10

Mass [g]

Part [%]

DM [%]

DM [g]

ODM [%]

ODM [g]

351.400 100.200 451.600

77.812 22.188 100.00

1.487

6.717

98.513

6.617

1.487

6.717

98.513

6.617

Fig. 2 The cumulative yield of biogas [m3.Mg−1 fresh matter]

Waste Substrates Biogas Yield. In order to determine the heat demand of container micro-installations, in the first stage, tests of the biogas yield of the substrate mixture were carried out. The composition of the mixture is presented in Table 1. The research allowed to determine the level of energy self-sufficiency of the installation. The subject of the research was a mixture of solid and liquid substrates, subjected to anaerobic decomposition. A waste test mix (M4) (Table 2) and a reference sample (M10) (Table 3) were prepared. The M4 mixture was compiled as a combination of microbial inoculation, bovine manure and tested waste substrates. The reference sample (M10) was compiled as a combination of bovine slurry and microbial inoculation. As a result of the tests carried out on samples M4 and M10, biogas productivity levels were determined: daily, cumulative (Fig. 2) and methane concentrations in the produced biogas were indicated. The results of biogas productivity tests of samples M4 and M10 are presented in tabular form (Table 4).

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Table 4 Results of biogas productivity tests of samples M4 and M10 Sample

The test parameter

M4 M10 M4 M10 M4 M10 M4 M10

Average methane concentration Average methane concentration Average daily yield of biogas Average daily yield of biogas Maximum daily productivity of Maximum daily productivity of Cumulative yield of biogas Cumulative yield of biogas

in biogas in biogas

biogas biogas

Unit of measure

Result

% v/v % v/v m3.Mg−1 m3.Mg−1 m3.Mg−1 m3.Mg−1 m3.Mg−1 m3.Mg−1

53 47 0.48 0.24 1.13 0.99 13.04 6.58

fresh fresh fresh fresh fresh fresh

mass mass mass mass mass mass

Fig. 3 Average daily biogas productivity for the periodic and quasi-continuous system

Thermal losses and energy efficiency. The obtained data from laboratory tests were used to determine the energy possibilities of a container biogas plant. In the created energy balance, the biogas productivity was compared with the needs of the chamber heating system and energy losses through conduction. The total heat loss was calculated on the basis of heat transfer coefficients by individual walls of the container installation and structural elements of the digester. The design external temperature was adopted according to the II climate zone. It is used in calculating heat load of buildings in accordance with PN-EN 12831. Thermal properties of individual construction materials were adopted according to material tables. The internal temperature was 45 °C (water jacket temperature) or 38 °C for the bottoms of the fermentation chamber (no heating jacket). Calculations of heat loss streams were made, depending on the heat transfer coefficient, barrier surface and temperature difference on both sides of the barrier. The total design heat loss (QT) was calculated by summing the heat losses through individual container walls (Q1 to Q6) in accordance with the formula 1. QT ¼ Q1 þ Q2 þ Q3 þ Q4 þ Q5 þ Q6

ð1Þ

The total design heat loss (QT) after adding losses of all barriers amounted to 1075.65 W.

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According to the calculations, the power of the heating device should be equivalent or higher than the sum of the heat loss through the barriers (barriers). Figure 3 presents a graphic description of biogas productivity, depending on the selected system of work. The utilization system (periodic fermentation chamber filling system) and the microbiological system operating mode (quasi-continuous fermentation chamber filling system) were considered. The average daily biogas productivity (ABP) for the periodic system (PS) was calculated based on the total biogas productivity related to the hydraulic retention time (HRT = 27 days) (ABP-PS = 0.48 m3
Mg−1fresh matter). The average daily biogas productivity (ABP) for a quasi-continuous system (QCS) was obtained on the basis of average productivity for the period of optimal biogas production (ABP-QCS = 0.68 m3
Mg−1fresh matter). Based on the results of biogas productivity calculated for the periodic and quasi-continuous system (Fig. 3), the heating power obtained from biogas combustion was determined. The calculations (for periodic fermentation) were based on: dependence of heat obtained from biogas combustion (QU), hourly biogas productivity (WHU) and the average calorific value of biogas (WB) and efficiency of a gas boiler (ɳ) burning biogas (formula 2). QU ¼ WHU
WB


 g  100

ð2Þ

The calculations (for a quasi-continuous system) indicated the dependence of heat obtained from biogas combustion (QM), hourly biogas productivity (WHM) and the average calorific value of biogas WB and the efficiency of a gas boiler (ɳ) burning biogas (formula 3). QM ¼ WHM
WB


 g  100

ð3Þ

Table 5 Production of biogas heat for periodic fermentation Parameter

Symbol

Value

Unit of measure

The efficiency of a gas boiler and internal installation Average calorific value of biogas Cumulative productivity of biogas The duration of the process Average daily productivity of biogas The fermenting mass Daily biogas yield of the utilizer Hourly biogas yield of the utilizer Heat from biogas combustion Heating power from the combustion of biogas

η

96

%

WB WCAL t W0 m WDU WHU QU PHWM

17 13.04 27 0.48 7.85 3.79 0.16 2.58 716.19

MJ
m−3 m3
Mg−1.fresh matter days m3
Mg−1 fresh matter t m3
d−1 m3
h−1 MJ W

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Table 6 Production of biogas heat for quasi-continuous fermentation Parameter

Symbol

Value

Unit of measure

The efficiency of a gas boiler and internal installation Average calorific value of biogas Average daily productivity of biogas The fermenting mass Daily biogas efficiency of micro biogas plants Hourly biogas efficiency of micro biogas plants Heat from biogas combustion Heating power from the combustion of biogas

η

96

%

WB WQC M WDM WHM QM PHWM

17 0.68 7.85 5.34 0.22 3.63 1008.38

MJ
m−3 m3
Mg−1 fresh matter t m3
d−1 m3
h−1 MJ W

Calculations showed (Table 5) that the periodic fermentation system will not be able to cover the total heat requirement (716.19 W). The quasi-continuous fermentation system is characterized by a higher heat production (Table 6), which means that such a system can be regarded as self-sufficient in terms of energy (1008.38 W). The calculations were made for the fermentation chamber fill factor of 82%. The installation space on the side wall of the container (determined effective side surface of a 20-foot container 15.6 m2) was used and the photovoltaic installation and solar collector were proposed. The hybrid heating system can support the operation of two fermentation systems: periodic and quasi-continuous. The power of solar devices was determined as the real power of PV panels (solar collectors) and expressed in watts [W] [24]. The number of photovoltaic panels (4 pcs) and solar collectors (1 item) for the side surface of the container has been determined. For the calculations were adopted: the unit surface area of the PV panel (1.474 m2) and the active surface of the solar collector (2.130 m2). The power of solar devices was calculated in accordance with the published methodology [24] on the basis of the following formula 4: PSOL ¼ ME
S


g
n 100

ð4Þ

where: PSOL - real power of PV panels/solar collectors [W], ME - solar radiation power [Wm−2], S - active surface of the PV panel/solar collector [m2], η - efficiency of PV panel/solar collector [%], n - number of PV panels/solar collectors. It was assumed that the efficiency of the PV panel is 18% and the efficiency of the solar collector is 69%. Calculation results, comparing heat losses with potential heating power, were presented in two cases. The first case involves the cooperation of a gas boiler with a solar collector. The second case involves the cooperation of a gas boiler with a photovoltaic installation.

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Fig. 4 Comparison of heat losses and heating power obtained from the solar system and gas boiler

In the case of a hybrid system with a PV installation, a discount system was included in the calculation, which in 80% balances the use of electricity from the power grid (Fig. 4). Heating power and balances between sources, used in the analyzed system (Fig. 4). Heat sources were used: solar collector Hewalex Thermomax HP 400-20, 4 solar panels WINAICO feeding the electric heater and gas boiler VITODENS 200-W. Heat losses were calculated on the basis of heat transfer coefficients by individual walls and structural elements, using in this case average monthly temperatures in the day/night system for their comparison with the operation of the solar and biogas systems (Fig. 4). Despite the use of an additional solar system, calculations showed that 3 months (January, February and December) the system operates on the edge of the energy needs of the fermenter.

4 Summary and Conclusions The research showed that the cumulated biogas productivity reached the level of over 13 m3 from a Mg of fresh mass. The obtained results of biogas efficiency levels can be improved by increasing the digestibility of the mixture and better balancing macronutrients and the C/N ratio. A mixture of wastes with possibly varied composition was tested to approximate the real problems of waste disposal. The highly diversified composition of the mixture showed inhibitory qualities, thanks to which the level of biogas productivity was deliberately lowered.

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It has been shown that the change of chamber operation mode (periodic system to quasi continuous system) intensively increases the energy capacity of the fermenter, with a constant level of heat losses through the partitions. Obtained average daily biogas yields indicated that from the waste mix, productivity can be expected at 0.48 m3 of biogas from a tonne of fresh mass in the case of a periodic system and 0.68 m3 of biogas from a tonne of fresh mass in the case of a quasi-continuous system. Both biogas productivity results were used to analyze the energy efficiency of the digester in a periodic and quasi-continuous system. The considered systems (periodic and quasi-continuous) refer to the use of the proposed fermenter as a utilization or microbiogas plant. Identified energy shortages can be limited by optimizing the control of the biological process and optimizing the parameters of thermally insulating layers. The element of support may also be multiplication of chambers or additionally their mutual phase shift of daily biogas efficiency (biogas yield in periodic system). Identified energy shortages can be limited by optimizing the control of the biological process and optimizing the parameters of thermally insulating layers. The element of support may also be multiplication of chambers or additionally their mutual phase shift of daily efficiency.

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Standard Used in the Research 1. DIN 38414 S 8. Niemiecka znormalizowana metoda badań wody, ścieków i osadów. Osady i sedymenty (grupa S). Określenie charakterystyki fermentacji (S. 8). DIN Deutches Institut fur Normung e. V., Berlin (2012) 2. KTBL-Heft 84 2009: Schwachstellen an Biogasanlagen verstehen und vermeiden. Kuratorium für Technik und Bauwesen in der Landwirtschaft e.V. (KTBL), Darmstadt, Druckerei Lokay, Reinheim, 56 s 3. PN EN 12831 2004: Instalacje ogrzewcze w budynkach Metoda obliczania projektowego obciążenia cieplnego 4. PN-74/C-04540/00. Wydawnictwo Normalizacyjne. Warszawa. Oznaczenie zasadowości

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5. PN-75/C-04616/01. Wydawnictwo Normalizacyjne. Warszawa. Oznaczanie suchej masy osadu i substancji organicznych.Woda i ścieki. Badania specjalne osadów. Oznaczanie zawartości wody, suchej masy, substancji organicznych i substancji mineralnych w osadach ściekowych 6. PN-75/C-04616/04. Wydawnictwo Normalizacyjne. Warszawa. Oznaczenie lotnych kwasów tłuszczowych 7. PN-90 C-04540/01. Wydawnictwo Normalizacyjne. Warszawa. Woda i ścieki. Badania pH, kwasowości i zasadowości. Oznaczanie pH wód i ścieków o przewodności elektrolitycznej właściwej 10 µS/cm i powyżej metodą elektrometryczną

Possibilities of Using Biomass from Nutshells for Energy Purposes Andrzej Bryś, Magdalena Sokalska, Szymon Głowacki, Weronika Tulej, Joanna Bryś and Mariusz Sojak

Abstract Demand for energy, which is largely produced from fossil fuels, is increasing together with civilizational development. Using this type of fuels contributes to considerable pollution of the natural environment, and results in the increase of the average temperature worldwide. Another problem is that the deposits of fossil fuels will likely run out in the next century. In order to limit the greenhouse effect and other adverse effects of using fossil fuels, an attempt was made to find renewable resources of energy to replace them. One of such fuels that may successfully replace hard and brown coal, crude oil or even natural gas, is biomass, one type of which is nutshells. This work contains results of research on energy properties of nutshells of selected nut species. The following properties were examined: the nutshell share in the total mass of the nut, water content (u), moisture and ash content as well as calorific value of nutshells. The results of the conducted examinations indicate that the outer shells of nuts are characterized by very good energy properties, due to low moisture and small ash content as well as high calorific value. Keywords Biomass from nutshells Calorific value


Water content
Moisture
Ash content


A. Bryś (&)
M. Sokalska
S. Głowacki
W. Tulej
M. Sojak Faculty of Production Engineering, Department of Fundamental Engineering, Warsaw University of Life Sciences, SGGW, Nowoursynowska 164, 02-787 Warsaw, Poland e-mail: [email protected] J. Bryś Faculty of Food Sciences, Department of Chemistry, Warsaw University of Life Sciences, SGGW, Nowoursynowska 159 C, 02-787 Warsaw, Poland © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_2

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1 Introduction Consumption of energy, related to the industrial revolution increased sharply as early as in the 18th century. Continuous increase in consumption of energy has led to a situation, in which conventional resources of energy such as hard coal, brown coal, crude oil or natural gas deposits are running out. Therefore, people need to seek for new resources of energy. Moreover, the negative impact of fossil fuels on the natural environment is becoming a serious worldwide problem due to the fact that emission of pollution to the atmosphere resulted in global warming and acid rains. Scientific and technical development enabled finding new, renewable and more environmentally-friendly resources of energy, such as wind, water, solar and geothermic energy. Additionally, energy is produced from combustion of biomass, biogas or communal waste. The percentage share of different resources of energy (including renewable resources) in Poland for the years 2013–2015 is presented in Table 1. Table 1 presents changes in the percentage share of energy generated from different types of resources of energy over the period of three years, which shows that in the last few years, the share of renewable resources of energy such as biogas, wind, or liquid fuels increased at the expense of solid biofuels or water. Recently, due to increased ecological awareness of the society and implementations of new regulations issued by the European Union, the share of renewable resources of energy has increased. It is a very positive phenomenon but it is still insufficient. Moreover, in the near future, it will not be impossible to stop using conventional resources of energy and rely on renewable resources of energy. The structure showing the use of renewable resources of energy in Poland in 2015 is presented in Fig. 1. Figure 1 shows that solid biofuels have the highest share in renewable energy generation amounting to 72%, followed by liquid biofuels and wind energy, whose shares are equal to 11% each. Energy from biogas amounts to 3%, energy from water – 2%, and energy generated by heat pumps – 1%. Table 1 Percentage share of different resources of energy in Poland for the years 2013– 2015 [1]

Type of energy resource

2013

2014

2015

Heat pumps Biogas Water Communal waste Sun Geothermy Wind Solid biofuels Liquid biofuels

0.44 2.12 2.45 0.39 0.29 0.22 6.03 79.88 8.18

0.55 2.56 2.31 0.45 0.43 0.25 8.13 76.14 9.18

0.56 2.64 1.82 0.46 0.52 0.25 10.75 72.22 10.77

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Fig. 1 Percentage share of respective renewable resources of energy in Poland in 2015 [1]

Biomass is classified as a solid biofuel, and comprises liquid or solid biodegradable substances of animal or plant origin. It may also come from waste, agricultural or forestry by-products, as well as processing of related products by different industries; cereal grain intended or not intended for intervention purchase. Biomass is also obtained from communal and industrial biodegradable waste of animal and plant origin, including waste from waste processing installation and waste and water treatment installations, with special consideration to sewage sludge [2]. Biomass usually consists of fibrous materials, ashes and extracts. Fibrous materials in the plant biomass are mainly hemicelluloses, celluloses and lignins. Lignins are polymers, which increase mechanical and chemical resistance of cellulose walls, which are responsible for transport of water in cell walls, and their calorific value is equal to 28.8 MJ/kg. Celluloses are fibrous carbohydrates, which form the basis of walls of plants cells. The calorific value of cellulose is equal to 17.3 MJ/kg. Hemicelluloses are polysaccharides that form a quarter of plant substance. The heat value of hemicelluloses is equal to 16.2 MJ/kg [3]. The main chemical components of biomass are coal, oxygen and hydrogen. In energy industry, biomass is considered a fuel, which has numerous benefits for the environment, such as: • favourable balance of CO2 emission, which is connected with the fact that it takes up the same amount of CO2 during development as it is required during combustion, • decreased emission of SO2, • limiting consumption of fossil fuels, the deposits of which are constantly decreasing, and which will run out in the nearest future. Despite the above mentioned benefits, biogases also have drawbacks as they emit the following pollutants CH4, LZO, SOx, NH3, NOx, PM10 to the environment during combustion [4].

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2 Renewable Energy in the EU and in Poland There is a considerable disproportion between the amount of renewable energy produced in the EU and in Poland. This phenomenon is presented in Fig. 2, and is connected with the fact that there are no large power plants generating mostly renewable energy in Poland. Instead, there are a lot of ‘micro-sources’ of energy, which are largely located in rural areas due to the fact that rural areas dominate in Poland. In Poland, biomass plays the most important role out of all resources of renewable energy because of the fact that arable lands cover approx. 15 mln hectares, while only 5 mln ha is sufficient to satisfy the country’s food needs [5]. Based on Fig. 2, we may observe how small the share of renewable energy is in the total amount of energy produced both in the European Union and in Poland. In the European Union, the upward trend related to production of renewable energy started in 2009, when it amounted to 148.4 Mteo (mega tons of equivalent oil), followed by a decrease – in 2014 the production decreased to 68.2 Mteo. In Poland, the upward trend related to production of renewable energy continued until 2013 when the production reached 8.6 Mteo. In 2014 the production of renewable energy in Poland decreased to 8.1 Mteo. Biomass may come from substances of animal or plant origin, as well as substances from forestry and food-processing industry, as well as industrial and communal waste. Biomass is used in household furnaces as heat energy, but it may also be used to obtain biofuels and electrical energy, which shows its potential in terms of energy and versatility. Biomass production in Poland and in the EU, compared with the total production of renewable energy, is presented in Fig. 3. In Poland, activities to facilitate the development of electrical power industry based on biomass have been initiated. They include support for producers and investors, programs promoting biofuels, stimulation of development of bioenergy

Fig. 2 Primary energy in the EU and in Poland in the years 2001–2014 [1, 6]

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Fig. 3 Energy produced from biomass in the EU and in Poland in the years 2004–2013 [6]

production and production technology. Unfortunately, these activities are additionally hindered by numerous overlapping factors, including: • • • •

society’s reluctance towards RRE, lack of social awareness regarding RRE, too high cost of installation, lack of stable means of support [5].

Based on Fig. 3, it may be concluded that in Poland, energy from biomass has a very large share in the total amount of energy obtained from renewable resources of energy. In the years 2010–2012, it amounted to over 50% of the total energy from renewable resources. Nutshells, which are waste biomass from food industry, may be a good source of energy.

2.1

Production of Nuts Worldwide: Walnut (Juglans Regia L.), Hazelnut (Corylus Avellana L.), Peanut (Arachis Hypogaea L.) and Pistachio (Pistacia L.)

Walnut trees are grown in America, Europe, Asia and northern Africa, in the countries of western, south-eastern and central Europe, as well as Central and Minor Asia including Afghanistan and India, and reaching as far as China. Walnut trees are also grown in Canada, and in the northern and central USA. In Poland, walnut trees are mainly grown in the south-eastern part of the country, but they may also be found in the north, west, and south-east of Poland [7]. Hazel, together with other plants, forms undershrub in the forests in the whole moderate climatic zone of the northern hemisphere. It was cultivated in ancient Greece and Rome. Hazelnut trees are grown on a mass-scale in Turkey, Italy, the USA, Azerbaijan, Spain, Chile and France [8].

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Pistachio nuts come from eastern and central Asia. At present, it grows wild in Lebanon, Palestine, Syria, Iraq, Iran as well as in Southern Europe and desert countries of Asia and Africa. At present, industrial-scale production of pistachio nuts is mainly located in California, where plantations are modern, and intensively watered. Pistachio trees are also cultivated in a traditional way, without artificial watering systems in Iran, Turkey or Syria [10]. Peanuts come from South America, from Brazil. Presently, they are mainly cultivated in subtropical and tropical areas in such countries as China, India, USA, Argentina, Nigeria or Indonesia [10]. Main producers of peanuts, hazelnuts, walnuts and pistachio nuts are presented in Fig. 4. Production of nuts all over the world is varied depending on the kind of nut, and the season of the year. Every year is different in terms of temperature or rainfall, which results in higher or lower yields. Volumes of production of the above mentioned nut species for the 2004–2011 and 2014–2015 are presented in Figs. 5 and 6. Figure 5 shows walnut, hazelnut and pistachio production. Based on the data, it is possible to observe how nut production changed over the period of 11 years. Overall production of nuts in 2004 was considerably smaller compared with 2015. The figure also presents great changeability of production of each nut species, which is related to weather phenomena during the season.

Fig. 4 Main producers of walnut hazelnut, pistachio nut and peanut in the years 2014/2015, by countries [9]

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Fig. 5 Worldwide production of walnut, hazelnut and pistachio nut in the years 2004–2011 and 2014–2015 [9]

Fig. 6 Worldwide production of peanuts, hazelnuts, walnuts and pistachio nuts in the years 2004– 2011 and 2014–2015 [9]

Peanuts production has the highest share in the overall worldwide nut production amounting to millions of tons (Fig. 6). Due to so high amounts of peanut production, the figures for the overall production of hazelnuts, walnuts, and pistachio nuts were summed for the purpose of this comparison. Figure 6 shows a large disproportion between peanut production and production of other nut species. Also, a considerable increase in peanut production in 2015 may be observed, compared with the previous years.

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3 Goal and Scope of Work The goal of the work was to analyse the possibilities of using hazelnut, walnut, peanut, and pistachio nut shells for energy purposes. The scope of the work comprises general description and characterization of renewable resources of energy, including biomass as a product with the highest potential out of renewable resources of energy available. Nutshells of nuts grown in Poland and all over the world constituted the biomass for the analysis. The scope of research comprised determination of shell share in nuts of different species, water content (u) by means of dryer-weight method, determination of ash in the muffle furnace, and determination of calorific value in a bomb calorimeter.

4 Methodology Nuts of the four following nut species: walnuts, pistachio nuts, hazelnuts and peanut were examined. The material (the whole nuts including nutshell) was obtained from the production lines of plants processing nuts or bought in shops selling products for direct consumption. The examinations of nuts included: • determination of the content of shells in the total mass of nuts, • determination of water content (u) in nutshells using dryer-weight method • determination of ash content in shells following combustion in a muffle furnace at the temperature of 700 °C, • determination of calorific values of nutshells of different species in the constant volume conditions in a pressure bomb calorimeter in the oxygen atmosphere.

5 Results of Research Each species of nuts has a different shell, which is related to its percentage share in the total mass of the nut. Table 2, which presents the results of research, shows that the average percentage content of the shell in a nut was the lowest for peanuts, and amounted to 30.2%. The highest share of nutshell was observed for hazelnuts – 67,7%, followed by walnuts (60.7%), and pistachio nuts (57%), with the latter two having similar values to the hazelnut. It means that peanuts have the highest content of edible substance, while hazelnut, walnut and pistachio nuts mainly consist of shells. Out of the four examined nut species, the lowest water content was determined for pistachio nutshells – 0.002 kg H2O/kg d.s., which can be attributed to the fact that pistachio nuts undergo drying prior to being exported to Poland. A similar

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Table 2 Selected physical properties of nutshells of the examined species Nutshell

The shell share in the total mass of the nut %

Water content u (kg H2O/kg d.s.)

Moisture %

Ash content %

Calorific value kJ/g

Peanut Hazelnut Walnut Pistachio nut

30.2 67.7 60.7 57.0

0.050 0.158 0.124 0.002

4.8 13.7 11.0 0.2

2.00 0.74 1.38 1.42

20.71 20.04 19.74 19.31

situation may be observed for peanuts, which also undergo thermal treatment prior to transportation. The highest water content, equal 0.158 kg H2O/kg d.s. was determined for hazelnuts, which also have the highest moisture (13.7%). Table 2, presented above, shows that peanut shells have the highest ash content (2%), followed closely by pistachio nuts (1.42%) and walnut (1.38%). The lowest content of ash was determined for hazelnut—0.74%. Based on the obtained results, it may be concluded that hazelnut shells are the best fuel, considering the content of ash, and peanut shells are worst fuel, considering this parameter, probably because of the fact that peanuts grow underground, and have direct contact with soil. The data presented in Table 2, shows that pistachio nut shells have the lowest calorific value (19.31 kJ/g), and peanuts have the lowest calorific value – 20.71 kJ/ g. The best fuel, in terms of calorific value, is peanut shells, followed by hazelnut shells, while pistachio nut shells and walnut shells have lower calorific values, and are fuels of worse quality.

6 Summary and Conclusions Energy from renewable resources of energy constitutes an auxiliary source of energy for conventional resources of energy. It is crucial for our future. Therefore, new sources of renewable energy are being sought, and use of existing resources of renewable energy is being optimized. Nutshells have very good properties, which makes them suitable for energy purposes. They are characterized by low moisture, small ash content, and high calorific value, which results in nutshell biomass having very good properties. As worldwide production of nuts increases every year, the amount of nutshells to be used as biomass rises. Based on the results of research, it may be concluded that hazelnuts (67.7%) have the highest share of shell in the mass of the nut, followed by walnuts (60.7%) and pistachio nuts (57%), with peanuts having the lowest share (only 30.2%). The lowest water content u was determined for pistachio nutshells (0.002 H2O/kg d.s.), and peanut nutshells (0.05%), which can be attributed to the fact that these species are imported from abroad, and undergo thermal treatment – drying, which prevents microbiological spoilage, prior to transportation. Moreover, peanuts are washed prior to drying to remove soil from their surface. Therefore, the

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thermal treatment they undergo is very intensive. The highest water content (u), determined for walnut (0.158 H2O/kg d.s.), which is similar to the values for hazelnut, may be attributed to the fact that these two species are grown in Poland, and do not undergo such intensive thermal treatment. Examinations of ash content in shells of different species of nuts show that peanuts have the highest ash content (2%), which can be attributed to their chemical composition, and the fact that they have direct contact with soil as they grow underground. Pistachio nut and walnut shells also have high ash content of 1.42% and 1.38%, respectively. Ash content parameter is directly connected with chemical composition of shells. The best fuel in terms of calorific value is peanut shells, whose calorific value is equal 20.71 kJ/g, followed by hazelnut shells (20.04 kJ/g). The lowest calorific value equal to 19.31 kJ/g was determined for pistachio nuts. Theoretically, in 2014, the total worldwide production of nutshells of the examined species of nuts, i.e. hazelnuts, walnuts, pistachio nuts and peanuts for energy purposes might replace 5.9 million tons of coal, and in 2015 – over 6.7 million tons, considering the calorific value for coal equal 40.2 MJ/kg, which means that using at least a fraction of this by-product has justified economic and environmental benefits

References 1. Główny Urząd Statystyczny, 2016, Energia ze źródeł odnawialnych w 2015 r., Warszawa 2. Dz. U. 2015 poz. 478. Ustawa z dnia 20 lutego 2015 r. o odnawialnych źródłach energii 3. W. Ciechanowicz, S. Szczukowski, Ogniwa paliwowe, wodór, metanol i biomasa szansą rozwoju obszarów wiejskich i zurbanizowanych (Kolegium wydawnicze UWM, Olsztyn, 2015) 4. T. Nussbaumer, Aerosols from Biomass Combustion (International Energy Agency, Switzerland, 2001) 5. K. Krzyżanowska, K. Nuszkiewicz, Alternatywne źródła energii i ich zastosowanie (Wydawnictwo Zespołu Szkół Centrum Kształcenia Rolniczego im, Jadwigi Dziubińskiej w Golądkowie, Golądkowo, 2014) 6. Główny Urząd Statystyczny, 2012, Energia ze źródeł odnawialnych w 2011 r., Warszawa 7. H. Zdyb, Leszczyna (PWRIL, Warszawa, 2010) 8. S. Zagaja, Z. Suski, Orzech włoski i leszczyna (PWRIL, Warszawa, 1991) 9. Internet, https://www.nutfruit.org/wp-continguts/uploads/2015/11/global-statistical-review2014-2015_101779.pdf. Accessed 13 May 2017 10. J. Janick, R.E. Paull, The Encyclopedia of Fruit & Nuts (CABI, London, 2008)

Study of PAR Intensity Distribution in Cylindrical Photobioreactors Beata Brzychczyk, Tomasz Hebda and Jan Giełżecki

Abstract The production of microglons for energy purposes is difficult and costly. One of the important parameters influencing the efficiency of photosynthesis in photobioreactors is light radiation. In order to obtain information on the distribution of intensity of photosynthetic active radiation PAR in the PBR space measurements of the photon flux (PPFD) were measured at the nodes of the measured mesh. The tests were made for two cylindrical LEDs in designed photobioreactors. The measurements were made during the culture inside the culture medium using a Quantum MQ-200 Apogee Instruments Quantum Digital Meter. The tests were performed for the different intensity of light, light colour and the length of exposure time. Preliminary lighting studies have spearheaded the first stage of the modeling and lighting optimization process in the designed photobioreactors. They allowed the following conclusions: • No statistically significant differences were found between the instantaneous intensity of PAR radiation for the analyzed photobioreactors, • The increase in biomass of alga results in a change in the intensity distribution of photosynthetic active radiation PAR in photobioreactors, • The increase in optical density in the photobioreactor causes a decrease in light intensity within the reactor. Keywords Photosynthetically active radiation (PAR) Photosynthetic photon flux density (PPFD) Microglons photobioreactor




B. Brzychczyk (&)
T. Hebda Faculty of Production and Power Engineering, Department of Mechanical Engineering and Agrophysics, University of Agriculture in Krakow, Ul. Balicka 120, 30-149 Kraków, Poland e-mail: [email protected] J. Giełżecki Faculty of Production and Power Engineering, Institute of Agricultural Engineering and Informatics, University of Agriculture in Krakow, Kraków, Poland e-mail: [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_3

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1 Introduction The problem of breeding these simplest organisms transforming diffused radiation energy into a higher level to meet the energy needs of the modern world is still open and current [1]. This leads to a lot of work related to the use of algae for biofuel production [3, 5] or biogas [11, 12, 17, 20]. Recent scientific work brings new insights into the effectiveness of systems especially closed photobioreactors which offer better control of breeding conditions. The main problem in the design of efficient photobioreactors is the amount of energy, the specification and the selection of parameters that govern photobioreactors’ performance relative to the model used and the creation of technical bases to facilitate optimization and scaling [9, 10, 14–16, 21]. From the point of view of delivering radiation energy to a large-scale biomass production system efficient photobioreactors are required to provide effective exposure to light. The process of converting light, whether natural or artificial, is essentially a dynamic and variable process. Just mixing water in a photobioreactor causes the cells to be exposed to light radiation at different times. The spatial distribution of the microglobes particles involved in the photosynthesis process changes the radiation field and the availability of light energy in the PBR space [8]. Although many studies have shown significant lightness and agitation conditions this knowledge is still insufficient to determine the algal and cropping systems optimal for the species and the available quantitative data is usually empirically determined [2, 14]. In addition, the distribution of photon flux in photobioreactors is not well represented by the Lambert-Beer law and three-dimensional simulations on the system are necessary to calculate accurately the time exposure of microorganisms to light [6]. For photosynthetically active radiation, radiation from the range 380 nm–710 nm [18] is most commonly used. PAR radiation is absorbed by photosynthetic dyes— chlorophylls, organic compounds present in plants, algae and photosynthetic bacteria. The function of chlorophyll in photosynthetic organisms is the absorption of light quanta and the processing of energy. Chlorophyll and chlorophyll b are the most widespread in nature and occur in all plants dyes. Chlorophyll c and d are found only in some algae. Green chlorophyll color is caused by high absorption in the red and blue parts of the light spectrum and low absorption in the part of the green light spectrum (500 nm–600 nm wavelength) [4, 7, 19]. The maximum absorption for chlorophylls is in the violet-blue range of 400 nm–500 nm and orange-red 600 nm– 700 nm. The maximum absorption for chlorophyll a is 420 nm and 668 nm for chlorophyll b 440 nm and 648 nm, while for carotenoids the maximum absorption is in the range of 400 nm–500 nm with a maximum of 420 nm, 450 nm and 480 nm. The intensity of photosynthesis depends on the intensity of radiation in the PAR range. The increase in intensity of the radiation is accompanied by an increase in the intensity of photosynthesis to saturate this process. The photosynthesis is saturated at an average of about 800 lmol m−2 s−1. At about 600 lmol m−2 s−1 linear dependence of photosynthesis is observed on the intensity of irradiation. The smooth flow of photosynthesis does not require such high levels of solar radiation. In many

Study of PAR Intensity Distribution in Cylindrical Photobioreactors

29

situations excessive sun exposure can be harmful. The inability to process the collected energy and additionally too low temperatures lead to photoinhibition—permanent or temporary damage to the photosynthetic apparatus (PS II). During photoinhibition, the photochemical reactions (light dependent) are smooth. The enzymatic reactions of photosynthesis (light independent but temperature dependent) are limited. The intensity of the radiation below the light-saturation of photosynthesis is limited by the intensity of photosynthesis [13].

2 Target The aim of the experiment was to investigate the distribution of the intensity of photosynthetic active radiation of PAR inside photobioreactors of PBR I and PBR II together with the preliminary analysis of the designed lighting for the assumed farms. It was hypothesized that the concentration of cells in the culture medium depends on the distribution of light in the photobioreactor geometry, the type of lighting and the optical properties of the medium. The research shows that not only type of lighting characterized by a photon stream, but also the exposure time of a single microalgae cell to light is an important breeding parameter.

3 Methodology of Measurement The study was conducted for two identical light sheaths in cylindrical photobioreactors of 4.5 dm3 each. The active capacity of the bioreactors was 3.996 dm3. The culture was inoculated with 4 mL of chlorella vulgaris type BA0002a obtained from the Baltic Sea Collection (CCBA) of the Institute of Oceanography UG. The photovoltaic reactor cultures were illuminated in a 16.5 h/7.5 h—day/night system. The culture temperature during the exposure time was 32.8 C for PBR I and 34.2 C for PBR II. The breeding was carried out in a periodic system. Reactors (inner diameter 173 mm, height 170 mm) with established cultures were located inside the cylindrical light sheaths. The inner diameter of the light sheaths was 246 mm, the height of the casing was 190 mm. Each light jacket included 150 RGB LEDs, programmer and power supply. The following experiments were carried out on the designed test bench. The intensity distribution of the PAR intensity for PBR I and PBR II lighters was determined at a 96-h interval between the two experiments. For the identical culture (CO2 enrichment, nutrient, light), the amount of biomass in the culture medium was determined. Biomass growth was determined by direct method counting cells under microscope using Thoma cell. Table 1 shows the results of cell counts for two photobioreactors carried out on individual days of experiments.

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Table 1 Number of Chlorella vulgaris cells type BA0002a in ml Date 2016/12/04 2016/12/08

PBR I number of cells ml−1 6

6.77
10 17.1
106

PBR II number of cells ml−1 7.5
106 19.7
106

In addition, the density distribution of the PAR intensity for the light jacket in PBR photobioreactor was determined taking into account different optical densities. Optical density measurements were made using a densitometer. Quantum MQ-200 Apogee Instruments (Figs. 1 and 2) with waterproof immersion probes with a spectral range of 410 nm to 655 nm were used to measure the photosynthetic active PAR radiation. The diameter of the touch probe was 2.4 cm and the height was 2.8 cm. Measurement of density distribution of the photon flux was made inside the culture medium. Units of measurement were mol m−2 s−1, indicating the amount of light energy available to photosynthetic organisms irrespective of the type of illumination.

Fig. 1 Quantum MQ-200 Apogee Instruments quantum digital meter; (own elaboration)

Fig. 2 Measurement error at a specified angle of incidence [22]

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The measurement was made using a designed tripod that enabled the touch probe to move inside the reactor both vertically and horizontally. Measurement points were placed in the form of a grid as shown in the diagram (Fig. 3). The meter probe was traversed horizontally across the photobioreactor’s radius to its axis with a 10 mm step then the probe was lifted vertically on the tripod also with a 10 mm step. Figure 2 contains a diagram of the test bench with the distribution of measurement points. Average results from 10 measurements of the density distribution measurements of the photosynthetic radiation stream from the spectral range measured by the meter are shown in Fig. 5. The graphs show the distribution of the instantaneous photon-active photon radiation stream PAR measured inside the culture in the PBR I and PBR II bioreactors. The distance “d” changed from the inner wall of the reactor to its radius in the direction of the axis. Fig. 3 Test station layout: 1- photobioreactor, 2-LED light jacket, 3-touch probe, 4 measuring points, 5-axis reactor symmetry, 6-tripod, own elaboration

60 PBR I (avg)

50

PBR II (avg) PPFD,μmol m-2s-1

Fig. 4 Density distribution of the photon beam of PAR radiation in the photobioreactor PBR I and PBR II from the light source of 2016/12/04, d-distance measured from the inner wall of the bioreactor along the radius in the direction of the PBR axis, mm

40 30 20 10 0 0

10

20 30 40 50 60 distance measured d, mm

70

80

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Fig. 5 Distribution of density of the photon beam of PAR radiation in the photobioreactor section PBR I and PBR II of 2016/12/08

PPFD, μmol m-2s-1

70 60

PBR I (avg)

50

PBR II (avg)

40 30 20 10 0 0

20 40 60 distance measured d, mm

80

In both photobioreactors the distribution of the instantaneous PAR intensity for the PAR spectrum measured by the meter is similar. Based on the obtained results of the research and the theory on radiation issues an exponential function has been preliminarily used to estimate the amount of energy. At this stage of modeling, the function depends only on one parameter, which is the distance from the light source. Similar results and character of the curves were achieved by [6] in the photobioreactor modeling and photodynamic simulations for different densities of the culture medium. The decrease in the amount of available light energy into the bioreactor is exponential. Hypothetically dividing the reactor area into coaxially located cylindrical divisions spaced apart by the additional distance Dd on the basis of the accepted measurement functions it is possible to pre-estimate the amount of energy absorbed in a given layer by the biomass. Figure 4 shows graphs of the instantaneous photon-dynamic photon emission photon bursts PAR performed after 4 consecutive days. It has been observed that the biomass increase caused a change in the intensity distribution of the photosynthetic active radiation PAR in the designed photobioreactors although the overall nature of the curves has not changed. The light that enters the water is absorbed by the biomass of algae. You can not exclude multiple reflections in the layout. After applying the curves for each reactor separately from the first and second experiment it was observed how the nature of the instantaneous radiation distribution curves changed over 96 h for a given light jacket with biomass growth (Fig. 6). The most accurate matching of the theoretical model to the test results, determined by the value of the determination coefficient, was obtained for the exponential model. Table 2 shows the model parameters and R2.

Study of PAR Intensity Distribution in Cylindrical Photobioreactors Fig. 6 Comparison of PAR density distribution in photobioreactors in subsequent cycles

33

70

PPFD, μmol m-2s-1

60

PBR I (2016/12/04) PBR II (2016/12/04) PBR I (2016/12/08) PBR II (2016/12/08)

50 40 30 20 10 0 0

20

40

60

80

distance measured d, mm

Table 2 Mathematical form of momentary intensity distributions PAR for PBR I and PBR II

Date measurement

PBR I Model

2016/12/04

fPBRI ðd Þ ¼ 51:995e0:037d

99.42

2016/12/08

0:078d

94.90

R2, %

fPBRI ðd Þ ¼ 29:393e PBR II Model

R2, % 0:04d

2016/12/04

fPBRII ðd Þ ¼ 47:159e

98.85

2016/12/08

fPBRII ðd Þ ¼ 34:258e0:036d

92.78

The next part of the experiment included a preliminary evaluation of the photobioreactor photovoltaic (PBR I) shroud against three different optical densities of the culture medium. The optical density of the medium was determined by a McFarland (McF) densitometer. The adjusted equations of the regression curves based on the obtained experiment results and the density value of the culture medium are given in Table 3. With the increase in optical density the light radiation reaching the reactor was weakened. The higher the optical density, the smaller the instantaneous flow of Table 3 Mathematical form of momentary intensity distributions PAR for different optical densities No.

Optical density, q, McF

Character mathematical

1

2.36

fPBRI ðd; qMcF Þ ¼ 37:311e0:04d

2

2.70

3

6.19

R2, % 99.52

0:056d

98.38

0:088d

98.96

fPBRI ðd; qMcF Þ ¼ 32:798e fPBRI ðd; qMcF Þ ¼ 38:885e

34

B. Brzychczyk et al.

45 PBR I avg (2,7 McF)

40

PPFD, µmol.m-2s-1

35

PBR I avg (6,19 McF)

30 PBR I avg(2,36 McF)

25 20 15 10 5 0 0

20 40 60 distance mesured d, mm

80

Fig. 7 Distribution of average momentary intensity of PAR radiation in the photobioreactor PBR I cross section for different optical densities

60 PBR I (numers of cells a)

PPFD, µmol m-2s-1

50

PBR I (numers of cells b) PBR I (numers of cells c)

40 30 20 10 0 0

20

40

60

80

distance measured d, mm Fig. 8 Distribution of average instantaneous intensity of PAR radiation in PBR I photobioreactor cross section for a number of cells: a-6.77
106 cells/ml, b-17.10
106 cells ml−1, c-11.94
106 cells ml−1

Study of PAR Intensity Distribution in Cylindrical Photobioreactors

35

quantum photosynthetic radiation. The graph in Fig. 7 shows the changes in the exponential curves of the instantaneous PAR intensity for different optical densities and different cell numbers. Figure 8 shows graphs comparing the curves of the instantaneous intensity of PAR radiation for the PBR light bulb I, taking into account the cell density expressed by the number of cells. The graphical interpretation of the test results confirms the hypothesis that the smaller the number of cells in the medium, the more energy in the form of photosynthetic radiation in the reactor. An increase in the number of cells increases the energy absorption of photons.

4 Conclusions Preliminary lighting studies have spearheaded the first stage of the modeling and lighting optimization process in the designed photobioreactors. They allowed the following conclusions: • No statistically significant differences were found between the instantaneous intensity of PAR radiation for the analyzed photobioreactors, • The increase in biomass of alga results in a change in the intensity distribution of photosynthetic active radiation PAR in photobioreactors, • The increase in optical density in the photobioreactor causes a decrease in light intensity within the reactor, • The most accurate matching of the theoretical model to the test results was obtained for the model of:

y ¼ a: eb:d

ð1Þ

where: y-density of photons, lmol m−2 s−1, a, b-constant model, d-distance measured from the inner wall of the bioreactor along the radius in the direction of the PBR axis, mm. The above tests were performed for the different intensity of light, light colour and the length of exposure time. Acknowledgments This Research was financed by the Ministry of Science and Higher Education of the Republic of Poland (statutory activities DS 3600/WIPiE/2018), Faculty of Production and Power Engineering, university of Agriculture in Krakow.

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References 1. 2. 3. 4.

5. 6. 7. 8. 9.

10. 11. 12. 13. 14.

15. 16.

17. 18. 19. 20. 21.

22.

L. Brennan, P. Owende, Renew. Sustain. Energy Rev. 14(2), 557–577 (2010) N.T. Eriksen, Biotech. Lett. 30(9), 1525–1536 (2008) Y. Chisti, Biodiesel from microalgae. Biotechnol. Adv. 25(3), 294–306 (2007) F.L. Figueroa, S. Salles, J. Aguilera, C. Jiménez, J. Mercado, B. Viñegla, M. Altamirano, Effects of solar radiation on photoinhibition and pigmentation in the red alga Porphyra leucosticta. Mar. Ecol. Progr. Ser. 151, 81–90 (1997) G.H. Huang, F. Chen, D. Wei, X.W. Zhang, G. Chen, Biodiesel production by microalgal biotechnology. Appl. Energy 87(1), 38–46 (2010) B. Kong, R.D. Vigil, Bioresour. Technol. 158, 141–148 (2014) M.P. Lesser, Limnol. Oceanogr. 41(2), 271–283 (1996) M. Cassano, W.P. Schleich, Phys. Rev. A 52, R3429 (1995) A. Miron Sanchez, A. Contreras Gomez, F. Garcia Camacho, E. Molina Grima, Y. Chisti, Comparative evaluation of compact photobioreactors for large – scale monoculture of microalgae. J. Biotechnol. 70, 249–270 (1999) E. Molina Grima, Photobioreactors: light regime, mass transfer, and scaleup. J. Biotechnol. 70, 231–247 (1999) M. Montingelli, S. Tedesco, A. Olabi, Renew. Sustain. Energy Rev. 43, 961–972 (2015) J.H. Mussgnug, V. Klassen, A. Schlüter, O. Kruse, J. Biotechnol. 150(1), 51–56 (2010) J. Pilarski, K. Tokarz, M. Kocurek, Plant adaptation to light spectra composition and intensity. Works of the Electrotechnical Institute (256) (2012). ISSN 0032-6216 J. Pruvost, Chap. 19 – Cultivation of Algae, in Photobioreactors for Biodisel Production, Biofuels. Alternative Feedstocks and Conversion Processes (2011), pp. 439–464. https://doi. org/10.1016/B978-0-12-385099-7.00020-6 O. Pulz, Photobioreactors: production systems for phototrophic microorganisms. Appl. Microbiol. Biotechnol. 57, 287–293 (2001) E. Sforza, D. Simionato, G.M. Giacometti, A. Bertucco, T. Morosinotto, Adjusted light and dark cycles can optimize photosynthetic efficiency in algae growing in photobioreactors. PLOS ONE 7(6), e38975 (2012). https://doi.org/10.1371/journal.pone.0038975 A. Vergara-Fernández, G. Vargas, N. Alarcón, A. Velasco, Biomass Bioenerg. 32, 338–344 (2008) J. Weiner, Life and evolution of the biosphere. General Ecology Guide (PWN Scientific Publisher, Warsaw 1999). ISBN 83-01-12668-X (in Polish) K.M. Weyer, D.R. Bush, A. Darzins, B.D. Willson, Bioenergy Res. 3(2), 204–213 (2010) P.E. Wiley, J.E. Campbell, B. McKuin, Water Environ. Res. 83(4), 326–338 (2011) J. Wolf, E. Stephens, S. Steinbusch, J. Yarnold, I.L. Ross, C. Steinweg, A. Doebbe, C. Krolovitsch, S. Müller, G. Jakob, O. Kruse, C. Posten, B. Hankamer, Multifactorial comparison of photobioreactor geometries in parallel microalgae cultivations. Algal Res. 15, 187–201 (2016). https://doi.org/10.1016/j.algal.2016.02.018 www.apogeeinstruments.co.uk/content/MQ-100-200-300-manual.pdf. Accessed 7 Aug 2017

Drying Kinetics of Selected Waste Biomass from the Food Industry Beata Brzychczyk, Bogusława Łapczyńska-Kordon, Tomasz Hebda and Jan Giełżecki

Abstract In recent years, biomass is one of the most important renewable energy sources. Most often it is a material with a high water content, which reduces its energy potential. Therefore, it is necessary to carry out the preliminary drying phase. The purpose of the work was to analyze the kinetics of drying of waste resulting from the production of juices obtained by extrusion. Drying process (forced convection, medium flow rate 1.5 m s−1 are, initial relative humidity 5–10%) were carried out at various temperatures of 45, 76, 96 °C, for apple pomace, formed in the form of cuboidal cubes. The influence of process parameters on the drying kinetics was determined. The drying curves and the drying rate over time and the water content in the sample at a given process temperature were analyzed. Keywords Convective drying


Apple pomace
Energy properties

1 Introduction In connection with the emerging and repeatedly signaled problem of seasonal waste management - pomace from the process of pressing fruit and vegetable juices, at local small producers, a cycle of research and actions that could support the process of their development at the place of production was initiated. The waste that is produced, in large quantities, in a short period of time as an unstable material with a high water content quickly undergoes molding and crushing and requires efficient treatment so that they can be classified as raw material for reuse [1, 2]. Bearing the above in mind, research into the kinetics of drying fruit pomace from seasonal B. Brzychczyk (&)
B. Łapczyńska-Kordon
T. Hebda Faculty of Production and Power Engineering, Department of Mechanical Engineering and Agrophysics, University of Agriculture in Krakow, Kraków, Poland e-mail: [email protected] J. Giełżecki Faculty of Production and Power Engineering, Institute of Agricultural Engineering and Informatics, University of Agriculture in Krakow, Kraków, Poland © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_4

37

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apples created in the juicing process has begun. A convection drying process was used to manage the waste in order to preserve the raw material for further processing, storage and/or reduction of weight, and increasing calorific value. The convection drying process used in steady conditions is one of the oldest methods of removing the water content. The driving force of the process is the increased temperature difference between the product and the drying agent (air), causing the migration of water. The most important parameters of convection drying are: medium temperature, medium flow rate, relative humidity [3–6]. The convection drying process disappears after obtaining the equilibrium moisture. Removal of water, depending on the speed of drying and temperature causes deformation of the shape and thus the change in volume, internal porosity, density change [7, 8]. Unfavorable changes caused by convection drying are limited by the selection of appropriate parameters such as temperature, humidity and speed of the drying medium [9, 10].

2 Target The purpose of preliminary research was to analyze the kinetics of convection drying of apple pomace and to explain the influence of selected material properties on the drying process. The scope of research included determining the energy properties of apple pomace: analytical moisture of the material, heat of combustion, calorific value, volatile content, ash and drying kinetics, drying speed, shrinkage for processes carried out at different temperatures.

3 Methodology of Measurement The raw material for testing was apple julep from the Idared variant from the juicing process. The test material was formed in the form of square cuboids. The geometrical dimensions (a, b, c) of the samples with an accuracy of ±0.01 mm were determined using the callipers. The dimensions of the samples subjected to the experiments were in the following ranges: a = (21.58 – 32.92) ± 1 mm; b = (27.00 – 35.21) ± 1 mm; c = (7.00 – 15.60) ± 1 mm. Samples were stored at about −18 °C. The apple pomace before the experiment was subjected to a thawing process under natural convection conditions (ambient temperature 20 °C– 23 °C) for about 10 min. The samples were then placed in the basket of the laboratory scale, inside the dryer. Drying was carried out using an ELKON laboratory drier (KC 100N), by forced convection at v = 1.5 m
s−1, with a drying agent humidity of 5–10%, at temperatures (t) 46, 76, and 94 °C at normal pressure in the drying chamber. The TES-1307 temperature meter with a set of K type thermocouples connected via the interface with a PC computer was used to record the sample temperature and the temperature inside the drying chamber. Temperature

Drying Kinetics of Selected Waste Biomass from the Food Industry

39

registration took place every 30 s with an accuracy of ±0.1 °C using the program Temp Monitor_S2 v 1.0.16. The mass change of the samples was measured using a laboratory scale AS.220.R2 220 g/0.0001 g (Radwag) with an accuracy of 0.0001 g using the Measure-Win v.5.2.0 software. The tests were carried out to establish a constant mass, in the set process parameters, separately for each sample with a registration frequency every 30 s. Each experiment was repeated three times. For the purpose of the publication, results with a read-out every 270 s were presented. In addition, the dry matter content was determined in raw apple pomace by drying the samples at 115 °C ± 5 °C. On the basis of the obtained measurement data, the kinetics of drying for samples dried under different temperature conditions were developed, while maintaining the established conditions. Drying curves were determined, the reduced content of water in the material was determined (Ured), drying speeds were determined and the shrinkage coefficient and internal porosity were determined. The shrinkage was calculated based on geometrical measurements of the samples before and after drying. In addition, energy parameters were determined: analytical humidity of the material according to PN-EN ISO 18134-3: 2015-11, heat of combustion and calorific value according to PN-EN ISO 18125: 2017-07, content of volatile components as per PN-EN 18123: 2016-01 and ash according to PN-EN ISO 18122: 2016-01. The characteristic parameters for apple pomace are determined in tables (Tables 1 and 2). Material shrinkage was calculated with a large approximation based on geometrical measurements before and after the drying process at a given temperature. Table 2 lists the calculated shrinkage coefficients. The highest shrinkage coefficient was obtained for the lowest temperature, while for temperatures of 76 and 94 °C comparable. In addition, the average apparent density after the drying process was calculated as a function of temperature. The highest apparent density was obtained

Table 1 Averaged values of the physicochemical properties of apple pomace parameters Parameter

Symbol

Unit

Parameters of apple pomace dried at 105 °C % Moisture Mad MJ kg−1 Gross calorific value qv,gr,d MJ kg−1 Calorific value qp,gr,d % Content of volatile parts Vd % Ash Ad Parameters of raw apple pomace kg H2O kg−1 Average water content xw Average apparent density q g cm−3 kg m−3 Average mass density qm Average internal porosity e –

Value

Reference

4.205 19.174 17.170 80.84 1.57

[11] [12] [12] [13] [14]

0.812 0.8095 1075 0.244

[15] [15] [16] [16]

40

B. Brzychczyk et al.

Table 2 Average contraction factor Average apparent density, after the drying process, g cm−3

Shrinkage factor %

t, °C

0.44 0.60 0.41

28.79 28.39 41.67

94 76 46

for the process carried out at 76 °C. For convective drying of apple pomace, the average apparent density at both 46 and 94 °C did not differ significantly. All the experiments were carried out on a research stand consisting of the following elements: automation system and registration of process parameters and data of experiments carried out together with a PC computer and software, drying chamber, laboratory scale, temperature meter together with thermocouples. Figure 1 provides a schematic diagram of the test bench. The results of the conducted experiments are shown in the graphs of Figs. 2, 3, 4, 5, 6, 7, 8, 9 and 10. The experiments were carried out under conditions determined for the following temperatures: 46, 76, 94 °C. Figure 2 presents the results of measurements of temperature inside the sample during the processes. The first stage of drying (about 16 min) is connected with placing the sample in the drying chamber, leveling the set process temperature after the chamber is cooled down and reaching a constant temperature through the sample (Fig. 2). The diagrams in Figs. 3, 4 and 5 show the drying curves of the material as a function of time for individual temperatures of the processes carried out, along with the determined regression curves. All graphs show typical changes in absolute humidity over time. In the first stage of the process, a significant decrease in the water content associated with simultaneous increase in dry matter in the sample is visible. At higher temperatures, the drying period is shortened and it can be seen that for the process carried out at 94 °C it is the shortest. The following deceleration of changes in humidity over time after obtaining in all samples of the tested material a critical point corresponding to critical humidity, begins the second drying period with a decreasing rate of water discharge from the sample surface. After exceeding the next characteristic point, the drying curve in each case approaches the equilibrium moisture content [7, 10]. Comparison of curves for drying apple pomace (Figs. 3, 4 and 5) from the temperature of the conducted process allows to observe similar their course. The higher the temperature of the process, the shorter the drying time, which is confirmed by studies conducted by other researchers on apples. The speed of drying depends on the rate of heat transfer to the dried material. Sample time, for the selected case, needed to dry an apple pomace sample with a water content of 0.1 kg H2O
(kgs.s)−1 (u·(uo)−1 = 0.126) at 94 °C was 315 min (5 h and 25 min)—Fig. 3. Time required to dry the apple pomace sample with water content 0.1 kg H2O·(kgs.s.)−1 (u·(uo)−1 = 0.122) in temperature 76 °C it was up 749 min (12 h and 48 min) – Fig. 4.

Fig. 1 Schematic diagram of the laboratory stand; 1-microcontroller, 2-temperature sensor, 1-temperature sensor 2, 3-weight, 4-sample, 5-dryer, 6-fan. (own study)

Drying Kinetics of Selected Waste Biomass from the Food Industry 41

42

B. Brzychczyk et al. 120

100

t, °C

80

60

40 t1, °C t2, °C

20

t3, °C me τ,sec 0 0

5000

10000

15000

20000

25000

30000

35000

40000

Fig. 2 Characterization of temperature changes inside the sample for different process temperatures

5.0

120

4.5 100

4.0

80

3.0 u(temp.94°C), kg H2O·(kg s.s.)¯¹ t3, °C Poly. kg H2O·(kgH2s.s.)¯¹ trend(u(temp.94°C), line (u(temp. 94°C)·(kg O s.s.)) -1)

2.5

60 t, °C

u, kg H2O·(kg s.s.)¯¹

3.5

2.0

40

1.5 1.0

20

0.5 me τ, sec 0

0.0 0

5000

10000

15000

20000

25000

30000

35000

Fig. 3 Curve for drying apple pomace as a function of time (u = f(s), kg H2O·(kgs.s.)−1), for temp. 94 °C

Drying Kinetics of Selected Waste Biomass from the Food Industry

43

5.0

90

4.5

80

4.0

70 60

u(temp. 76°C), kg H2O·(kg s.s.)¯¹

3.0

t2; °C trend (u(temp. 76°C)·(kg H2Os.s.)¯¹ s.s.)-1)) Poly. line (u(temp. 76°C), kg H2O·(kg

50 t, °C

2.5

40

2.0 30

1.5

20

1.0 0.5

me τ, sec

0

0.0 0

5000

10000

15000

20000

25000

30000

35000

Fig. 4 Curve for drying apple pomace as a function of time (u = f(s), kg H2O
(kg temp. 76 °C

−1 s.s.) )

4.5

50

4.0

45

for

40

3.5 u, kg H2O·kg¯¹s.s.

10

3.0

35

u(temp.46°C), kg H2O·(kg s.s.)¯¹

30

t1; °C 2.5

Poly. kg H2O·(kg trend (u(temp.46°C), line (u(temp. 46°C)·(kg H2s.s.)¯¹ O s.s.))-1)

25

2.0 20 1.5

t, °C

u, kg H2O·(kg s.s.)¯¹

3.5

15

1.0

10

0.5

me τ, sec

0.0

5 0

0

10000

20000

30000

40000

50000

60000

70000

80000

Fig. 5 Curve for drying apple pomace as a function of time (u = f(s), kgH2O·(kgs.s.)ˉ1) for temp. 46 °C

44

B. Brzychczyk et al. 1

120 U(red.); 46°C U(red.); 94°C t2, °C

0.9

0.7

100

80

0.6 0.5 U 0.4

60 t, °C

u(red.), kg·kg¯¹

0.8

U(red.); 76°C t1, °C t3, °C

40

0.3 0.2

20

0.1 me τ,sec 0

0 0

5000

10000

15000

20000

25000

30000

35000

Fig. 6 Comparison of drying curves of reduced water content in apple marc samples as a function of time (u (red) = f(s)), kg H2O·(kgs.s.)−1 for different temperatures

0.5

120

0.45 100

0.4

80

du/dτ;kg·s¯¹·m¯², (temp. 94°C) 0.3

t, °C

du/dτ;kg·s¯¹·m¯²

0.35 t3, °C

0.25

60

0.2 40

0.15 0.1

20

0.05 0

0 0.00

1.00

2.00

3.00

4.00

u, kg H2O·(kg s.s.)ˉ¹

Fig. 7 Drying speed of apple pomace as a function of water content (du/ds = f(u); kg s−1 m−2), for temperature 94 °C

Drying Kinetics of Selected Waste Biomass from the Food Industry

45

0.5

90

0.45

80

0.4

70 du/dτ;kg·s¯¹·m¯², (temp. 76°C)

0.3

60

t2; °C

50

0.25 40

t, °C

du/dτ;kg·s¯¹·m¯²

0.35

0.2 30

0.15

20

0.1

10

0.05 0

0 0.0

1.0

2.0

3.0

4.0

u, kgH2O·(kgs.s.)¯¹

0.50

50

0.45

45

0.40

40

0.35

du/dτ;kg·s¯¹·m¯²,(temp.46°C)

35

0.30

t1; °C

30

0.25

25

0.20

20

0.15

15

0.10

10

0.05

5

0.00

t, °C

du/dτ;kg·s¯¹·m¯²

Fig. 8 Drying speed of apple pomace as a function of water content (du/ds = f(u); kg s−1 m−2), for temperature 76 °C

0 0.0

1.0

2.0

3.0

4.0

u, kgH2O·(kgs.s.)¯¹ .

Fig. 9 Drying speed of apple pomace as a function of water content (du/ds = f(u); kg s−1 m−2), for temperature 46 °C

46

B. Brzychczyk et al. 120 4 100

3

80

2.5 60

2

t, °C

u*;kg·s¯¹·m¯²

3.5

1.5

40 u*;kg·s¯¹·m¯², (temp.46°C) u*;kg·s¯¹·m¯² (temp. 76°C) u*;kg·s¯¹·m¯² ,(temp. 94°C) t1, °C t2, °C t3, °C

1 0.5

20

0

0 0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

u; kg H2O·(kg s.s.)ˉ¹

Fig. 10 Changes in the drying rate (smoothed with the Brown model (u*)) (u* = f(u); kg s−1 m−2), for different temperatures

However, the time needed to dry a sample of apple pomace with a water content 0.1 kg H2O·(kgs.s.)−1, (u·(uo)−1 = 0.135) in temperature 46 °C it lifted up 1399 min (23 h and 31 min) Fig. 5. As the temperature rises, the drying time is shortened. The shortest drying time was recorded at 94 °C. Raising the temperature to 94 °C shortens the convection drying time of apple pomace four times. The lower the temperature of the drying agent, the drying time is increased by 75%. All trend curves with very good fit describe fourth degree polynomials. Table 3 presents regression models with matching factors. In order to compare the drying kinetics, for samples that could differ in the initial water content, a reduced water content was calculated. The results of calculations of the reduced water content as a function of time, for a given process temperature, are illustrated in Fig. 6. At the highest speed, the convection drying process was carried

Table 3 Regression models and values of determination coefficients Regression model y = 1e–17x – 1e–12x + 4e–08x – 0.0007x + 4.6384 y = 6e–18x4 – 6e–13x3 + 2e–08x2 – 0.0005x + 4.2265 y = 2e–19x4 – 6e–14x3 + 5e–09x2 – 0.0002x + 4.361 4

3

2

R2

t, °C

0.9988 0.9992 0.9997

94 °C 76 °C 46 °C

Drying Kinetics of Selected Waste Biomass from the Food Industry

47

out at 94 °C. For example, during convection drying, the reduced water content (point U = 0.45) for the temperature of 94 °C was reached during s = 1 h and 15 min, while for the temperature of 76 °C the time extended to s = 1 h and 48 min the drying process at 46 °C was s = 3 h and 54 min. The diagrams in Figs. 7, 8 and 9 present changes in drying speed depending on water content and process temperature. Analyzing the course of the curves of the kinetic drying rate, it can be concluded that the intensity of the water loss is the highest at the highest temperature of the process. Differences in drying rates for individual temperatures are reduced with the loss of water in the material. For temperatures 46 and 94 °C and content 3.07 kg H2O·(kgs.s.)−1 the difference in the drying rate was 0.16427 kg s−1 m−2, a at content 1.01 kg H2O·(kgs.s.)−1 the difference in drying speed was 0.05773 kg s−1 m−2 (Figs. 7 and 9) Comparing the drying rates between processes carried out at temperatures 76 °C i 94 °C, for water content 3.07 kg H2O (kgs.s.)−1 and 1.01 kg H2O·(kgs.s.)−1 differences in drying speed were respectively 0.09231 kg s−1 m−2 and 0.03904 kg s−1 m−2. However, the difference in drying rates of apple pomace at 46 and 76 °C at the water content 3.07 kg H2O·(kgs.s.)−1 was 0.07197 kg s−1 m−2, while at content 1.01 kg H2O·(kgs.s.)−1 the difference was 0.01867 kg s−1 m−2 (Figs. 8 and 9). Changes in the drying rate (smoothed with the Brown model (u*)) depending on the water content, taking into account the process temperature, are shown in Fig. 10. The course of the drying speed curves shows that as the process temperature increases, the apple cake is dried at a higher speed. The drying air temperature affects the drying kinetics of apple pomace. Increasing the temperature shortens the drying time of apple pomace in this drying method. With the loss of water content, the drying speed at the final stage of the process reaches an approximate value. After 2 h and 55 min the drying rate for processes carried out at three different temperatures takes the approximate value 0.05 kg s−1 m−2.

4 Conclusions Convection drying can be a quick and easy method of on-site waste preservation for the purpose of further storage and preservation of the raw material for further processing. By applying the optimization of the convection drying process, including the use of drying in periodically variable conditions and the use of waste energy from other processes, the outdated method of drying can be successfully used. Experiments have shown that when drying apple pomace, the temperature increase from 46 °C to 94 °C drying significantly reduces the drying process by four times. Convection drying at a temperature close to 100 °C shortens the drying process by 75% compared to the process carried out at a temperature close to 50 °C. The drying process is fastest for the highest temperature. After about 3 h of the process, the drying speed is the same as the temperature of the process.

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Acknowledgments This Research was financed by the Ministry of Science and Higher Education of the Republic of Poland (statutory activities DS 3600/WIPiE/2018), Faculty of Production and Power Engineering, university of Agriculture in Krakow.

References 1. B. Borycka, Utylizacja wybranych produktów odpadowych przemysłu owocowo-warzywnego. Przem. Ferm. Owoc. Warz. 11, 38–40 (1999) 2. J. Kumider, Utylizacja odpadów przemysłu rolno-spożywczego. Wyd. AE. Poznań (1996), pp. 60–70 3. I. Zlatanović, M. Komatina, D. Antonijević, Low-temperature convective drying of Apple Cuber. Appl. Thermal Eng. 53(1), 114–123 (2013) 4. T. Kudra, C. Strumiłło (eds.), Thermal Processing of Biomaterials (Gordon and Breach Science Publishers, New York, 1998) 5. D. Veli, M. Planini, S. Tomas, M. Bili, Influence of air velocity on kinetics of convection Apple dryling. J. Food Eng. 64(1), 97–102 (2004) 6. A. Kaya, O. Aydin, C. Demirtas, Drying kinetics of reg delicious apple. Biosyst. Eng. 96(4), 517–524 (2007) 7. C. Strumiłło, Dry. Technol. 24(9), 1059 (2006) 8. V.T. Karathanos, S. Anglea, M. Karel, Collapse of structure during drying of celery. Dry. Technol. 11, 1005–1023 (1993) 9. A. Pikoń, Aparatura chemiczna, Warszawa (1983), p. 529 10. M. Rasouli, S. Seiiedlou, H.R. Ghasemzadeh, H. Nalbandi, Convective drying of garlic (Allium sativum L.): Part I: Dying kinetics, mathematical modeling and change color. Aust. J. Crop Sci. 5(13), 1707–1714 (2011) 11. PN-EN ISO 18134-3:2015-11 - Solid biofuels – Determination of moisture content – Oven dry method – Part 3: Moisture in general analysis simple 12. PN-EN ISO 18125:2017-07 - Solid biofuels – Determination of calorific value 13. PN-EN 18123:2016-01 - Solid biofuels – Determination of the content of volatile matter 14. PN-EN ISO 18122:2016-01 - Solid biofuels – Determination of ash kontent 15. Cz. Strumiłło, Podstawy teorii i techniki suszenia, WNT Warszawa (1983) 16. A. Andres, C. Bilbao, P. Fito, Drying kinetics of Apple cylinder under combined hot air-microwave dehydration. J. Food Eng. 63(1), 71–78 (2004)

Process of Gradual Dysfunction of a Diesel Engine Caused by Formation of PM Deposits of FAME Origin Bogusław Cieślikowski

Abstract Fuel combustion optimisation in compression-ignition engines with multi-stage HPCRS injection is the main direction of research in the area of the thermodynamic stability of fuels with FAME addition, also including the formation of PM. This paper presents stages of multi-aspect diagnostic inference in relation to the causes of failures of an engine’s functional systems as a result of PM deposits. The engine operating parameters were evaluated using a dedicated tester, showing the significance of diagnostic procedures during the vehicle servicing periods, which prevent the occurrence of emergency states signalled by the MIL warning lamp. The diagnostic procedure showed a gradual injector dysfunction which contributed to PM formation, necessitating an earlier service intervention. XRF spectrum analysis in relation to the determination of elements forming the PM along with IR spectroscopy showed the presence of organic FAME compounds in the PM deposit. Keywords Engine


FAME
Fuel injection
Spectral analysis

1 Introduction The chemical formulation of engine fuels is continuously evolving due to requirements relating to improved combustion processes, cleanliness of engine components, and environmental protection, contributing to the development of engine design [1]. Fuel combustion optimisation in compression ignition engines with multi-stage injection of hydrocarbon fuels and fuels with addition of biocomponents is the main direction of research in the area of the thermodynamic stability of fuels and development of engines equipped with HPCRS (High Pressure Common Rail B. Cieślikowski (&) Faculty of Production and Power Engineering, Department of Mechanical Engineering and Agrophysics, Agricultural University of Cracow, ul. Balicka 116B, 30-149 Kraków, Poland e-mail: [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_5

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System). Oxidation resistance is one of the most important properties of fuels containing FAME (Fatty Acid Methyl Esters) due to their low stability, which causes the formation of products that hamper the correct operation of the engine [2]. The fuels for compression-ignition engines equipped with HPCRS and catalytic multifunctional aftertreatment systems, DPF (Diesel Particulate Filter), and SCR (Selective Catalytic Reduction) must have adequate physical, chemical and functional properties [3]. The evolution of fuel quality, including biocomponents, requires specialist studies to identify their quality and functional problems and to indicate possible solutions. The propensity for formation of PM (Particulate Matter) deposits is one of the important problems closely related to the structural and group composition of fuels used in compression-ignition engines [4]. Some fuel properties, such as high viscosity, low volatility, content of olefins, aromatic compounds and biocomponents (FAME), facilitate formation of carbon deposits in the area of injector holes, the combustion chamber, turbocharger and the DPF. A gradual growth of PM layers leads to the loss of correct fuel atomization, immobilization of the VTG (Variable Turbine Geometry) guide apparatus, blocking of the EGR (Exhaust Gas Recirculation) valve, and obstructed flow in the DPF channels. The result is engine failure states, lighting up of the MIL warning lamp, and activation of the substitute engine operational performance [5, 6]. The complex characteristics of diagnostic tests require a multi-aspect diagnostic inference process, and analysis of the records of engine working parameters within servicing cycles which will significantly extend the engine life.

2 Causes of IDID (Internal Diesel Injector Deposits) Formation The hazards for the HPCR system relating to IDID formation result from limitation of the dynamics of internal injector components or their total immobilization, causing the hydraulic dysfunction of such components. This process can also be noticed in a VTG (Variable Turbine Geometry) turbocharger and the components guiding the exhaust as in the EGR [7]. FAME additives in the diesel fuel favour IDID formation due to acidic pollutants generated during FAME production and formed by auto-catalytic separation of fatty acid esters with participation of metal ions [8]. The deposits thus formed can also intensify the corrosion processes [9]. The periodic service maintenance of the vehicle, as a preventive measure, requires an analysis of fault codes stored in the controller memory with the use of a dedicated tester, and the evaluation of “freeze frame” and dynamic characteristics of the injector supply system against the record of fuel pressure in the container. PIBSI (Polyisobutylene bis Succinic Anhydride) with high contents of amine in interaction with fatty acids carboxylic dimers is particularly prone to deposit formation. Such deposits are not soluble in generally used organic solvents, which

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hampers their analysis and the determination of their chemical structure. Studies to date indicate that IDID can be formed from fuel oxidation products. Such products can appear particularly in the case of unstable diesel fuels containing FAME additives or can be a result of the ageing of fatty acid esters present in lubricating additives [8, 9]. Multifunctional detergent-dispersant additive packages for diesel fuel require testing for compatibility and laboratory stability because they comprise many various ingredients that can interact, and can exhibit incompatibility that manifests itself by turbidity, separation and deposit formation [1]. The multifunctional detergent-dispersant additive comprises a lubricating additive, a corrosion inhibitor, demulsifier, antifoaming agent, additive increasing the cetane number, oxidation inhibitor, depressant, and biocide [10]. The multifunctional detergent-dispersant additive package for advanced diesel fuels must protect the HPCRS from the IDID, nozzle coking, wear and seizure of the high-pressure fuel pump, and fuel system corrosion. It is necessary to counteract the fuel oxidation processes, with the ability to form a protective layer preventing the sedimentation of highly-adhesive deposits and films [7]. In addition to procedure CEC F-23-01, the Worldwide Fuel Charter (WWFC 2013) introduced the procedure CEC F-98-08 for cleanliness assessment of pintle injectors and high-pressure multi-hole injectors (for category 4 and 5 diesel fuels). According to WWFC 2013, for category 4 and 5 diesel fuels the maximum acceptable power loss is 2% during tests according to CEC F-98-08 [11].

3 Assessment of Technical Conditions of Common Rail Fuel Injection System in Compression-Ignition Engine In the tested M9R engine, the EDC Bosch system controls the time and opening phases of the HPCRS, supervises the operation of the VTG turbocharger, and controls the DPF auxiliary systems. The test drive indicated the loss of dynamics accompanied by increased fuel consumption, despite the absence of MIL warning lamp signalling. The absence of signalling for a developing failure state can also be attributed to the specific features of controller software in the EDC 16/CP33 engine [12]. The software differences correspond not only to the injection map structure (Duration), SVBL (Single Value Boost Limiter) turbocharger control map, but also relate to the autodiagnostics and the error threshold value. The determination of the causes of such a condition requires engine diagnostics with the use of a CLIP probe equipped with an interface dedicated to vehicles of that make (see Fig. 1) [13]. After connecting the kit to the OBD II 16-pin connector, the vehicle identification commences based on the VIN, followed by general CAN diagnostics via communication with all network controllers, which is a routine procedure. Skipping this procedure may lead to erroneous diagnostics results if detected defects in the multiplex network have not been previously eliminated. The vehicle CAN diagnostics usually requires additional interventions to eliminate defects that were

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Fig. 1 CLIP probe with interface

detected and written in the numerical form on reference lines between the vehicle, multimedia and peripheral systems (see Fig. 2). The lists of error codes was reviewed after a successful CAN diagnostics and after selecting the “Fuel System” tab for communication with the EDC 16 engine controller. The absence of MIL lamp signalling was confirmed, as there were no error codes saved by the controller. The error code for “air supply circuit” was saved only after a long-term, full engine load on the test drive section. The “freeze frame” parameters were read for analysis of the engine operating parameters at the moment when the controller detected the error (see Fig. 3).

Fig. 2 Vehicle multiplex network test

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Fig. 3 “Freeze frame” at error occurrence

A difference was found between the desired values of turbocharging pressure and the actual value generated by the MAP pressure sensor located in the intake system downstream of the turbocharger. There was a large discrepancy between these values, and the difference grew as the engine load increased. This condition can also be attributed to excessive resistance of exhaust gas flow through the DPF. An auxiliary control parameter is also voltage at the air mass flowmeter signal output. The voltage in this case was too low (3.56 V vs the roughly 5 V required at the indicated rotational speed). A possible cause of this condition may also be the incorrect positioning of the exhaust gas guide apparatus in the VTG turbocharger as a result of PM deposits. Such being the case, it is necessary to extend the diagnostic inference scope to include the correct fuel injection in the HPCRS, despite the absence of a relevant error. The representative system parameters were reviewed, mainly correctional doses of individual injectors to evaluate their correct operation. The read values (see Fig. 4) indicated a large variation of injector correctional doses, albeit within the permitted range, which justifies the absence of an additional error. Note also the large value of positive fuel dose correction for the 3rd cylinder. This fact is not irrelevant for the PM deposit formation in the VTG turbocharger and is one of the reasons for blocking of the mechanism positioning the exhaust gas guiding apparatus.

Fig. 4 Check of CR correctional doses

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The EDIA-5 analyser (see Fig. 5) was used to determine the defect causes in detail. The analyser allows the injectors’ voltage signals and the time analysis of amplitudes and high-pressure build-up to be recorded [14]. The recorded pressure vs time curves indicate the occurrence of high pressure for the 3rd cylinder injector over an extended time which suggests a possible nozzle coking, and the excess injected fuel contributes to increased smoke in the exhaust gas. Further widening of the diagnostic process includes an assessment of the DPF functional condition. The exhaust gas temperature upstream of the particulate filter was 159 °C, close to the condition for commencement of DPF regeneration. Erroneous operation of the exhaust gas temperature sensor would prevent the regeneration process, leading to an excessive differential pressure (permitted values are from 20 to 60 mbar) and recording of the DTC 203115 error code. Although the differential pressure was 30 mbar (see Fig. 6), there was a slight improvement of the filter differential pressure as a result of unremovable PM deposits. The filter regeneration occurred when the deposits amounted to 41 g (which is a permitted value according to the manufacturer), and the amount of deposits in the filter after the last regeneration was 35.4 g which indicates a low DPF regeneration effectiveness; if the vehicle is used over short distances, the DTC 203115 error will be recorded. The engine diagnostics stages indicate the need to widen the interpretation of the fuel system functional states and auxiliary systems using a dedicated version of the diagnostic kit. A replacement or repair of, e.g. the VTG turbocharger, would lead to a short-term improvement of the engine condition as incorrect fuel atomization at high positive fuel dose correction will directly contribute to repeated PM formation around the nozzle holes, and will also lead to deposit formation on the turbocharger guide apparatus and in the DPF channels.

Fig. 5 Injector coil current characteristics and pressure in the fuel rail

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Fig. 6 DPF pressure functional parameters

Hence, the emphasis should be placed on full imaging of working parameters of interdependent systems, and not on single symptoms or replacement of engine components according to the error codes. Diagnosticians should have the necessary knowledge allowing them to correctly analyse the engine damage, particularly in the case of a multi-symptom analysis of the engine’s functional condition. The last action is to delete the errors saved in the controller memory, which must be done after the repair or replacement of damaged components.

4 Spectral Analysis of Deposits Spectral analysis was performed on the PM deposits taken from the HPCR fuel outlets and from the DPF channels [15]. Microscopic analysis of deposits (see Fig. 8) indicated the presence of deposit grains glued by a tarry substance. X-ray fluorescence spectra with XRF ED energy dispersion were recorded using an ED 2000 recorder from Oxford Instruments, and IR spectra (FTIR) were recorded on an FTS 175 from BIO-RAD. The deposit taken from the 3rd cylinder injector had a fine-grained and “dry” structure with a visible fraction of mineral material. A PM qualitative analysis was performed using the X-ray fluorescence (XRF) method, and samples were taken from the injector holes and the DPF channels after washing them with hexane (see Fig. 7). The qualitative analysis was based on changes of spectra intensity for identified elements. In the deposits studied, the presence of metals was mainly detected, such as iron, zinc, chromium, nickel and copper. In addition, the presence of calcium, phosphorus and sulphur was detected. The presence of calcium, phosphorus and sulphur results from the degradation of diesel fuel, including the additive package. Moreover, the depressants also contain iron ions [8]. The XRF spectrum from deposits taken from the VTG turbocharger guide apparatus indicated a high intensity of iron ions. These pollutants result mainly from corrosion of steel parts whose structure is more

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Fig. 7 XRF spectra for deposits taken from the injector holes and the DPF

susceptible to the corrosive action of FAME. A relatively high intensity of calcium and zinc spectra is visible, indicating pollution with diesel fuel, as is a significant share of the spectrum indicating the presence of nickel. After washing the deposits on the outer surface of analysed areas with chloroform, the samples were analysed in the IR spectrum. Fuel and engine oil residues, as well as products of their degradation, were found. The IR spectrum for substances precipitated in the 3rd cylinder injector zone is leaner (Fig. 8). First, a comparative analysis was performed for spectra typical for hydrocarbons, i.e. the wave numbers: 2850–3000 cm−1, 1464 cm−1, 1377 cm−1, 722 cm−1 [10]. A raised background was noticed in both cases, indicating the presence of PM. In addition, vibration spectra are present typical for hydroxyl group bonds (about 3400 cm−1) which can come from absorbed water, but also can be a derivative of carboxylic acids and alcohols [4]. The 1655 cm−1 spectrum in the 2000–1600 cm−1 diagnostic area is also intensive, indicating the oxidation of organic compounds to carbonyl and carboxylic structures. The effect of the action of these compounds on nitrogen oxides is related to the presence of hydrated salts of carboxylic acids. These substances can also come from the oxidation and degradation processes of alkaline additives present in diesel fuel. The 1630 cm−1 spectrum comes from other compounds containing C-O-NO2 bonds, formed as a result of nitro-oxidation of fuel and engine oil ingredients in contact with nitrogen oxides. An intensive 1747 cm−1 spectrum is observed, related to the presence of esters for which relations of C = O carbonyl groups (aliphatic) with the 1750–1735 cm−1 spectrum are representative [5].

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,7 1,6 1,5 1,4 1,3

Absorbance

1,2 1,1 1,0 0,9 0,8 0,7 0,6 0,5 0,4 0,3 0,2

3500

3000

2500

2000

1500

1000

Wavenumbers (cm-1)

Fig. 8 IR spectrum of soluble part of the deposit from injector holes (green) and levers positioning the exhaust gas guide apparatus

5 Conclusions The presented test and diagnostic inference stages during the vehicle servicing procedure will allow prevention of multi-symptom engine failures signalled by the MIL warning lamp. 1. The PM deposits lead to incorrect fuel atomization and dosing in the HPCRS, which is a cause of VGT and DPF damage, and which, in the case of absence of service interventions, results in error codes in the OBD II system. 2. In the diagnostic test procedures with the use of a dedicated tester, the emphasis should be placed on full imaging of working parameters of interdependent systems, and not on single symptoms of reduced functionality of the systems or replacement of engine components according to the error codes. 3. The analyses of X-ray fluorescence spectra with energy dispersion in relation to determination of elements forming the deposit along with IR spectroscopy indicated the presence in the PM of organic compounds of FAME origin.

References 1. R. Caprotti, A. Breakspear, et al., Detergency Requirements of Future Diesel Injection System, SAE Paper 2005-01-3901 (2005) 2. W. Stanik, J. Jakobiec, M. Wądrzyk, Wpływ stabilności termooksydacyjnej biokomponentów na pracę układu wysokociśnieniowego wtrysku paliwa typu Common Rail. Logistyka Nr5 (2015), pp. 569–576

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3. L. Chapman, Diesel soap–formation and related problems, in National Tanks Conference. Boston, 21 September 2010 4. R. Quigley, R. Barbour, E, Fahey, D. Arters, W. Wetzel, J. Ray, A study of the internal diesel injector deposit phenomenon. TAE, Fuels 7th Annual Colloquium, January 2009 5. B. Cieślikowski, Spectral analysis of deposits from a catalytic converter of Diesel engine. Combust. Engines 3(146), 1–6 (2011) 6. H. Gunter, Układy wtryskowe Common Rail w praktyce warsztatowej: budowa, sprawdzanie, diagnostyka (Warszawa. Wyd, Komunikacji i Łączności, 2010) 7. W. Stanik, J. Jakóbiec, M. Wądrzyk, Design factors effecting the formation of the air-fuel mixture and the process of combustion in compression ignition engines. Combustion Engines; nr 3dod. CD s (2013), pp. 40–50. ISSN 0138-0346-2013 8. F. Novel-Cattin, F. Rincon, O. Trohel, Evaluation method for diesel particulate trap regeneration additives: application to fire additives. SAE Paper 2000-01-1914. https://doi.org/ 10.4271/2000-01-1914 9. S. Pehan, M. Jerman et al., Biodiesel influence tribology characteristics of a diesel engine. Fuel 88(6), 961–1152 (2009) 10. W. Stanik, Badania poliizobutylenobursztynoimidów w zakresie oceny użytkowej dodatków detergentowo – dyspergujących do paliw silnikowych. Doctoral dissertation, AGH (2015) 11. CEC/TC 19 WG24: Report of the Ad-hoc Injector Sticking Task Force – 02 August 2011 12. J. Merkisz, S. Mazurek, Pokładowe systemy diagnostyczne pojazdów. Wyd. Komunikacji i Łączności. Warszawa (2007), pp. 226–319. ISBN 978-83-206-1633-0 13. L. Preisner, Delta Tech Electronics EDIA/2014 14. Information materials: DeltaTech Electronics (2011) 15. J. Sadle, Spektroskopia molekularna (Wydawnictwa Naukowo Techniczne, Warszawa, 2002)

Selective Catalytic Dehydration of Bioethanol Vitaliy E. Diyuk , Vladyslav V. Lisnyak

and Ruslan Mariychuk

Abstract In this article, we report on the dehydration of bioethanol over solid acid catalysts―0.1 mmol g−1 of phosphotungstic acid loaded on activated carbon carriers obtained from waste biomass. An ethanol vapor showed a selective transformation, catalyzed by the phosphotungstic acid, into diethyl ether at between 120 and 150 °C. At the temperature range of 180–205 °C, the ethanol conversion reaches almost 99.7% with 100% selectivity towards ethylene. The adsorption and catalytic studies have shown that the oxygen-containing functional groups on carbon solids act as sites of the immobilization of phosphotungstic acid and of the ethanol adsorption contributing to alcohol dehydration.







Keywords Bioethanol Catalytic dehydration Bioresource technology Activated carbon from waste biomass Phosphotungstic acid







1 Introduction 1.1

Bioethanol Catalysis and Solid Acid Catalysts

Over the past decades, bioethanol consumption as fuel has steadily increased, and it amounted to about 100 million tons by 2015 [1]. An important role of bioethanol, an alternative to fossil energy resources, is due to the simplicity of its production. This operation does not require special equipment and uses different natural raw materials and bio-wastes that has not a harmfully effect on the environment [2, 3]. Significant volumes of production and a low cost of bioethanol allow us to consider it as valuable raw material for getting important chemicals. They include diethyl ether, ethylene, ethylene oxide, propylene, butadiene, acetaldehyde, and vinyl V. E. Diyuk
V. V. Lisnyak (&) Taras Shevchenko National University of Kyiv, Kiev 01601, Ukraine e-mail: [email protected]; [email protected] R. Mariychuk Prešov University in Prešov, 080 01 Prešov, Slovakia © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_6

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acetate [4, 5]. The bioethanol dehydration depends on the experimental conditions and the used catalyst. A catalyst directs the reaction in such a way that desired products of the vapor phase dehydration, e.g., diethyl ether and ethylene, are selectively formed: Cat; Dt

2 C2 H5 OH ! C2 H5 OC2 H5 þ H2 O Cat; Dt

C2 H5 OH ! C2 H4 þ H2 O

ð1Þ ð2Þ

At below 160–180 °C, the endothermic reaction over a catalyst gives diethyl ether. This reaction is thermodynamically advantageous at low temperatures. Within the operation window of a catalyst, increasing the reaction temperature above 180 °C increases the rate of catalytic dehydration and stimulates high levels of ethylene production. The most active catalysts of bioethanol dehydration are heteropolyacids [6, 7]. They differ from other catalysts [4] because of considerable acidity and reasonable thermal stability. However, the heteropolyacids have a low specific surface area which limiting the catalytic activity. To found application in heterogeneous catalysis, one can improve the heteropolyacids efficiency with the dispersion increasing. For such a purpose, carbon materials can be used as supports of heteropolyacids when preparing the dehydration catalysts. In this article, we reported on solid acid catalysts prepared by using activated carbon (AC) obtained from the waste biomass as a carrier matrix for phosphotungstic acid (PTA). This AC acts as an adsorbent and helps making the PTA highly dispersed. In addition, AC was oxidized to promote the dispersion of the acids species on the carrier and to prevent them from sintering. These catalysts and carriers were characterized by thermogravimetric analysis (TGA), thermal desorption and nitrogen adsorption methods. The activity of the catalysts in the bioethanol dehydration and their selectivity towards ethylene or diethyl ether were also tested in a heated micro-reactor. The goal of this study is to report the effect of carbon carrier surface on the dispersion of PTA and the catalytic performance for bioethanol dehydration. By combining the adsorption and catalytic studies, the possible reasons for the effect of surface oxidation on the catalytic activity and selectivity were given.

2 Experimental 2.1

Preparation

Apricot fruit pits, the waste from food-processing plants, were subjected to carbonization and steam activation [8]. The resulted AC was used as a carrier. To increase the content of the surface oxygen-containing groups those may act as adsorption centers for solid acids, AC was refluxed in a 15% solution of HNO3 for

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2 h. Then, the sample was washed with water and dried under a standard procedure. The oxidized sample was labeled as ACO. The catalysts were prepared by the incipient wetness impregnation. In a typical preparation, 1 g of the carbon carrier (AC or ACO) was impregnated with 0.1 mmol water solution of PTA (H3PW12O40  5H2O, Merck reagent) that acidified with adding HNO3 to prevent the decomposition of PTA [9]. The prepared catalysts were denoted as AC-PTA and ACO-PTA.

2.2

Characterization

Nitrogen adsorption-desorption isotherms of the carriers and the catalysts were measured at −196 °C by a Micromeritics ASAP 2020 static volumetric analyzer. The Brunauer-Emmett-Teller surface area (SBET) and pore volume (VS) were given by the analyzer workstation. Thermal behavior of both the carriers and respective catalysts was examined by thermodesorption method [8, 10]. The concentration of the oxygen-containing functional groups (CFG) was measured by the thermoprogrammed desorption with IR registration (TPD IR) of CO2 and CO gases. They are products of the thermal decomposition of the oxygen-containing groups in an argon medium [11]. For samples of AC-PTA and ACO-PTA, the thermal stability of the surface layer was determined by TGA in an argon flow at 1 atm. Thermogravimetric (TG) and derivative thermogravimetric (DTG) mass loss curves were recorded at a heating rate of 10 °C/min. Gas phase dehydration of bioethanol (DBE) over AC-PTA and ACO-PTA solid acid catalysts was studied in a flow catalytic reactor [12]. The saturated ethanol (EtOH) vapors collected above the liquid bioethanol and diluted with an inert gas-carrier were introduced into the reactor, at the total flow of 45 cm3 min−1. In the flow, the ethanol concentration was kept at 1.09  10−3 mol L−1. The catalyst volume packed into the flow reactor was 1 cm3. On the reactor outlet, the reaction mixture components and the yield of dehydration products were monitored with an IR spectrometer. For by-products check, volatile compounds were analyzed by gas chromatography (GC) on a Shimadzu GC 2010 instrument. The catalytic activity was referred to as bioethanol-to-diethyl ether (BETDE) and bioethanol-to-ethylene (BETE) conversion processes. The half-conversion temperatures of ethanol to diethyl ether (t50%(DE) and of ethanol to ethylene (t50%(E)) were chosen as measures of catalytic efficiency. For the BETE process, the catalysts were classified by the reaction temperature at 100% ethanol conversion to ethylene (t100%(E)). To determine the adsorptive behavior of the studied catalysts, we measured the peaked temperature at the ethanol desorption (tdes(EtOH)) by the TG method, at a heating rate of 5 °C/min.

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3 Results and Discussion At the first stage, TGA of unsupported PTA was performed. Heating of PTA causes a sharp weight loss effect (3.2 wt%) peaked at 165 °C on the DTG curve (Fig. 1). We attribute the weight loss to the dehydration of the acid crystal hydrate. In the narrow temperature window at below 220 °C, it loses 5 water molecules. Progressive thermal dehydration causes the forming of anhydrous acid. In the temperature range of 230–500 °C, there is no change in weight or the weight change is small. This observation confirms the high thermal stability of the anhydrous acid. Using AC and ACO carriers and the loading of PTA from the water solutions are the reasons for the significant decrease in the textural parameters SBET and VS. Table 1 sums all respective texture change regarding modifications. It shows the reduced SBET and VS values after AC oxidation into ACO. The microporous structure contracts due to the pore closing. If one accounts for a more uniform PTA supporting on the oxidized carbon surface, this reduction seems to be not crucial. From the CFG data obtained by TPD IR method, it is clear that ACO contains *5 times more functional groups than AC. They can act as adsorption centers of PTA during the preparation of the ACO-PTA catalyst. The TG and DTG curves for AC and AC-PTA are compared in Fig. 2.

Fig. 1 TG (1) and DTG (2) curves of PTA dried at 120 °C, heating in the argon flow

Table 1 Textural, adsorption and catalysis parameters Sample

SBET, m2 g−1

AC 1,350 ACO 890 AC-PTA 720 ACO-PTA 610 a Temperature at peak

VS, cm3 g−1

CFG, mmol g−1

tdes(EtOH), °C

0.46 0.41 0.35 0.32 maximum

0.82 111 3.84 117 0.85 95a 3.88 95a of the largest effect

t50%(DE), °C

t50%(E), °C

t100%(E), °C

133 139

179 172

204 194

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Fig. 2 a TG and b DTG curves: 1 – AC, 2 – AC-PTA, heating in the argon flow

Within the temperature range of 30–200 °C, the recorded TG curves show different trends. A significant amount (3 wt%) of the absorbed water can be removed from the surface of AC at 100 °C. In the case of AC-PTA, two effects of weight loss have peaked at 125 °C (1.3 wt%) and 175 °C (1.1 wt%). For the AC-PTA, water is desorbing at a higher temperature. This observation is associated with the possible formation of crystalline hydrate structures on the surface. In the temperature range of 200–600 °C, TG curves for both studied samples, for the carrier AC and the catalyst AC-PTA, run parallel, and respective DTG curves coincide well. Such a trend is explained by the similarity of processes on the surface of the carbon support and the catalyst based on it. Some decrease in the mass of the sample (2.7–2.8 wt%) is registered in this temperature range, and it is caused by the decomposition of the oxygen-containing functional groups [11, 13]. This thermal process passed beyond the temperature range of the decomposition of PTA or any other transformation of the PTA, see Fig. 1 for comparison. At temperatures between 200 and 600 °C, no redox reactions of PTA and the carbon matrix were registered. We suggested that the samples of AC-PTA and ACO-PTA are stable in this temperature range. At higher temperatures, there is the partial reduction of tungsten from PTA taking place for the expense of the surface carbon. Here below we will look at the reaction chemistry of DBE in the presence of AC-PTA and ACO-PTA catalysts. The reaction of DBE can run over the surface, however, the reaction rate depends on the temperature. The temperature regulates the parallel passing of both BETDE and BETE processes producing diethyl ether and ethylene. Within the studied temperature range, under optimized reaction conditions, we detected (by GC) only trace amounts of products of the ethanol oxidation, this reaction can pass on the surface of catalysts. For temperatures below 140–145 °C, only diethyl ether is present at the catalytic reactor outlet (Fig. 3). A comparison of the data presented in Fig. 3 (see curves 1 and 2) shows that the yield of diethyl ether reaches a maximum at 146 °C. At this temperature, the ethanol conversion over AC-PTA and ACO-PTA catalysts gives 53% and 65% yield of diethyl ether, correspondingly. With an increase in the temperature of dehydration to 160–170 °C, the diethyl ether yield is sharply reducing.

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Fig. 3 Ethanol conversion to diethyl ether (1, 2) and ethylene (3, 4) catalyzed by 1, 3 – AC-PTA and 2, 4 – ACO-PTA

On this background, one can see a significant increase in the yield of ethylene. Curves 3 and 4 in Fig. 3 demonstrate that one can reach about 100% yield of ethylene over AC-PTA and ACO-PTA catalysts at 204 °C and 194 °C. It is remarkable that this temperature is 10 °C lower for the ACO-PTA catalyst. Based on the obtained data, we may distinguish two temperature windows of the DE reaction over the AC-PTA and ACO-PTA catalysts. In the first temperature window, between 120 and 150 °C, the diethyl ether formed with high selectivity, the yield of up to 65%. In the second temperature window, between 180 and 205 °C, we registered a regime of catalyst work which characterized by the highest ethylene selectivity, up to 100%, and the overall conversion of ethanol into ethylene. Among the studied catalysts, the ACO-PTA catalyst based on the oxidized AC matrix shows the highest efficiency. For this catalyst, the yield of diethyl ether is greater, and t50%(DE), t50%(E) and t100%(E) values are smaller (see Table 1). The higher catalytic activity can be explained by the action of two influenced factors. The highest dispersion of PTA on the carrier surface and the greatest adsorption capacity of the oxidized surface to alcohol are the reasons for the better performance. From these observations, we supposed the formation of adsorption complexes of PTA-ethanol. In order to study the effect of the chemical nature of the surface layer on the adsorption properties, we investigated ethanol desorption from the surface of ACO and ACO-PTA. As seen in Fig. 4, the adsorbed ethanol can desorb between 40 and 220 °C. For ACO, TPD data showed a broad peak of the ethanol desorption centered at 117 °C. For AC, TPD curve of ethanol desorption is similar, tdes(EtOH) = 111 °C. Ethanol has a boiling point of 78 °C, and both aforementioned temperatures exceed that value. One can explain this fact by suggesting the formation of a fairly strong ethanol adsorption complex. This complex can involve the surface groups of the matrix within micropores. For AC-PTA and ACO-PTA catalysts, in comparison with carriers, three effects can be distinguished on the ethanol desorption curves: at 95, 145, and 185 °C. The main amount of ethanol presents on the carbon surface in a weak-adsorbed form, which desorption peak is

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Fig. 4 TPD data: the ethanol desorption: 1 – ACO, 2 – ACO-PTA

at 95 °C. This temperature for ACO-PTA catalyst is lower by 22 °C than tdes(EtOH) for ACO carrier (Table 1). The loaded PTA can block a part of oxygen-containing groups and limiting the adsorption of ethanol; also it fills a part of micropores preventing the access of ethanol. That is why one can explain the observed decrease in the temperature tdes(EtOH) by the action of PTA. The other two effects peaked at 145 and 185 °C are well consistent with the temperature windows of the formation of diethyl ether and ethylene at catalytic dehydration. Therefore, at above 120 °C, we registered tandem desorption of ethanol and ethanol dehydration products: diethyl ether, at the temperature range of 120–150 °C, and ethylene, at the temperature range of 160–210 °C. In sum, the thermodesorption peaks correspond to two types of active sites, the catalytic action of which give two different dehydration products. Factually, both effects are the largest for the ACO-PTA catalyst. From this observation, we associated the highest efficiency of this catalyst with the higher adsorption capacity of its surface layer.

4 Conclusions In the present work, we investigated the correlation between the properties of AC carrier prepared from agrowastes and the catalytic performance of the loaded PTA in the DBE reaction. TPD, TGA and BET measurements showed that the oxygen-containing groups increase the dispersion of PTA. In fact, the PTA impregnated AC can catalyze both BETDE and BETE reactions. The highest conversion of ethanol had observed between 110 and 200 °C. Within the temperature window of 120–150 °C, in the presence of AC-PTA and ACO-PTA catalysts, we showed selective production of diethyl ether from ethanol. Besides, ethylene can be formed with 100% selectivity in the temperature range of 180–205 °C. Our results obtained at the catalytic and adsorption studies clearly display the importance of the oxygen-containing surface groups. They act as sites of PTA

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immobilization, and also they are ethanol adsorption sites promoting its dehydration. We suggest that the use of such solid acid catalysts will help integrate bioethanol into chemical industry [4], and it could be a solution in producing a renewable bioethylene [14].

References 1. H.B. Aditiya, T.M.I. Mahlia, W.T. Chong, H. Nur, A.H. Sebayang, Second generation bioethanol production: a critical review. Renew. Sustain. Energy Rev. 66, 631–653 (2016) 2. P. Alvira, E. Tomas-Pejo, M. Ballesteros, M.J. Negro, Pretreatment technologies for an efficient bioethanol production process based on enzymatic hydrolysis: a review. Bioresour. Technol. 101(13), 4851–4861 (2010) 3. R. Singh, A. Shukla, S. Tiwari, M. Srivastava, A review on delignification of lignocellulosicbiomass for enhancement of ethanol production potential. Renew. Sustain. Energy Rev. 32, 713–728 (2014) 4. A. Mohsenzadeh, A. Zamani, M.J. Taherzadeh, Bioethylene production from ethanol: a review and techno-economical evaluation. ChemBioEng. Rev. 4(2), 75–91 (2017) 5. J.M.R. Gallo, J.M.C. Bueno, U. Schuchardt, Catalytic transformations of ethanol for biorefineries. J. Braz. Chem. Soc. 25(12), 2229–2243 (2014) 6. W. Alharbi, E. Brown, E.F. Kozhevnikova, I.V. Kozhevnikov, Dehydration of ethanol over heteropoly acid catalysts in the gas phase. J. Catal. 319, 174–181 (2014) 7. A.M. Alsalme, P.V. Wiper, Y.Z. Khimyak, E.F. Kozhevnikova, I.V. Kozhevnikov, Solid acid catalysts based on H3PW12O40 heteropoly acid: acid and catalytic properties at a gas-solid interface. J. Catal. 276, 181–189 (2010) 8. V.E. Diyuk, R.T. Mariychuk, V.V. Lisnyak, Barothermal preparation and characterization of micro-mesoporous activated carbons: textural studies, thermal destruction and evolved gas analysis with TG-TPD-IR technique. J. Thermal Anal. Calorim. 124(2), 1119–1130 (2016) 9. Z. Zhu, R. Tain, C. Rhodes, A study of the decomposition behaviour of 12-tungstophosphate heteropolyacid in solution. Can. J. Chem. 81(10), 1044–1050 (2003) 10. V.E. Diyuk, R.T. Mariychuk, V.V. Lisnyak, Functionalization of activated carbon surface with sulfonated styrene as a facile route for solid acid preparation. Mater. Chem. Phys. 184, 138–145 (2016) 11. W. Shen, Zh Li, Y. Liu, Surface chemical functional groups modification of porous carbon. Rec. Pat. Chem. Eng. 1(1), 27–40 (2008) 12. V.E. Diyuk, A.N. Zaderko, L.M. Grishchenko, A.V. Yatsymyrskiy, V.V. Lisnyak, Efficient carbon-based acid catalysts for the propan-2-ol dehydration. Catal. Commun. 27, 33–37 (2012) 13. G. Hotová, V. Slovák, O.S.G.P. Soares, J.L. Figueiredo, M.F.R. Pereira, Oxygen surface groups analysis of carbonaceous samples pyrolysed at low temperature. Carbon 134, 255–263 (2018) 14. D. Fan, D.-J. Dai, H.-S. Wu, Ethylene formation by catalytic dehydration of ethanol with industrial considerations. Materials 6, 101–115 (2013)

Technical Options of Pruned Biomass Harvesting in the Apple Orchards Applying Baling Technology and Its Conversion to Energy Arkadiusz Dyjakon

Abstract The reduction of fossil fuels usage and increase of local agricultural and forest residues for energy purposes belong to the main drivers to face with a climate change in a sustainable and environmentally friendly way. One of the alternative sources of wooden residues from agriculture is biomass generated during a regular fruit trees pruning. In Poland, there is a significant potential of pruned biomass from apple orchards that might be used to produce energy. In the paper the options of pruned biomass harvesting applying baling technology are presented. Next, the possibilities of the bales handling and their optional further treatment to produce energy are described. It was shown that depending on the local market requirements, the energetic use of pruning residues is feasible and may parallel lead to the CO2 emission reduction to the atmosphere. Keywords Pruning Energy


Apple orchard
Biomass harvesting
Baling technology


1 Introduction Biomass is a very important source of energy having a significant contribution to achieve the European target expected in the climate and energy package by 2020 [1]. To increase further their share on the energy market and strengthen the European strategy on bio-economy, it is necessary to use more and more of agriculture by-products [2]. In apple orchards there are many options to gain the biomass residues suitable for energy production (see Fig. 1). One of the interesting and valuable resources of waste biomass is pruning. Prunings are woody residues composed mainly by small branches and twigs produced during the regular management activity related to the care of agricultural crops such A. Dyjakon (&) Institute of Agricultural Engineering, Wroclaw University of Environmental and Life Sciences, ul. Chelmonskiego 37a, 51-630 Wroclaw, Poland e-mail: [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_7

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(a) branches after yearly pruning (b) trunk (orchards removal) (c) rooting (orchards removal)

Fig. 1 Biomass sources in the apple orchard

as orchards, vineyards or olive groves. One of the fruit orchards having potential to generate energy from wooden residues are apple orchards. To maintain high fruits quality and productivity, apple orchards require proper treatment, including branches pruning in the winter-spring period [3]. In case of significant deterioration of the apples production (after 20–30 years in average), the old trees are removed and to new one are planted. As a result, the pruning residues from apple orchards (see Fig. 2) are characterized by a regular yearly production of lower amounts of biomass per hectare (up to few Mg ha−1, in average 3.5 Mg ha−1) [4], and uprooting residues obtained at the end of the commercial life of the given plantation (even up to 100 Mg ha−1 or more). Both residues must be disposed of, but different possible strategies might be applied leading to different final results, profits or costs. Taking into account the size distribution area of the apple orchards in Europe, harvesting losses of branches and high heating value of wooden material the total energetic potentials from yearly pruning operations are: 29.11 PJ/year for theoretical, 22.50 PJ/year for technical and 18.63 PJ/year for economic. According to Poland, which possess the highest shares of the apple orchards in Europe, these values are 9.3 PJ/year, 7.4 PJ/year and 5.9 PJ/year, respectively [3]. In relation to the year by year trees pruning in the apple orchards, the following options might be recognized (see Fig. 3): – pruned biomass mulching on the inter-row area, – pruned biomass removal from the inter-row area and open-air combustion on site, – pruned biomass harvesting and use for other purposes (i.e. energy production). After pruning, ligneous residues are generally left spread all over the ground in the orchard. Processing in the orchard requires to carry out their elimination. If they are not removed, they become an obstacle for the other cultivation operations (a) mulching

(b) on-site combustion

(c) harvesting

Fig. 2 Options of pruned biomass treatment in the apple orchards

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Fig. 3 The use of pruned biomass for energetic purposes [11] PRUNING IN APPLE TREE

LOCAL HEAT PRODUCTION

HARVESTING

TRANSPORT TO FINAL USER

SHORT-TERM STORAGE

related to fruit (apples) production. In case of mulching and on-site burning, both options are costly and do not bring any financial benefits for a farmer. Leaving mulched residues in the soil contribute to enhance the organic matter content, but on the other hand it does not solve a problem with increasingly aggressive pests [5]. Removal of the pruned branches is usually carried out with tractors provided with rakes or similar devices for dragging (picking-up) the branches along the rows to dispose burn them on site (at the end of the orchards headland). However, open-air combustion is forbidden in most European countries due to the fire hazards. Therefore, the harvesting of the wooden residues in the apple orchard and their use for energetic purposes (PtE – Pruning to Energy) seems to be more efficient and reasonable. There are three general options the branches can be harvested: – manual collection, – mechanical collection combined with chipping, – mechanical collection combined with compaction (baling). Manual collection of cut branches is performed very rarely as it is time consuming. Moreover, the loose form and a very low bulk density of manually harvested biomass disqualifies its combustion in the boilers. Mechanical collection and chipping is an effective procedure [6, 7], but the harvested wet biomass residues requires later more strict storage conditions (i.e. forced drying, under a roof storage or periodic pile overturning) to prevent material properties deterioration or rotting. As a result, this technology is attractive and good in terms of chips combustion in the energetic units, but the harvesting process is more expensive and demands more direct energy input (i.e. fuel consumption) [8] than baling technology [9]. The alternative solution is mechanical collection combined with baling. The procedure is cheaper and requires less energy input in comparison to chipping [9, 10]. Additionally, the natural open air drying of bales, preventing material decomposition during storage, might be applied. However, some inconvenience is the necessity of having dedicated boilers for bales combustion to maintain the whole logistics chain simple in realization. The aim of the paper is (i) the review of the options of pruned biomass harvesting in the apple orchards applying baling technology and (ii) the review of the possibilities of pruned biomass bales conversion to energy.

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2 The Pruning to Energy Strategy The concept of pruned biomass baling system, which is focused on PtE strategy with ecological and economic footprint (see Fig. 4), is simple [11]. The idea is to harvest the pruning residues in the orchard in a single pass and with one operator

Fig. 4 Main technological options of pruned biomass baling in the apple orchard

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only. The baler picks up and compacts pruning residues into dense round bale. After the harvest the produced bales are collected and stored on site (or delivered to the plant). It is important that the pruning bales will not deteriorate during storage over a long period (unlike a pile of woodchips that are rotting), even though they are harvested in very wet conditions. During the next few weeks the natural drying process takes place without a risk of spontaneous combustion. It arises from the fact, that although the wet pruned residues are compacted, there is still enough space for the air flow between the branches under open-air storage. As a result, the moisture content in the raw material decreases from 45–55% to 15–20% increasing the lower heating value [12, 13]. Finally, the bales are ready to be transported to the final consumer. Having a suitable biomass boiler the bales might be directly combusted to produce heat and/or electricity. It should be marked that the shape and density of bales allow a better cost efficient transportation from the field to the power plant with conventional equipment (transportation platform, open trailer, etc.).

3 Pruning Harvesting Options Applying Baling Technology Many adopted and dedicated machineries have been developed to scrape, pick-up, harvest and convert the pruning residues into valuable product in the form of bales [14] that might be stored and used later by final consumer for heating. Therefore, many options are available on the market which the farmer can choose and apply in the apple orchard (see Fig. 5). Depending on the advancement of the technology the pruned biomass in the apple orchard might be harvested in one or two-stage processes. Currently, the most common approach is two-stage technology [14, 15]. Because of in the majority of the cases, after the pruning, the cut branches and shoots lie scattered around the apple trees, in the first stage, they must be gathered in the middle of the interrow. This operation might be done by the workers during the pruning of the trees. (a) in front of the tractor

(b) in rear of the tractor

(c) in front of the baler

Fig. 5 Options for windrowers attachment to improve pruned biomass harvesting process

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Fig. 6 Small baler for pruned biomass baling strategy (Source www.caebinternational.it): a small baler without additional equipment, b small baler with windrowers and temporary storage unit of bales, c small baler with temporary storage unit of bales

Although it requires more time, it increases harvesting efficiency (there are lower harvesting losses). However, to save time and facilitate the harvesting process, the device called a sweeper or windrower are in use [16]. Usually, they are attached to the tractor (in front or in rear) as well as to the baling machinery (see Fig. 6). As a result, the machine simultaneously removes the branches from both sides of the interrows and sweeps them to the middle part. In more developed models, thanks to the adjustable arms, it is possible to regulate the distance between the sweeping rotors and the range of the operation [16]. The windrowers are made of flexible and highly resistant plastic bars or rubber. The rotational speed of rotors may be smoothly adjusted with the use of hydraulic drives, depending on the needs and conditions. The examples of the selected machineries in operation are shown in Fig. 6. The second stage of this process is an appropriate baling of the pruned biomass arranged in the middle of the interrows. For this purpose the professional machineries for pressing the pruned biomass, called balers, are used [17, 18]. The pruned residues are collected from the interrows with the use of a pick-up system and then fed into the baling chamber, where the rubber belts, rolls, or a combination of rolls and chains, roll up the pruned residues into cylindrical-shaped bales. At the end of the process the bale is wrapped with a plastic or organic string (or net) to avoid bale destruction and maintain the proper shape during the storage or transportation period [16]. These machineries are mounted on the back of the tractor and they are supplied with power from PTO (Power Take-Off). In Figs. 7 and 8 some examples of the balers with optional equipment are shown. It should be added that on the market there is also available a pressing (baling) machinery producing the rectangular bales (Fig. 9), but it is not so popular, like a round baler. In case of compaction, there are two forms possible to be produced (see Fig. 10): – rectangular bales (very rarely), – round bales.

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(a) big baler with windrowers

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(b) big baler without additional equipment

Fig. 7 Big baler for pruned biomass baling strategy [19]

Fig. 8 Baler producing rectangular bales (Source www.lerdaagri.com)

(a) rectangular bale

(b) round bale

(d) temporary pruned bales storage

Fig. 9 Compacted pruned biomass bales in the apple orchards

The size of rectangular bales produced from pruned biomass in the orchards is 32  42 cm or 36  46 cm (www.lerdaagri.com), whereas diameter of the round bales might vary from 30–40 cm up to 120 cm. The length of the bales is ca. 60 cm (small bales) and ca. 100–120 cm (big bales), respectively [9, 20, 21]. It should be marked that in practice about the choice of the baling strategy and the size of the produced bales decide many parameters, like [22, 23]: orchards size and characteristics, economic pruning potential, local market requirements and demand for biomass, biomass price etc.

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Fig. 10 Pruned biomass conversion options to energy

4 Conversion Options of Pruned Biomass Bales to Energy The pruned bales from apple orchards are a good wooden material to be used for energetic purposes. It is characterized by heating value in the range of 17–19 MJ/kg [4, 24] which is similar to other wastes coming from agricultural and forestry sector [25]. The conversion of chemical energy contained in biomass bales into useful energy might be realized throughout their direct or indirect combustion in the boiler (see Fig. 11). In case of direct pruned bales burning to generate heat and/or electricity the dedicated boilers with an appropriate volume of the combustion chamber are required. The size of the boiler decides about the thermal capacity and the feeding frequency. As a consequence, the large bales are designed for institutional heating systems or commercial central heat and power plants (see Fig. 12), whereas the

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Fig. 11 Commercial heat and power plant for bales combustion (www.volund.dk)

Fig. 12 Small power boilers assigned to the combustion of pruned biomass in the form of: a bales (www.tilgner.pl), b briquettes (www.atmos.eu), c wood chips (www.valeenergy.co.uk), d pellets (www.ekogren.pl)

small bales are suggested for smaller and individual heating units assigned mainly to households (see Fig. 12a). If direct combustion of bales is not possible, the indirect method have to be applied. The bales are transformed to other form of solid fuel. Depending on the requirements, they might be converted to wood chips, pellets or briquettes. Then, the obtained solid biofuels are suitable for small scale (see Fig. 12b–d) as well as for

A. Dyjakon

Energy consumption, kWh/Mg

76 250 200 150 100 50 0 Chipping

Briquetting

Pelletisation

Fig. 13 Approximate energy demand for a process of pruned bales conversion [26–33]

commercial scale utilization. The main disadvantages of indirect direction of bales combustion are higher costs of the process caused by the additional energy input to comminute the bales and produce wood chips, pellets or briquettes. The approximated values of the energy demand required for chipping, pelletisation and briquetting processes are shown in Fig. 13. Besides the energetic benefits, there is also an environmental aspect that is of added value to this logistics chain. The usage of pruned biomass for energetic purposes contributes also to the reduction of CO2 emission. The CO2 emission index from bituminous coal combustion (as the typical conventional fuel) is 94.7 kg/GJ [34] or 357 kg/MWh [35]. Assuming the combustion efficiency in the heating boilers (0.92) and the lower heating value for pruned biomass 18.0 GJ/Mg), the avoided carbon dioxide emission amounts to more than 1500 kg per tonne of wooden by-product material.

5 Conclusions The removal of pruned biomass in the apple orchards is obligatory. Across the various options, the harvesting of the biomass applying baling technology seems to be the most effective, especially in terms of energetic input. Depending on the technical facilities and financial possibilities, the harvesting process might be realized using simple or sophisticated machinery. The bales collected in the apple orchard are after several-month storage period ready for combustion in the heating unit having also an positive environmental impact in reduction of carbon dioxide emission. However, it is conditioned by the possibility of whole bale combustion in the boiler. Otherwise, additional steps of biomass conversion will have to be applied to adopt the biomass form to other boiler requirements which results on significant energy input and make a whole logistic chain more complex.

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22. A. Dyjakon, Best practices on the sustainable use of prunings, Discussion panel: mobilising pruning residues to expand Europe’s biomass market - hosted by Czesław Adam Siekierski MEP (Member of European Parliament), Chair of the European Parliament’s Committee on Agriculture and Rural Development, European Parliament, 15 June 2016, Brussels, Belgium (2016) 23. D. Garcia-Galindo, M. Gomez-Palmero, S. Germer, L. Pari, V. Afano, A. Dyjakon, J. Sagarna, S. Rivera, C. Poutrin, Agricultural pruning as biomass resource: generation, potentials and current fates. An approach to its state in Europe, in 24th European Biomass Conference and Exhibition (EUBCE), 6–9 June 2016, Amsterdam, The Netherlands (2016) 24. G. Picchi, C. Lombardini, L. Pari, R. Spinelli, Physical and chemical characteristics of renewable fuel obtained from pruning residues. J. Cleaner Prod. 171, 457–463 (2018) 25. R. Garcia, C. Pizarro, A.G. Lavin, J.L. Bueno, Spanish biofuels heating value estimation. Part II: Proximate analysis data. Fuel 117, 1139–1147 (2014) 26. A. Gąsiorski, Z. Posyłek, T. Dróżdż, Nakłady energetyczne podczas mielenia biomasy przygotowywanej do procesu peletowania. Przegląd Elektrotechniczny 93(1), 229–232 (2017) 27. J. Frączek, K. Mudryk, M. Wróbel, Nakłady energetyczne w procesie brykietowania wierzby Salix Viminalis L. Inżynieria Rolnicza 3(121), 45–52 (2010) 28. J. Koppejan, S. Sokhansanj, S. Mellin, S. Mandrali, Status overview of torrefaction technologies, Technical Report, International Energy Agency (2012) 29. J.S. Tulumuru, Specific energy consumption and quality of wood pellets produced using high-moisture lodgepole pine grind in a flat die pellet mill. Chem. Eng. Res. Des. 110, 82–97 (2016) 30. A. Žandeckis, F. Romagnoli, A. Beloborodko, V. Kirsanovs, A. Menind, M. Hovi, D. Blumberga, Briquettes from mixtures of herbaceous biomass and wood: biofuel investigation and combustion tests, in Proceedings of the 8th Conference on Sustainable Development of Energy, Water and Environment Systems (2013) 31. D. Kuptz, H. Hartmann, Throughput rate and energy consumption during wood chip production in relation to raw material, chipper type and machine setting, in Proceedings of 22nd European Biomass Conference and Exhibition, 23–26 June 2014, Hamburg, Germany (2014) 32. J. Frączek, K. Mudryk, M. Wróbel, Nakłady energetyczne w procesie mielenia zrębków wierzby Salix Viminalis L. Inżynieria Rolnicza 4(122), 43–49 (2010) 33. M. Wróbel, K. Mudryk, A. Gąsiorski, Z. Posyłek, T. Dróżdż, Nakłady energetyczne procesu peletowania wybranych rodzajów biomasy. Przegląd Elektrotechniczny 93(1), 233–236 (2017) 34. A.-J. Perea-Moreno, M.-A. Perea-Moreno, M. Pilar-Dorado, F. Manzano-Agugliaro, Mango stone properties as biofuel and its potential for reducing CO2 emissions. J. Clean. Prod. 190, 53–62 (2018) 35. KOBiZE (The National Centre for Emissions Management), Calorific Values and CO2 Emission Factors in 2015 for Reporting within Emission Trading System (ETS) for 2018 (KOBiZE, Warsaw, Poland 2017)

Analysis of Physical Properties of Pellet Produced from Different Types of Dendromass Szymon Głowacki, Weronika Tulej, Mariusz Sojak, Andrzej Bryś, Ewa Golisz and Jakub Kaczmarczyk

Abstract The work assesses physical properties of pellets produced from wood of coniferous and deciduous trees of different varieties. Four assortments of pellet produced by three main pellet producers, i.e. Duraterm, Ecogold and Happypellet were used for this purpose. Results of research related to specific density, bulk density, calorific value, volatile matter content and ash content of the analysed materials were similar to those provided by producers. Keywords Pellet


Logging residue
Calorific value
Wood waste

1 Introduction Wood biomass obtained from forests, orchards or wood processing industry may be varied in form. Usually, it has a form of chips, green waste, shavings, branches, boughs or bales. These materials are used to produce, i.a. pellets, briquettes or ethyl alcohol (cellulose ethanol), which largely facilitates their transport, storage and dosing, in addition to improving their quality. Production of pellets consists of three stages: drying, grinding and pressing, which is necessary because they are formed from very fragmented biomass, in high-pressure conditions in a rotary pellet mill (press), with no addition of bonding agents. The final product are small cylindrical granules with the diameter ranging between 6 and 25 mm, and the length of a few centimetres. Pellet mill is used to minimize the volume of biomass, and consequently to obtain high density. Such a fuel as pellet is characterized by very low moisture—as low as 6%. Due to the fact

S. Głowacki (&)
W. Tulej
M. Sojak
A. Bryś
E. Golisz
J. Kaczmarczyk Warsaw University of Life Sciences, Nowoursynowska 166, 02-787 Warsaw, Poland e-mail: [email protected] W. Tulej e-mail: [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_8

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that pellet contains 100% of wood, it has very low ash content (0.5%) and harmful substances content [1]. However, it has high energy value. The above features make this fuel environment-friendly, in addition to being easy to transport, store, and distribute [2]. The granulate is extremely competitive to crude oil and coal in terms of economy and ecology [3–5]. A crucial aspect of pellet production is the fact that it may be produced from locally available raw materials, which allows for creating new workplaces. In the process of wood combustion, the amount of CO2 emitted is roughly equal to the amount required by the plants during photosynthesis [6, 7], thus it is possible to say that the process is practically CO2 free. Other advantages of pellet include high calorific value (2 kg of pellet is equivalent to 1 l of oil, and the calorific value of pellet is equivalent to approx. 70% of the calorific value of hard coal) and zero CO2 emission (the amount of CO2 produced during combustion is roughly equal to the amount required for photosynthesis), as well as low SO2 emission. Pellets are locally available, renewable resource of energy, which does not contain any additional harmful chemical substances (lacquers or adhesives). Moreover, pellets are easy to use and resistant to self-ignition, may be combusted in automatic boilers, are resistant to rotting (do not absorb atmospheric moisture), and have low content of ash, which may be used as plant fertilizer.

2 Goal and Scope of Work The goal of this work was to examine physical properties of selected types of wood pellets, with varied form and composition, produced by different manufacturers. The scope of work also comprised determination of the following: specific density, bulk density, calorific value and heat value, volatile matter content and ash content in the pellets. Based on the performed examinations and analyses, it was assessed, which of the examined wood biomass products is characterized by the best energy and ecology-related properties.

3 Methodology Measurements were performed in the drying laboratory at the Faculty of Production Engineering of the Warsaw University of Life Sciences in Warsaw. Calorific values of the samples were determined with the use of a bomb calorimeter. Ash content was determined by means of low burning method, performed according to the norm PN-EN 14775:2010 [8]. Volatile matter content was performed according to the norm PN-EN 15148:2010 [9].

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Four types of pellets, produced by three leading pellet producers, i.e. Duraterm, Ecogold and Happypelet, were examined. The material was dried in the tunnel dryer at the temperature of 60 °C to the moisture content of approx. 8%.

4 Material Pellets produced by Duraterm company were made from pine. Pine trees grow over large areas, therefore growing conditions and structure of wood vary considerably. Pine is a fast-growing tree, with the maximum height of 35 metres and a diameter of 95 cm. Branches usually start at 1/3 of height, and the lower part of the trunk is bare, i.e. without branches [10]. Pellets produced from pine wood were manufactured in the process of pressing with high pressure of compression. The waste material used included sawdust, chips and shavings. Ecogold company produces two types of pellets. The first type is produced from a mixture of oak (20%) and coniferous trees (80%) waste material. The manufacturer provides the information that the coniferous mixture mainly consists of Scots pine, and to a lesser extent of spruce. This type of pellet was produced from a by-product (sawdust and dust residue) from woodworking [11, 12]. Pellet from oak wood is the second type of product manufactured by Ecogold. It contains 100% of oak waste material. Oak grows up to 50 m, with the diameter of 1.5–2 m, and branches in the upper part of the tree (higher than 15 m above the ground) [13]. This type of pellet is produced from sawdust and dust residue from woodworking. It is worth noting that sawdust from sawmills was not used for production of this type of pellets as they would not comply with the quality norms for such pellets. Another product was pellet from coniferous wood, mostly pine sawdust. It has a small content of sawdust and chips of other kinds of wood, and does not contain any bonding agents (Table 1).

Table 1 Technical specification of the examined pellets

Calorific value Moisture Ash content Granulation

Pine pellet

Pellet from 20% oak and 80% coniferous trees

Pellet from oak wood

Pellet from pine sawdust

18 MJ/kg 7% 0.4% 6–10 mm

19 MJ/kg 8% 0.6% 6 mm

18.5 MJ/kg 8% 0.7% 6 mm

18 MJ/kg 6% 0.7% 6 mm

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5 Results of Research The research involved physical-chemical properties of the materials [14]. The analysis included the following parameters of the products: specific density, bulk density, calorific value, volatile matter content and ash content. Specific density, or specific mass is the proportion of the mass of a certain amount of substance (in this case pellet) to its volume [15]. This parameter was calculated with the following formula: q¼

m V

where: q – density; m – mass; V – volume. Pellets are produced using pellet mill, and are regular in diameter, but have irregular bases [16]. In order to perform the experiment, the material being examined had to be prepared properly. Fifteen straight, samples without cracks were selected, whose bases were then polished. The next step involved determination of mass of the samples, which was performed using laboratory scales, with the accuracy to the fourth floating point. The following formula for cylinder volume was used to calculate the volume: V ¼ PP  H ¼ pr 2  H where: V – volume; PP – base area; H – height; r – base radius. The exact height and base radius were measured with a slide caliper. The results of the calculations are presented in the table and on the graph below (Fig. 1). The presented results show that specific densities vary greatly depending on the type of pellet. Mixed pellet produced by Ecogold has the lowest density equal

density [kg/m3]

1300 1250 1200 1150

Duraterm pine Ecogold mixed

1100 1050 1000 950 900

Ecogold oak Happypellet coniferous

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Number of experiment Fig. 1 Specific density (Source Own compilation)

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148.743 kg/m3, while coniferous pellet by Happypellet has the highest density equal 1229.234 kg/m3. The difference between these two values is equal 17%. This results show the importance of numerous factors during production, including the degree of size-reduction prior to production, temperature, or pressing power applied in the process of pellet production from dendromass. Interestingly, the results show that chips (pellets produced by Happypellet are produced from material that mainly consists of chips) may be pressed much harder than dust, which contains a lot of air. Bulk density, like specific density, is defined as the ratio of the mass of the material to its volume, with one difference, i.e. bulk density is only calculated for solid materials because of the fact that the value of the volume is the total volume of the solid material and the spaces between its particles (in liquid and gaseous states, the spaces between particles do not exist or are underestimated). In other words, it is volume density or apparent density of piled material [17]. Methodology of this examination is quite straightforward. It is necessary to perform a number of measurements (which is time-consuming) in order to calculate the most accurate average from the obtained results. The vessel used for the experiment was filled with the material being examined, and the surface of the material was levelled. The vessel prepared in this way was then placed on the scales and the mass was weighted. The results of the examinations are presented in the table and on the graph below (Fig. 2). The results are analogical to those obtained for specific density. Out of the examined samples, pellet produced by Ecogold from mixed raw material has the lowest apparent density (774.2533 kg/m3), while pellet produced by Happypellet has the highest apparent density (952.0623 kg/m3). It may easily be observed, that the difference in bulk and specific density is considerable. The value of volume density is twice as low as that of specific mass. It is density that is important in

bulk density [kg/m3]

1000 950 900

Duraterm pine

850

Ecogold mixed

800

Ecogold oak Happypellet coniferous

750 700 0

5 Number of experiment

Fig. 2 Bulk density (Source Own compilation)

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transportation and storage of the material. This value largely depends on size-reduction of the material. Theoretically, the more size-reduced the material, the higher bulk density (less free space). However, as calculations related to specific density show, too high level of size-reduction results in smaller but more numerous air gaps. It is also directly connected with the gravity of a given material, which may significantly increase its volume density under the influence of its own mass or pressure force.

6 Calorific Value This experiment was performed in a bomb calorimeter, and consisted of two samples of the material, which allowed for obtaining values of heat of combustion of the fuels being examined. Based on the obtained results, and the following formula, calorific values for the examined samples were obtained: Qj ¼ Qs  24:42ð8:84H  W Þ where: Qj—calorific value; Qs—heat of combustion; H—hydrogen content; W— moisture content. The obtained values are presented in Table 2 below. The above results are very interesting, and generally correspond to the information provided by producers, i.e. there are no big discrepancies between the results obtained in the experiments and the data provided by producers. The highest calorific value (19207.12 J/g) was determined for coniferous pellet, mostly produced from pine wood waste, followed by pellet produced by Ecogold, containing mixed pellet compounds. Interestingly, the lowest calorific value (17888.12 J/g) was determined for pellet produced from oak by Ecogold.

Table 2 Results of research using calorimeter. (Source Own compilation) No.

Type of fuel

No. of sample

Heat of combustion (Qs)(J/g)

Mass of the sample (g)

Analytical hydrogen (Ha) (%)

Calorific value (Qj) (J/g)

Average calorific value (J/g)

1 2 3 4 5 6 7 8

Duraterm pine

1 2 1 2 1 2 1 2

19798 19269 20303 19356 18583 19393 20748 19866

1.0000 1.0000 1.0001 1.0000 1.0000 1.0000 1.0000 1.0000

6 6 6 6 6 6 6 6

18698.12 18169.12 19203.12 18256.12 17483.12 18293.12 19648.12 18766.12

18433.62

Ecogold mixed Ecogold oak Happypelet coniferous

18729.62 17888.12 19207.12

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It is worth paying attention to the obtained results. According to literature, calorific value for deciduous trees is higher than for coniferous trees, which is true [18]. Then, why such results of the analysis of the examined pellets? Calorific value is also expressed in other units of measurement, usually as the ratio of the amount of energy (J) to its volume (in this case m3). The results of the conducted experiments are expressed as the ratio of energy to the mass of the sample. Oak has high density, and for dry fuel wood, its specific density reaches 700 kg/m3, and pine wood has much lower density of 480 kg/m3.

7 Volatile Matter Content So called coke-oven trial was performed to obtain a percentage share of volatile matter. Volatile flammable material is a fraction of flammable material, which at the temperature of 850 °C and without the presence of oxygen escapes (undergoes thermolytic decomposition) in the form of organic gases (moisture excluded) and vapour. Volatile matter content in pellets is high, and its theoretical value, according to the literature amounts to 70–76%. High content of volatile matter in biomass is a problem as it considerably hinders controlling combustion process by changing conditions of ignition and combustion. In order to calculate and obtain the real percentage value of volatile matter, two separate trials were performed for each of the materials being examined. The results are presented in the Table 3 below. The research, in which size-reduced material was examined, confirmed the theoretical percentage share of volatile matter in wood biomass. All the examined materials had similar percentage values of approx. 76%, which classifies them as materials with high content of volatile matter [19]. High content was obtained due to considerable size-reduction of the samples, which facilitated the release of gases.

Table 3 Results of research related to volatile matter content Source Own compilation No of crucible

Material

Mass of charge prior to torrefaction (g)

Mass of charge following torrefaction (g)

Percentage share of volatile matter (%)

1 2 3 4 5 6 7 8

Duraterm pine

1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

0.236 0.231 0.235 0.237 0.229 0.235 0.237 0.248

76.4 76.1 76.5 73.3 77.1 76.5 76.3 75.2

Ecogold mixed Ecogold oak Happypelet coniferous

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Table 4 Ash content (Source Own compilation) No of crucible

Material

Mass of charge (g)

Ash mass (g)

Percentage share of ash (%)

1 2 3 4 5 6 7 8 9 10 11 12

Duraterm pine

1.380 0.990 1.120 0.890 1.198 1.112 1.142 1.713 1.547 1.095 1.103 1.417

0.012 0.008 0.010 0.010 0.012 0.011 0.014 0.018 0.016 0.010 0.010 0.013

0.869 0.808 0.893 0.890 1.001 0.989 1.051 1.051 1.034 0.913 0.907 0.917

Ecogold mixed

Ecogold oak

Happypelet coniferous

The last examinations of the biomass involved ash content analysis in each type of pellet. Ash is the solid, powdery residue left after the burning of an organic substance, such as solid fuels (e.g. hard coal), liquids (e.g. gas oil), or living organisms mass. It is a secondary product, obtained as a result of high temperature impact on mineral substances contained in the material. Ash contains most elements, which were present in the material prior to combustion, although after incineration, they may form other chemical compounds [20]. Reactions during combustion may result in volatile matter formation, which do not constitute ash. In order to perform proper analysis, the material used for the experiments was size-reduced. The results are presented in Table 4. The results of the above research are similar to those presented in the literature. Among the examined materials, pellet produced by Duraterm has the lowest ash content. The pellets were produced from pine, and their percentage ash content amounted to only 0.838% of the mass of the charge. The highest ash content was determined for pellets made from oak, which is a deciduous tree. The product manufactured by Ecogold company has approx. 1.051% ash content. It is also worth noting that all the examined samples had similar percentage of ash content of approx. 1%. Such ash content is described in most scientific publications, in which the estimated ash content in pellets amounts to approx. 1%. Such low ash content results in low dust emission (approx. 20 times lower than for coal) [21]. Additionally, wood ash may be used as a fertilizer, since it contains considerable amounts of nutritional components such as potassium, calcium, phosphor or magnesium, as well as microelements. Besides, it is completely free-of-charge as it is a by-product in the process of combustion. Due to considerable amount of potassium, wood ash is suitable fertilizer for most plants, including tomatoes, cucumbers, cabbage, and cauliflower. Plant ash may also be used as a fertilizer for annual flower plants. However, this fertilizer should not be used for plants requiring

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acid soil ph (most coniferous bushes and trees, erica, or e.g. highbush blueberry) as magnesium and calcium oxides result in soil alkalization, which is unfavourable to these plants. A very important fact is that ash does not contain nitrogen. Therefore, it is necessary to remember about additional nitrogen fertilization, if necessary [22].

8 Conclusions The following conclusions were formulated based on the performed experiments and related analyses: Pellet produced by Happypellet has the highest specific density, while pellet produced by Ecogold has the lowest specific density. The difference between these two densities is considerable, and amounts to approx. 17%. Pellet manufactured by Happypelet was produced from chips, which is less resistant to compression, compared to pellet produced from dust by Ecogold. The results of research show certain relation between bulk densities and specific densities. As with specific density, Happypelet product had the highest bulk density, and the product manufactured by Ecogold had the lowest density. In this case, the difference between these two bulk densities was nearly 22%, which has a significant impact on transportation or storage of this product. The product with similar calorific properties and higher concentration provides more energy from the same volume than the one with lower bulk density. Another interesting aspect was calorific value of the examined pellets. Pellet produced from oak (deciduous wood)—oak should have higher density, the results of the experiments indicated the opposite. Although deciduous wood has higher density than coniferous wood (i.e. oak log provides more energy than e.g. pine log), when the product is size-reduced, and the ratio of energy to mass (instead of energy to volume) is analysed, the obtained results will differ. The values will be closer to each other or higher for coniferous wood. Volatile matter content in all the examined samples was similar, and consistent with the data presented in the literature. The results of analysis of ash oscillated around 1%, which was also in accordance with the scientific literature. It is worth noting that wood ash has a beneficial effect on plants when used as a fertilizer, as opposed to coal ash.

References 1. H. Insam, B.A. Knapp, Recycling of Biomass Ashes (Springer, Berlin, 2011) 2. R.C. Brown, Thermochemical Processing of Biomass: Conversion into Fuels, Chemicals and Power (Wiley, Chichester, 2011) 3. K. Franciszek, Odnawialne źródła energii w świetle globalnego kryzysu energetycznego wybrane problemy (Difin, Warszawa, 2010)

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4. Zielona Księga a Europejska Polityka Energetyczna—Raport, Anna Konarzewska, Bezpieczeństwo Narodowe I/2006 5. D. Niedziółka, Zielona energia w Polsce (CeDeWu.pl, Warszawa, 2012) 6. P. Zbiorowa, Biomasa dla energetyki i ciepłownictwa—szanse i problemy (Wieś Jutra, Warszawa, 2007) 7. K. Krieger, Renewable energy: biofuels heat up. Nature 508, 448 (2014) 8. PN-EN 14775:2010, Biopaliwa stałe—Oznaczanie zawartości popiołu (2010) 9. PN-EN 15148:2010, Biopaliwa stałe—Oznaczanie zawartości części lotnych (2010) 10. G. Piotr, K. Adam, Biomasa leśna na cele energetyczne (IBL, Sękocin Stary, 2013), s. 59–76 11. M. Domański, L. Dzurenda, Drewno jako materiał energetyczny (SGGW, Warszawa, 2007) 12. National Research Council (U.S.), Panel on electricity from renewable resources, in Electricity from Renewable Resources: Status, Prospects, and Impediments (New York, 2010) 13. R. Kamil, Charakterystyka techniczna biomasy pochodzenia leśnego z wykorzystaniem modelu spadku wilgotności” (WZSCKR, Golądkowo, 2014) 14. H. Kopetz, Renewable resources: build a biomass energy market. Nature 497, 29 (2013) 15. G. Piotr, G. Anna, Biopaliwa (Wieś Jutra, Warszawa, 2002) 16. D. Ladislav, Wykorzystanie energetyczne dendromasy (SGGW, Warszawa, 2011) 17. K. Dariusz, K. Jacek, K. Marek, K. Paweł, Teoretyczne i eksperymentalne aspekty pirolizy drewna i odpadów (UWM, Olsztyn, 2014) 18. J.E. Trancik, Reneweble energy: back the renewables boom. Nature 507, 300 (2017) 19. H.-P. Ebert, Palenie drewnem we wszystkich rodzajach pieców (Studio Astropsychologii, Białystok, 2003) 20. S. Szczukowski, Wieloletnie rośliny energetyczne (Multico, Warszawa, 2012) 21. E. Klimiuk, M. Pawłowska, Biopaliwa - technologie dla zrównoważonego rozwoju (PWN, Warszawa, 2012) 22. G. Anna, Modelowanie energetycznego wykorzystania biomasy (ITP, Warszawa, 2010), s. 134–145

Ultrasonic Impact on the Drying Process of Wood Biomass Szymon Głowacki, Weronika Tulej, Mariusz Sojak, Andrzej Bryś, Małgorzata Jaros and Daniel Szulc

Abstract This work examines the impact of pre-treatment of wood biomass with ultrasounds with the frequencies of 21 and 40 kHz on the process of convective drying in a chamber dryer. Convective drying is a relatively cheap and widely used method, characterized by a free flow of heated air by the material being dried. The white willow (Salix alba L.) was used in the research due to its availability and the highest coefficient of use for energy-related purposes in Poland. The goal of the work was to assess the impact of ultrasound pre-treatment of wood biomass on the process of convective drying. Samples of the white willow (Salix alba L.) were pre-treated with ultrasounds with the frequencies of 21 or 40 kHz for the period of 10, 30 and 60 min. After ultrasound pre-treatment, the material was dried in the convective dryer using free convection method, at the drying temperature of 60 °C.




Keywords Wood biomass Renewable resources of energy Convective drying White willow





Ultrasounds


1 Introduction Nowadays, development of methods that allow for using renewable resources of energy is crucial to become independent of fossil fuels and decrease their negative influence on the environment. Imperfect laws and regulations related to certain renewable energy resources and growing shortage of conventional resources of energy may contribute to the necessity to return to the oldest known source of heat, i.e. biomass. Therefore, it is worth developing techniques allowing for the most efficient use of this resource [6]. Biomass use is beneficial in professional power industry due to its stable quality, low price, close location and high degree of concentration [9]. S. Głowacki (&)
W. Tulej
M. Sojak
A. Bryś
M. Jaros
D. Szulc Department of Fundamental Engineering, Warsaw University of Life Sciences (SGGW), Warsaw, Poland e-mail: [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_9

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Drying is one of the most important and time-consuming stages of wood treatment, which requires 40–70% of the total energy used in the process of wood processing. It is a crucial stage as it increases the heat value of the product and improves the boiler operation parameters, which, in turn, increases the efficiency of the process and decreases the emission of pollution to the air. Drying may be divided into natural (using solar energy) and artificial (in various types of dryers), and it involves evaporation of water from wood biomass to a certain limit, which evaporation occurs in certain conditions, appropriate for a given process. Advantages and disadvantages of different drying methods are assessed based on the following parameters: dried product quality, selection of the drying agent, as well as time and temperature of drying. In order to eliminate faults and shorten the duration of the drying process, various methods of wood pre-treatment, which have impact on its structure, e.g. size reduction, are applied [7]. Numerous countries have started a program of research on “energy forests”, the goal of which is testing the viability of energy willow plantations as an alternative to coal and oil. Plantations of energy plants are renewable as they depend on solar energy, soil, water availability and climate for their growth. Willow is not only a high-yield material but it is also more resistant than coniferous trees. It has potential to limit the dependence on fossil fuels, as well as reduce the unemployment, support other branches of industry, in addition to having a positive influence on the environment [1]. Wood (forest) biomass consists of plant organisms susceptible to biodegradation. They can be divided into two categories having the low (wood logs) and high (wood industry post-production waste material) percentage of use for energy purposes. It is directly connected with the properties of biomass, which specify its energy efficiency, the most important of them being [12]: moisture, bulk density, susceptibility to microbiological degradation, susceptibility to contamination, origin and composition of biomass. Forests cover approx. 30% of the area of Poland (9.1 mln hectares), which is one of the highest in Europe. The area covered by forests is growing steadily, with state-owned forests covering the largest area (approx. 7.6 mln ha). Wood produced in Poland may be derived from forestry as well as orcharding and horticulture [13]. Energy trees and plants must meet certain requirements as they are cultivated with the aim of obtaining the highest energy yield at the lowest expenditure. Their cultivation should be uncomplicated and inexpensive, with low soil and atmospheric requirements and high yield. Therefore, only certain kinds of trees are suitable for energy plantations, one of them being energy willow, one of the most popular energy trees grown in Poland [8]. Biomass used in production is usually divided into pieces. Unfortunately, the obtained fraction often has high moisture content, and, consequently, requires substantial drying prior to further processing [3]. Drying is one of the oldest processes developed by man, and, simultaneously, one of the basic methods of pre-treatment. It involves evaporation of water from the material or product being dried, using various drying agents. Solar energy and wind are classified as natural

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drying agents, while drying of material conducted in man-constructed dryers (in closed conditions) is considered artificial drying [4]. The negative impact of size-reduction of biomass may be eliminated by its drying. The process is conducted in special dryers [2], and requires additional financial outlay but the dried biomass becomes a product characterized by very good energy properties and higher heat value. Due to decrease in moisture content, microbiological processes cease, biomass weight decreases, and it stops losing its weight. All the above factors contribute to longer storage time of biomass, facilitate its transport and decrease the cost of these operations. Additionally, dried wood burns better in boilers, at the same time improving the parameters of their work [5]. Although, the exact date of discovery and the first application of ultrasounds by man is difficult to determine, ultrasounds have over a hundred-year history. From the scientific point of view, ultrasounds are defined as sounds above the upper audible limit of human hearing. Depending on the source, this limit is the frequency of 16 kHz or 20 kHz. Ultrasounds cannot be heard by men. Therefore, special devices are required to register sounds with so high frequencies. Ultrasounds can be used by animals using echolocation to communicate and to detect obstacles, such as dolphins or bats. The upper limit of ultrasounds is limited by the technical possibility to generate them—1 GHz, above which hypersounds start. Ultrasounds may be generated and processed in a variety of methods. Devices generating ultrasounds using selected amount of initial energy are called ultrasound converters, while devices processing ultrasounds into other forms of energy are called ultrasound receivers. Methods of ultrasounds generation are divided into reversible, i.e. related to the devices or systems that operate both as a converter and a receiver, and irreversible, i.e. devices or systems for generation of ultrasounds, which are either converters or receivers. Ultrasounds are used in numerous fields. Continuous research on ultrasounds has been carried out since their discovery, and new applications of ultrasounds are invented. According to their impact on the material or the environment in which they propagate, ultrasounds may be classified into passive and active [14, 15]. Favourable influence of pre-treatment of various food products with ultrasounds on drying time is well known, and widely used in food processing industry [10], although the mechanism of this phenomenon has not been fully explored yet. Nevertheless, ultrasounds are successfully used to remove moisture as pre-treatment with ultrasounds shortens the first and the second phase of the process. In some cases (e.g. yeast, mushroom, cauliflower) the drying process takes a few times shorter than normally, after pre-treatment of the above products with ultrasounds [16] (Table 1). Wood structure differs from the structure of food products, whose drying time may be shortened using ultrasounds. Despite this, there are numerous methods of pre-treatment, which have smaller or greater impact on its structure. Application of ultrasound waves with different frequencies may result in a series of alternative compressions and decompressions in wood. The mechanism can be compared to a sponge, which immediately returns to its original state, after it is compressed. Moreover, ultrasound waves cause cavitation in wood, which may induce pressure

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Table 1 Division of applications of ultrasounds Active applications of ultrasounds • drying of substances and materials, and in the process of extraction • in the process of coagulation—e.g. for sewage treatment • sonoluminescence— ultrasound-induced glowing of liquids • ultrasound therapy in medicine • washing and cleaning of items and articles using ultrasounds • triggering chemical reactions • welding, soldering—e.g. aluminum Source [15]

Passive applications of ultrasounds • ultrasound defectoscopy—non-destructive testing of materials • spectroscopy—formation and interpretation of spectra • hydrolocation—detection and determination of the position of objects under water using ultrasound waves • medical ultrasound (diagnostic sonography)

in its internal structure, due to violent changes in water particles. Mechanical and physical effects of ultrasounds include the induction and speeding up numerous processes related to diffusion of water, and lead to formation of microscopic tiny canals in wood structure. These changes may reduce the boundary layer of diffusion and increase convective mass transfer [17]. So far, the impact of pre-treatment of Cunninghamia (China fir) with ultrasounds on the duration of drying process has been examined. The examinations showed that ultrasound waves shortened the vacuum drying of this kind of wood in the temperature of 80 °C, and at the absolute pressure of 0.05 MPa. Moreover, the drying time decreased as the pre-treatment time increased. It is, therefore, worth studying the effect of pre-treatment with ultrasound waves on other drying methods, as they may facilitate removal of strongly-bound moisture from wood [11].

2 Goal and Scope of Work The goal of work was to assess the impact of the initial pre-treatment of wood biomass with ultrasounds on the process of the convective drying. The scope of work included the following: characterization of the wood biomass used in the experiments as well as the drying process and the effect of ultrasounds, collection and preparation of samples of the white willow (Salix alba L.), exposure of the samples of wood biomass to ultrasounds with various frequencies for different periods of time, convective drying of the pre-treated wood biomass, and the analysis of water content in the samples examined during the drying process.

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3 Research Methodology Samples of white willow (Salix alba L.) were prepared from shoots with the length of 25 cm and the diameter of approx. 2 cm, from a two-year old tree culture, cut into 5-centimetre-long pieces. Samples prepared in this way were packed in string bags with the dimensions of 100  200  0.040 mm, and stored in a refrigerator in the temperature of −4 °C. The samples were pre-treated with ultrasounds using ultrasound generator in the Warsaw University of Life Sciences (SGGW) at the Faculty of Food Sciences. They were placed in the ultrasound bath chamber made of acid-resistant steel, operating with the frequencies of 21 or 40 kHz and the power of 180 W. The ratio of the mass of the solution to the mass of the material was 4:1. Ultrasound exposure time was 10, 30 or 60 min. The experiment was carried out in duplicate. The drying process was performed in the drying laboratory at the Faculty of Production Engineering in the Warsaw University of Life Sciences. The drying process was conducted in the convective chamber dryer manufactured by MEMMERT, synchronized with the computer program, which measured the mass of the samples being dried in 1-min intervals, until the samples became stable, at the drying temperature of 60 °C. The control sample was also dried in a convective dryer, with the final stage of drying conducted in the drying furnace with the temperature of 105 °C, in order to determine the dry substance content [18] (Figs. 1 and 2). Fig. 1 Convective chamber dryer scales (drying oven) manufactured by MEMMERT

Fig. 2 Samples of biomass prior to drying (on the left) and following drying (on the right)

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4 Results Water content in wood W may be defined as the ratio of water content in wood to the mass of dry wood. The values of water content for the examined samples of willow were determined based on measurements of mass taken during the process of convective drying using the following formula:   mw  ms kgH2 O W¼ kgs:s: ms where: mw – mass of wet sample [g], ms – mass of dry sample [g]. This allowed for obtaining changes of water content depending on drying time for the control sample and for the samples not pre-treated with ultrasounds. Figure 3 shows changes of water content as the function of time for the control willow sample that was not pre-treated. Comparison of changes of water content as the function of time for the process of convective drying of the standard sample and the samples pre-treated with ultrasounds with the frequency of 21 kHz for 10, 30 and 60 min is presented in Fig. 3. Such comparisons were also performed for samples after pre-treatment with ultrasounds with the frequency of 40 kHz for 10,

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Fig. 4 Changes of water content as the function of drying time of samples pre-treated with ultrasounds with the frequency of 40 kHz for the period of 10, 30 and 60 min, at the temperature of 60 °C, compared with the control sample

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Fig. 5 Changes of water content as the function of drying time of samples pre-treated with ultrasounds with the frequency of 21 kHz for the period of 10 min, and the frequency of 40 kHz for 10 min, at the temperature of 60 °C, compared with the control sample

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Fig. 6 Changes of water content as the function of drying time of samples pre-treated with ultrasounds with the frequency of 21 kHz for the period of 30 min, frequency of 40 kHz for the period of 30 min at the temperature of 60 °C, compared with the control sample

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30 i 60 min (Fig. 4). Changes of water content as the function of time for samples pre-treated with ultrasounds with the frequencies of 21 and 40 kHz for 10, 30 and 60 min, in relation to the control sample, are presented in Figs. 5, 6 and 7, respectively.

5 Summary The conducted research related to ultrasounds as a method of pre-treatment of material prior to drying of wood biomass, did not show unequivocal impact on the process of drying. It may be caused by morphological structure of willow.

References 1. S. Białobok, Wierzby: Salix alba L., Salixfragilis L. (Państwowe Wydawnictwo Naukowe, Warszawa, 1990), pp. 9–27, 321–323, 339–340, 365–373 2. L. De Fusco, H. Jeanmart, J. Blondeau, A modelling approach for the assessment of an air-dryer economic feasibility for small-scale biomass steam boilers. Fuel Process. Technol. 134, 251–258 (2015) 3. J.K. Gigler, W.K.P. van Loon, I. Seres, G. Meerdink, W.J. Coumans, Drying characteristics of willow chips and stems. J. Agric. Eng. Res. 77(4), 391–400 (2000) 4. J.K. Gigler, W.K.P. Van Loon, M.M. Vissers, G.P.A. Bot, Forced convective drying of willow chips. Biomass Bioenerg. 19(4), 259–270 (2000) 5. L. Glijer, Suszenie drewna i nie tylko: poradnik (Wydawnictwo Wieś Jutra, Warszawa, 2011), pp. 18–26, 35–38, 58–61 6. S. Głowacki (red.): Postępy techniki w leśnictwie 63: Problematyka wykorzystania biomasy leśnej. Wydawnictwo Stowarzyszenie Inżynierów i Techników Leśnictwa i Drzewiectwa, pp. 36–41 (1997) 7. Sz. Głowacki, M. Sojak, S. Chojnowska, Wpływ temperatury i rozdrobnienia wierzby energetycznej na przebieg procesu suszenia. CIEPŁOWNICTWO, OGRZEWNICTWO, WENTYLACJA, nr 6 (2007) 8. S. Głowacki, W. Tulej, M. Jaros, M. Sojak, A. Bryś, R. Kędziora, Kinetics of drying silver birch (Betula pendula Roth) as an alternative source of energy, in Renewable Energy Sources: Engineering, Technology, Innovation, ed. by K. Mudryk, S. Werle (Springer Proceedings in Energy. Springer, Cham, 2018) 9. Sz. Głowacki, W. Tulej, M. Sojak, A. Bryś, J. Kaczmarczyk, M. Wróbel, M. Jewiarz, K. Mudryk, Analysis of the combustion process of selected wood biomass, in Renewable Energy Sources: Engineering, Technology, Innovation, ed. by K. Mudryk, S. Werle (Springer Proceedings in Energy. Springer, Cham, 2018) 10. M.E.G. Hendrickx, D. Knorr, Ultra High Pressure Treatments of Foods, Food Engineering Series (Kluwer Academic Press, New York, London, 2002) 11. Z. He, Z. Zhao, F. Yang, S. Yi, Effect of ultrasound pretreatment on wood prior to vacuum drying. Wydawnictwo Ciencia y tecnologia. Zeszyt 16(4), 395–402 (2014) 12. K. Jodłowski, Podręcznik dobrych praktyk w zakresie pozyskiwania biomasy leśnej do celów energetycznych (Wydawnictwo Instytut Badawczy Leśnictwa, Sękocin Stary, 2013) 13. J. Kieć, Odnawialne źródła energii (Wydawnictwo AR, Kraków, 2007)

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14. D. Knorr, M. Zenker, V. Heinz, D. Lee, Applications and potential of ultrasonics in food processing. Trends Food Sci. Technol. 15(5), 261–266 (2004) 15. A. Śliwiński, Ultradźwięki i ich zastosowania (Wydawnictwo Naukowo-Techniczne, Warszawa, 2001) 16. D. Witrowa-Rajchert, Ekspertyza. Nowe trendy w suszeniu żywności (Sieć AgEngPol, Warszawa, 2009) 17. A. Wójciak, W. Prądzyński, D. Chovanec, The effect of high energy ultrasonic treatment on wood and its components. Wydawnictwo Roczniki Akademii Rolniczej w Poznaniu (1993) 18. PN-77/D-04100

Analysis of Technical Solutions of Planting Machines, Which Can Be Used in Planting Energy Willow Taras Hutsol, Serhii Yermakov, Jurii Firman, Vasyl Duganets and Alla Bodnar

Abstract Energy willow planting process requires the use of highly effiecient and productive machines. The analysis of construction of machines for planting energy crops, forest plantations and seedlings and the processes which take place in the process of planting made it possible to systemize the accumulated experience in the design of planting machines, and highlight the most effective technical solutions. The revealed features of planting machines for different types of planting material are compared with the designs of energy willow planting machines. This study found a number of characteristics and advantages of different machine types, which will ultimately lead to an increase in productivity of planting aggregates and will facilitate the work of a planter.




Keywords Planting machine Plant setter Energy crops Cutting Planting material








Seedling planter
Forest planters


1 Introduction To date, a park of machines for laying energy plantations has been created, but the use of manual labor while planting tree crops significantly reduces the productivity of the plant setters used. In addition, planting of energy crops has a lot in common with planting of some other crops, in particular in forest cultivation and seedling planting, so to find ways to further improve machines for planting energy crops, it is advisable to analyze technological and design achievements in these areas. So, the creation of highly efficient plant setters is an actual scientific production task [1–3].

T. Hutsol (&)
S. Yermakov
J. Firman
V. Duganets
A. Bodnar State Agrarian and Engineering University in Podilya, Str. Shevchenko 13, 32300 Kamianets-Podilskyi, Ukraine e-mail: [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_10

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The general design of energy crops plant setters can be found in the brochures of the manufacturers producing the corresponding machinery, such as Egedal (Sweden), Iteam (Italy), Lignovis (Germany), Probstdorfer (Austria), Wimatec Mattes GmbH (Germany), and so on, and also on videodemonstrations of these machines, that often come with the presentation materials. However, these materials give only an over-the-top picture of the processes occuring inside the plant setters. The main material for the reproduction of such crops is the one-two year old lignified cuttings. According to the generalized results of the research, it is advisable to use cuttings from 20 to 30 cm in length and a thickness in the upper section of 4 to 15 mm, although in practice they use the cutters of 8…20 mm [4]. There are two ways of planting such cuttings: 1. when you plant the cuttings that have been previously prepared taking into account the proper size; 2. when you plant long (more than 2м) rods, and cut them directly in the plant setter. The loading of the full-size rods, and cutting them by the working elements of the machine is used in plant setters, known as “step-planter” (Fig. 1). Such machines are equipped with an oscillating mechanism for feeding the planting material (hereinafter referred to as p.m.) to coulter. When the technological process is implemented, the number of movements that the plant setter performs in order to plant reduces, that is why only one operator is able to provide high specific feed rate of cuttings, and also planting in 1 or 2 lines. His task is to select and attach the rod to the guide opening of planting machine. Such machines are specialized for dense planting of energy crops and appropriate manufacturers are responsible for their improvement (Egedal, Iteam, Lignovis etc.).

Fig. 1 Three-row plant setter of energy willow rods Step planter 3-reihig—Ernte Stemster. Source Lignovis

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When planting previously prepared cuttings, there is no process of cutting the rods with the plant setter, that is why the design of those machines that provide such kind of planting have a great variety, and considering the fact that the information about existing models available only with presentation and advertising materials, then the analogues can be found in plant setters that perform similar processes. First and foremost, those are the forest planters and seedling planters. Information about the structural aspects of forest planters can be found in the works of Asmolovskyi M.K., Zyma I.M., Malyutin T.T., Bartenyev I.M and others [5–7]. Similar studies were also conducted by Kasymov M.G., Mun V.P. and others [8]. But these studies are highly specialized and they do not contain examples of specific use for energy plantations.

2 Methodology of Research This work is aimed at identifying promising technical solutions, suitable for use in growing energy crops, which will increase the productivity of the cutting planting process. To achieve this objective, one has to accomplish the following task: • Analyze the constructions of forest and seedling planters and identify typical schemes; • Identify promising technical solutions that are suitable for use in the machines for planting energy crops. For an opportunity to draw conclusions about the possibilities of using constructive solutions of forest and seedling planters in the energy willow planters, the constructions and technological schemes of the process of planting that are realized in such machines are analyzed. The key elements of the process are highlighted and, according to this, systematized existing planting machines. The comparison of agrotechnical requirements to the process of energy willow planting with the parameters of this machines gave an opportunity to draw conclusions about the suitability of a technical solution for these purposes.

3 Analysis the Constructions of Forest and Seedling Planters and Their Compliance with the Requirements of Energy Willow Planting For those machines that are used in forest cultivation, the output is seedlings, saplings and cuttings prepared in advance, and by this they are close to energy crops plant setters. Seedling planters unlike the machines for planting tree crops, have a number of features resulting from the diversity of p.m. species, and also agrotechnical requirements for its planting. However, it is possible to find technical

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solutions for the planting of energy crops among them too. In all these machines the final result is ensured by the requirements for the installation and fixing of p.m. in the ground. The main agrotechnical processes that are implemented during planting are shown in Fig. 2. Having analyzed the working process of existing forest and seedling planters in terms of the prospects for increasing the productivity and automation of the process implementing, let us consider process 2 (Fig. 2), since an interconnection between the initial state of p.m. and its final placement into the soil takes place here, and that does not go without manual labor. In general, the technological process of transporting p.m. from the place of accumulation to the planting site can be characterized by the implementation of the following working processes: – – – –

extracting of p.m. from working tanks; loading of p.m. to the working element (or to the planting site at once); transporting of p.m. to the planting site; fixation of p.m. in the planting site (with necessary parameters)

These processes are interconnected in space and time with the general planting technology, as shown in Fig. 3.

Fig. 2 The main agrotechnical processes during planting [5]: 1—the preparation of a place for planting in the form of an uninterrupted furrow or a row of seedbeds; 2—the feed of p.m. and its placement in the planting site; 3—putting into the ground, and sealing along the line

Fig. 3 Structural scheme for the planting process using forest planters and seedling planters

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Analysis of working processes, that form the technological process of p.m. feed and its placement in a planting site, will allow to substantiate constructive decisions what will provide the necessary parameters (speed, rhythm, etc.) of work, and find their optimal values. Screening and transporting of p.m. from working tanks is typically performed manually, which a significant obstacle to achieving the high work productivity that is needed in the planting of energy crops. Transporting of p.m. to the planting site can also be performed manually, but in most cases it is solved by the equipment of plant setters with planting machines. There are several types of planting machines that can show different qualitative and quantitative indicators of the work done[9]. That is why, while looking for possible prototypes for energy tree crops plant setters, it is important to distinguish the degree of adaptation of these or other types of planting machines to agrotechnical requirements for their planting. In theory, machinery for planting forests is traditionally divided into four types of planting machines: radial (Fig. 6a), disk (Fig. 8a, b), lever-slide (or coulisse) (Fig. 12a) and the conveyor (Fig. 6b) [5, 6]. Analysis of the machines for planting forests showed that about 40–50% of the known plant setters brands are equipped with the planting machines of disk type, however, according to the indicators for use in planting of energy crops the planting machines of radial type are more suitable. Approximately every fourth machine brand is equipped with it. Sometimes the machines with such devices are equipped with means of automation. (for example, accessory PLA-1) [7]. In seedling planters we meet the same types (except only the lever-slide one) of planting machines, but it can be noted that large share of machines are equipped with vertical (Fig. 10b) or gravity (Fig. 10a) planting machine, although it should be noted that such solutions are used mainly for delivering of p.m. with a closed root system and therefore, given the features of design, they can hardly be recommended for use in the process of planting cuttings of energy wood crops. Thus, having analyzed the design of forest and seedling planters, we can select nine principal schemes for the implementation of the process of “placing p.m. in the planting site” (Fig. 1), which are illustrated in Figs. 3, 4, 5, 6 and 7.

Fig. 4 Technological schemes of planters without a planting machine: a—manual loading of p.m. in a slit or seedbed prepared by the machine; b—loading of p.m. to the mechanism of directing the seedlings over the coulter

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Fig. 5 Energy willow plant setter with manual feeding of cuttings Source Willowpedia

Fig. 6 Technological schemes of the planting machines with radial planting units: a—with planting units of the sprocket type; b—with conveyor planting units

Fig. 7 Plant setters with the radial planting unit with grabs. Source BioneraVideos1

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The easiest to implement are the plant setters with manual feed and placement of p.m. directly in the place of planting (Fig. 4a). Such machines have simple design, they are of small size and, accordingly, are cheaper. Minimization of additional accessories and working elements reduces the number of possible crashes, and therefore the reliability of work is high, and the lack of friction surfaces in the process of feeding p.m. provides high durability. However, in these machines there is a number of essential disadvantages associated with low level of the process mechanization and the substantial influence of the human factor on the quality of its performance, which reduces the possibilities of increasing productivity due to physiological limits of human capabilities. Under this scheme of the process implementation, the provision of ergonomic conditions of work is complicated and the working process requires a constant concentration of the planter, who performs a homogeneous, rhythmic, monotonous work, and therefore the dependence of the planting quality (verticality deviation of the planting, smoothness etc.) on the physical and mental state of a human [10]. It is possible to get rid of the latter disadvantage and improve the qualitative indicators of the seedling placement if you equip the plant setter with the p.m. tracking mechanism that allows you to synchronize the unit movement speed with the p.m. movement by the time of fixation. The tracking mechanism can be designed in the form of a grabber that moves backward in a horizontal plane (as shown in Fig. 4b) or in the form of two rubberized transveyers. Despite the slight complexity of the design, all the benefits of manual plant setters are preserved, while most of their drawbacks retain. One may find the machines of such type amongst the seedling planters, although it is noted that they are perfect for planting cuttings. Plant setters of such type are used in energy willow planting as well (Fig. 5). For a real reduction in the proportion of manual labor and all drawback associated with subjective factors, machines are equipped with planting devices— mechanisms that implement the transfer of p.m. to the planting site and its correct orientation. Radial units with sprocket-shaped holders (Fig. 6a) showed their best in forest planters. In seedling planters such planting machines are used mainly for seedlings with an open root system, and they can be identified with radial units of the conveyer type according to the principle of their work (Fig. 6b), in which the grabbers for p.m. are placed along the perimeter of the chain or tape. The advantages of such machines are conditioned by the exclusion of manual labor from the transportation process and positioning p.m. in the planting site. The role of man is reduced to extracting p.m. from the tanks and loading it to the planting machine grabbers. This allows you to achieve the best qualitative work indicators: to provide a stable plant spacing, orientation, accurate installation of p.m. in the planting place and so on. In addition, the possibility to change the place of laying p.m.

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(especially in conveyor ones) creates opportunities for comfortable working conditions and offers the prospects for using process automation tools. The disadvantages of the machines with radial planting units may include the need for positioning p.m. with regard to the grab while the laying process, and also the range of plant spacing adjustment, which is limited with the distance between the sprocket teeth or conveyor grabs. Radial planting units are well adapted for automation of technological process, as the grabs are able to independently extract the planting material from the specified coordinates. Which is easy to implement when applying flexible or hard cassettes to feed plants. Such solutions can be found among the machines for planting energy willow, however, as a non-cassette version, where the cuttings are taken to grabs by the planter (Fig. 7). Disk planting units are common among the design of forest planters. It should be noted that according to academic classification, disk units of rigid structure (Fig. 8a) and with elastic disks (Fig. 8b) fall into one category. In the working scheme the main difference lies in the fact that p.m. is laid in the special clamps on rigid disks, and in the elastic ones—in the place where two disks meet. The advantages of machines with disk planting units of rigid design are the accuracy of placing p.m. in the planting site, the accuracy of plant spacing, and the opportunity to set a small spacing. That is why they are used in planting, where it is necessary to reach the high density of plants in a row, that in the forestation finds its application for laying the shoots, and according to the initial parameters, such plantations are able to meet the requirements for planting energy crops. Units with elastic disks are use in the forest planting mainly for large p.m., however, they are also used in seedling planters, where they are used for planting tobacco, pepper, onions etc. The advantages of such machines are the simplicity of the planting unit, and also less danger of breakage. The disadvantages are the complexity of providing a radial location of p.m. when loading it into the planting machine, and hence the precise positioning of p.m. in the ground. Stable plant spacing under such a scheme depends on the competence and the condition of the planter.

Fig. 8 Technological schemes of the planting machines with disk planting units: a—with disk planting units (rigid disks); b—with elastic disk planting units

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Disk planting machines are implemented in planting energy willow (Fig. 9). Such plant setters require the constant performance of planters, one per row, and the monotony of work on loading cuttings in planting machines limits the possibility of increasing their productivity. Gravity planting machine (Fig. 10a) is a guide opening (a planting tube) in which planting material is directed to the planting site. Such machine is used in simple seedling planters (i.e. Ukrainian “Rosta” manual machines [11]). While using machines the device carries oscillatory motion in horizontal plane to be

Fig. 9 Energy willow plant setter with a disk planting machine. Source www.probstdorfer.at

Fig. 10 Technological schemes of the planting machines with the vertical planting material movement: a—with the gravity transportation of the planting material along the planting tube; b— with the vertical planting tool and circular motion devices

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agreed with the speed during positioning and planting seedlings. The simplicity and durability of the gravity planting machine construction make them promising for use as the last piece combined with additional devices, i.e. revolving and circular distributor mechanisms etc. The disadvantages of such devices are upgrading difficulties, requirements to the field, possibility of seedling damage while transportation and hitting the planting machine bottom. Machines with the vertical planting tool and circular motion or reciprocating motion devices (Fig. 10b) arrange careful transportation and potting of the planting material, so are used mainly for seedlings with the root-balled tree system into the cylindrical, conical, or pyramidal pots. There is a possibility to create ergonomic conditions in such machines, since the possibility for providing the work at the comfortable height and position, thus making the plant setter work easier. It is also possible to increase the productivity through the work of two planting pegs in one mechanism charging. Planting into the seedbeds, rather than in a gap does not create a big draught resistance of the device, but this fact provokes the necessity in the preliminary cultivation of matted and heavy soil. Such process implementation causes the construction complication and increased demands to sustain mechanism operability, especially for the reliability of the valve operation, the device stability is deteriorated with regard to the height dimensions. For planting energy willow you can use the planting tubes as guides for rods, which are cut into cuttings of 20–30 cm immediately before the planting. Such types of plant setters can be used for planting tapioca (an important tropical tuberous plant), which is planted similar to willow (Fig. 11).

Fig. 11 STR plant setter of the Italian company Iteam. Source internationalteam.eu

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Fig. 12 Technological schemes of planting machines with lever mechanisms: a—with lever-slide planting unit, b—with oscillating knife coulter

Lever-slide planting machines (Fig. 12) have not been widely used, because despite the convenient feeding of p.m. to the grabs, which can be directed to the right place in the required trajectory, such units have a number of disadvantages associated primarily with reliability, since the complex design and the lever system work create complex movements with variable grabbing speed, and the number of friction nodes increases. A disadvantage is also the limited ability to regulate the plant spacing. Planting machines with oscillating knife coulter (Fig. 12b) are known for their use in forest planters, since they allow to plant cuttings in seedbeds created by the knife coulter with relatively low energy requirements. For energy willow, where it is important to plant with as short plant spacing as possible, such design is ineffective, that is why their use for planting energy plantations is limited. In addition to these types of planting machines for planting the cuttings of energy crops the machines known as “rotor-planter” are used (Fig. 13). Plant setters look like loadbearing construction, which is a dismountable canvas of numerous pads resembling a track-laying mover. With a given plant spacing the cells for laying p.m. are placed in the pads [12]. The advantage of such machines is the high quality of placing p.m. in the planting site with precise plant spacing, given laying parameters (with a projection above the ground or level with), sealing of the planting site and so on. These machines work well in the problematic areas. However, the productivity of such machines remains low, although if the plant spacing is increased, there is a possibility to attract additional workers for the laying of cuttings.

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Fig. 13 The plant setter of energy willow with a planting unit that look like a caterpillar Wimatec Mattes GmbH (Hiмeччинa). Source http:// www.wimatec-mattes.de

4 Summary Having analyzed various designs offorest planters, seedling planters, and the machines for planting the cuttings for energy crops, we came to the following conclusions: • The reason for the low productivity of forest and seedling planting machines is manual labor in the process of placing p.m. in the planting site, that can partially be solved by the use of planting machines of different types; • The search for analogues in seedling and forest planting machines allows to suggest that some designs and principles of action are promising for use in the design of energy crops plant setters. In our opinion, radial, sprocket and conveyor planting machines, and also disk units of rigid design; • A promising direction is to reduce the proportion of manual labor when feeding p.m. by using rods in length of 2…3 m and installation on each line of the mechanism for cutting the cuttings; • In order to increase the productivity when planting pre-cut cuttings, it is necessary to create mechanisms for the automatic feeding of cuttings to the planting machines or directly to the planting site.

References 1. K. Dziedzic, B. Łapczyńska-Kordon, K. Mudryk, M. Wróbel, M. Jewiarz, B. Dziedzic, S. Yermakov, Decision support systems to establish plantations of energy crops on the example of willow (Salix Viminalis L.). Scientific achievements in agricultural engineering, agronomy and veterinary medicine polish Ukrainian cooperation. vol. 1, no. 1, pp. 150–160 (2017) 2. S.V. Yermakov, Perspektyvy udoskonalennia konstruktsii dlia sadinniazhyvtsiv enerhetychnykh kultur [Perspectives of improvement of constructions for energy crop planting]. Bull. State Agrarian Eng. Univ. Podilya 2(26), 37–45 (2017)

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3. V. Ivanyshyn, U. Nedilska, V. Khomina, R. Klymyshena, V. Hryhoriev, O. Ovcharuk, T. Hutsol, K. Mudryk, M. Jewiarz, Ɇ. Wróbel, K. Dziedzic, Prospects of growing miscanthus as alternative source of biofuel, in Renewable Energy Sources: Engineering, Technology, Innovation: ICORES 2017, (2018), pp. 801–812 https://doi.org/10.1007/978-3-319-72371-6_78 4. M.V. Roik, V.M. Sinchenko, Y.D. Fuchylo, Energetychna verba: texnologiya Vy`roshhuvannya ta vy`kory`stannya [Energy willow: cultivation technology and usage]. 340. LLC “Nilan-LTD”, Vinnitsa (2015) 5. M.K. Asmolovskyi, V.N. Loi, A.V. Zhukov, Mekhanizaciya liesnogo i parkovogo hoziaystva [Mechanization of the forest, park and garden management]. 450. BSTU, Minsk (2004) 6. I.M. Zyma, T.T. Maliutin, Mekhanizaciya lisohospodarskyh robit [Mechanization of the forest management work]. 488. “INKOS” firm, Kyiv (2006) 7. S.V. Yermakov, N.M. Borys, Sopostavlieniye resheniy liesoposadochnyh mashyn s tre-bovaniyami dlia energeticheskih drevesnyh kultur [Comparison of plant setter requirements for the energy wood crops (willow, poplar)]. Modern scientific reporter. Sci. Pract. J. 20-1(267), 67–70 Rusnauchknyga, Belgorod (2016) 8. N.G. Kasimov, V.I. Konstantinov, A.S. Kutiavin, Klassifikaciya rassadoposadochnyx mashyn po osnovnym priznakam funkcyonirovaniya. [Classification of seedlings planters according to the main operating principles]. Vestnik Izhevsk State Agric. Acad. 3(44), 20–25 (2015) 9. Seedling planters. http://www.agro-sistema.ru/index.php?option=com_content&view=article &id=89&Itemid=76. Accessed 20 Feb 2017 10. S. Yermakov, M. Borys, Analiz efektyvnosti agregativ dlya sadinnya energetychnoyi verby [Analysis of the machines` efficiency for energy willow planting], in Materialy XI Mezinarodni vedecko-prakticka conference “Veda a vznik – 2015”, vol. 14, pp. 47–49. Publishing House “Edukation and Science” s.r.o., Praha (2015) 11. Manual seedling planter PPM-1. Technical details and operations manual. http://www.rosta. ua/pics/passport/rrm1.rar. Accessed 20 Feb 2017 12. Planting of Short Rotation Plantations. http://www.lignovis.com/en/services/planting-ofshort-rotation-plantations-srp.html. Accessed 20 Feb 2017

Efficiency of Industrial Drying of Apple Pomace Małgorzata Jaros, Albert Gniado, Ewa Golisz, Szymon Głowacki and Weronika Tulej

Abstract The paper analyses the efficiency of apple pomace production in an enterprise producing dried vegetable and fruit. The dried vegetable and fruit was traditionally produced in drum driers. Pomace it is the pulpy residue remaining after fruit has been crushed in order to extract its juice and constitutes up to 25% of the total processed raw material. The research shows that to produce 1 ton of dried fruit is needed about 3.2 tons of dried pomace and about 400 kg of coal dust is consumed. The economic production efficiency was estimated at over 178% and the profit on sales of 1 ton finished product was 185 PLN. The costs of the enterprise directly related to production were taken into account and expressed in net terms. Investigating energy consumption in the production of dried pomace extracts, it was found that to reduce the humidity 1 of ton of pomace by 1%, it was necessary to use 142 MJ of energy in various forms. Increasing the efficiency of production must be associated with a reduction in the amount of heat for drying and introducing changes in technology. Keywords Apple pomace


Convective drying
Efficiency of drying
Biomass

1 Introduction Apples are the fruit most often grown in the European Union and Poland ranks a leading position in this area. Apple production increased in Poland from 1878 thousand tons in 2010 to 3604.3 thousand tons in 2016 [12]. Thanks to large production and relatively low production costs, in 2013 Poland became the global leader in the export of fresh apples, and is the second exporter of apple juice concentrate after China in the world. M. Jaros
E. Golisz (&)
S. Głowacki
W. Tulej Warsaw University of Life Sciences, Nowoursynowska 166, 02-787 Warsaw, Poland e-mail: [email protected] A. Gniado ENERGREEN S.C., Przemysław Popławski Mariusz Gniado, Potycz, Poland © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_11

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The pulpy residue remaining after fruit has been crushed in order to extract its juice is pomace, which as a waste mass from juice pressing processes constitute up to 25% of the total processed raw material. The pomace contains about 80% water, a lot of saccharides, and their pH is from 3 to 4 [21]. The composition of the pomace grows peel, approx. 94.1%, pulp and seeds 4.1%, [14, 19]. The large mass of apple pomace obtained in the process of pressing the juice has become a serious problem, noticed in all producer countries. Apple pomace does not have a targeted purpose, however, apple processing companies are looking for cost-effective and technologically solutions for their use. Their utilization is recommended due to the valuable ingredients contained in them for which fresh apples are valued [17]. The biochemical value of residues from the process of pressing apple juice is evidenced by the results of research carried out in many producer countries, including Poland [13]. Research shows that due to the high content of polyphenols having antioxidant and antiviral activity [16], there are sources of bioactive compounds with antibacterial, antiparasitic, anti-inflammatory and anti-cancer properties [7, 11]. They are therefore a valuable addition in food production. Researchers looking for value-added products indicate apple pomace as a raw material for the production of enzymes, organic acids, protein enriched feeds, edible fungi, ethanol, aromatic compounds and natural antioxidants [6, 18–20]. The economic rationale for the proposal to use such apple pomace is their low cost. The availability of pomace outside the apple harvest season requires proper processing. The most convenient processed form of the pomace is dried. Dried pomace retain their processing value, while they can be stored for a long time. In addition, the volume and weight reduced during drying significantly facilitates the storage and transport of product [10]. Research on the inclusion of dried apple pomace in the diet of various farm animals yielded very positive results, this applies to dairy cows [1], sheeps [5], goats [3], pigs [9], and poultry [4]. Food products containing properly selected quantities of dried fermented apple pomace, containing increased protein, fat and dietary fiber content, gain a new dietary quality of enriched food [16]. In addition to the indicated applications, dried apple pomace and selected yeast can be successfully used in the production of spirits [15]. Fresh pomace are used mainly as organic fertilizers or as animal feed. However, this method of utilization may pose a threat to animal health and the environment. Unfavorable environmental impact is mainly due to the high acidity of this waste. For example, fresh pomace added to ruminants’ feed cause fermentation in the rumen and alcoholemia of animals [20]. In the processing practice, knowing the benefits of rational management of waste from fruit and vegetable processing, many attempts have been made to balance them. Unprocessed pomace rot quickly, losing their valuable properties and can be a source of environmental pollution, thus constituting a significant problem for apple processing companies. The solution may be drying of pomace, because even those of reduced quality can be used as biofuel. The process of drying apple pomace should be economically and productively effective so that its product adds value to the production plant. The condition of this

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is the dried pomace quality acceptable by the potential customer and the profitability of the process for the producer. In order to justify the necessity of drying apple pomace, an expensive and highly energy-consuming process, it was decided to analyse the effectiveness of the technology of drying pomace, carried out by a specific company. The analysis was carried out on the basis of data provided by the company dealing in the production of dried fruit for food, feed and energy. The aim of this work was the analysis of the efficiency of apple pomace production in the enterprise producing dried fruit and vegetable. The scope of work included an analysis of the costs of enterprise, directly related to production, expressed in net terms.

2 Materials and Methods The company’s activity is seasonal. The peak of production falls on the harvesting period of apples, whose pomace constitute the largest mass of processed material. The surplus of pomace, which the company is unable to dry, is collected on an alternative storage yard and processed at the end of the season, usually at the end of December or later and intended solely for energy purposes.

2.1

Characteristics of the Raw Material

The pomace was sourced from the juice production plant within two months (October 20—December 20), when the apple juice was pressed at the maximum level of capacity of the press. Figure 1 shows a picture of fresh apple pomace made on a heap and in Fig. 2 produced apple juice. During the analysed period, the pomace contained about 3 kg of water per kilogram of dry matter, and met the requirement of drying Measurement of the moisture of the pomace and dried material was performed in the plant daily using a Radwag WPS 210S moisture Fig. 1 Apple pomace on the heap

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Fig. 2 Dried apple pomace

analyser, Gann G 86 hygrometer and Dramiński GMM hygrometer. technology— similar moisture. In order to compare the results of the measurements of the moisture of the pomace and dried material, the measurement was also made in the drying laboratory of the Department of Fundamental of Engineering at the Warsaw University of Life Sciences, for randomly picked sample of different places in the heap, using the drying method, based on the PN-90 /A-75101/03 standard, and the formula: w¼

m  ms 100 m

ð1Þ

where: w – moisture of sample, % m – mass of moist sample, g ms – mass of dry substance of sample, g Table 1 presents the results of the moisture determination of randomly sampled samples: the first in the laboratory, the other three in the drying plant. On the basis of Student’s t test for independent tests, it was found that at the level of a = 0.05 the determined moisture in a drying company does not differ significantly from the assay in the laboratory.

Table 1 List of moisture measurements of samples of pomace The date of the research

Relative moisture before drying (%)

Relative moisture after drying (%)

2015/11/5 2015/11/16 2015/12/3 2015/12/20

74.94 77.13 78.22 73.81

10.71 10.50 ± 0.5

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Methods of Estimation of the Production Effectiveness of Dried Pomace

Production efficiency, as an economic category, can be analysed on the basis of variously defined indices, depending on production results and inputs for production [2]. In the work, the following efficiency indicators were estimated: We1, also known as economy or profitability (formula 2), its desired value is less than one, which means that expenditures are smaller than the obtained effects, and We2 indicator being a measure of profitability of production (formula 3), its value is expressed as a percentage. We1 ¼

N E

We2 ¼ 100 

ð2Þ

EN N

ð3Þ

where: We1, We2 – indicator of production efficiency E – results of company activities (income from production) N – expenses incurred on the company’s operations (costs of production) Valuable information about production efficiency is provided indirectly by the profitability ratio of WRs sales of the produced product (formula 4), which determines the company’s ability to generate profit through sales. A high level of this indicator is desirable. WRs ¼ 100% 

EN E

ð4Þ

Another aspect in which the efficiency of production of dried apple pomace was considered was the energy consumption of production, assessed using the unitary indicator of direct energy consumption, Wenj, (formula 5) [8]. This indicator gives information about the amount of energy consumed in the studied process to produce a unit product. Wenj ¼ 100% 

W x

ð5Þ

where: Wenj – amount of energy, MJ x – amount of product. In the case of a dryer, the final product is the final weight Mk of the dried product, and x is the difference(x = M0 − Mk) of initial (M0) and final weight (Mk) of the raw material.

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Table 2 Basic technical and operational parameters of one drying line, determined based on data from two months of testing Parameter

Unit

Value

Nominal performance Average real performance

kg dried/h kg dried/h

1500 1200

Average heat consumption for evaporation of water Fuel consumption—culm, with the addition of biomass

kJ/kg

3350

kg/t dried

320–400

Temperature of the drying medium

°C

Installed power Drum dimensions

kW m

Mass of the dryer

t

700–850 80–130 205 9.00 2.30 34

2.3

Range Moisture: Raw material: 72% Dried material: 10% ibid Minimal calorific content of culm: 21400 kJ/kg Ash content up to 21% Outlet from the furnace Outlet from the drum Length Diameter

Characteristics of Drying Technology

Fresh pomace are harvested temporarily in the raw material warehouse to even out the supply stream and are then fed into two parallel drying lines. Each technological line is a set of integrated devices forming the equipment of the M-843 biomass tumble drier, made by the “Rofama” company. The basic technical and operating data of a single drying line is summarized in Table 2.

3 Results and Discussion The study was carried out in November and December, the peak months in the production of apple juice. At that time, the company dealt exclusively with drying apple pomace. Information on the consumption of electricity, solid and liquid fuels and purchased raw materials during this period was obtained on an ongoing basis from the company’s accounting book. The research shows that to produce 1 ton of dried fruit is needed about 3.2 tons of dried pomace and about 400 kg of coal dust is consumed. For the analysis of the effectiveness of the production of dried apple pomace, the values of production indicators referred to the working hours or to the weight of 1000 kg of dried product. at work it was assumed that all costs should be presented in net prices, which increased the values of the calculated indices, but it could be an argument to look for savings when comparing the company’s results calculated in gross prices. Net outlays that the company incurred to produce dried pomace

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Table 3 Net actual costs of working hours of two technological lines Components of costs

Expenditure, on average

Unit cost

Cost per 1 h of work

Electricity, including: power of engines and cooperating devices Coal dust for 2 dryers Diesel for backhoe loaders Raw material for 2 dryers Production workers

184.1 kW

0.32 PLN/kWh

58.91 PLN

960 kg/h 4 dm3/h 7680 kg/h 2 people

250.00 PLN/t 3.35 PLN/1 dm3 30.00 PLN/t 11.00 PLN/h

240.00 PLN 13.40PLN 230.4 PLN 22.00 PLN

Table 4 Components determining the energy consumption of the drying process Type of component

Expenditure, on average

Energy for producing 1 ton of dried pomace (%)

Electricity, including: –power of engines –power of cooperating devices Coal dust for 2 dryers with a calorific value of 22 MJ/kg Diesel for backhoe loaders with a density of 0.83 kg/dm3, calorific value of 43 MJ/kg

162.4 kW 21.7 kW

76.7 kWh = 276.12 MJ

3.02

960 kg/h

8800 MJ

96.33

4 dm3/h

59.48 MJ

0.65

Total

9135.6 MJ

100

resulted from the costs of electricity Kel, solid fuels Kps and liquid Kpc, labor costs of employees Kos and the raw material Ksur. N ¼ Kel þ Kps þ Kpc þ Kos þ Ksur

ð6Þ

The characteristics of the components of the cost of dried production are presented in Tables 3, 4 and 5. The consumption of electricity and solid and liquid fuels for the production of 1000 kg of dried fruit is summarized in Table 4. Table 5 Cost components for the production of dried apple pomace, related to 1000 kg of dried product Ingredients of production costs of dried

Denotation

Cost per 1000 kg of dried material (%)

Electricity Culm (coal dust) Diesel Raw material Production workers Total

Kel Kps Kpc Ksur Kos

24.54 PLN 100.00 PLN 5.58 PLN 96.00 PLN 9.17 PLN 235.29 PLN

10.43 42.50 2,38 40.89 3.90 100%

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Data from Tables 3 and 4 allow to determine the value of production cost components in relation to the weight of 1000 kg of dried fruit, their values are included in Table 5. As can be seen from Table 5, the production costs of 1000 kg of dried pomace apple calculated from the formula (6) amounted to 235.29 PLN. Over 83% of all production costs were the costs of raw material and culm used to dry pomace. and in them one should look for the possibility of reducing the total costs of the analyzed technology. The average price, which the company obtained from the sale of 1000 kg of apple pomace produced during the analyzed period, is 420 PLN. Profit is the difference between the sales price and expenditures, this is 184.71 PLN for 1000 kg of dried fruit. Economic efficiency of drying of apple pomace in the analyzed company, determined from formula (2), during the research period was 0.56. This value means that expenditures on production accounted for 0.56 of the income obtained from the sale of dried pomace. The indicator of the profitability of sales in net prices supplements the production efficiency ratio, determined from formula (4). He indicates that 44% of profit was achieved for every 1 PLN raised from sales. The level of profitability of dried pomace sales indicated in this way shows, that the company has big potential in shaping the margin on the sale of dried food. The We2 ratio, showing the relation of profit to expenditures, i.e. capital employed in production costs, was 78%, calculated from formula (3). This indicator may decrease drastically, when production will be burdened with high mark-ups, that increase the value of gross costs. Analysing the efficiency of the production of marc in the studied production line, in terms of energy consumption of the drying process, the unit direct energy consumption value was calculated, which amounted to 141.64 MJ/%, while the relative humidity of the raw material decreased by 64.5% on average. The calculations show that the production of 1000 kg of dried product requires the consumption of 9135.6 MJ of energy.

4 Conclusion Based on the analysis of the data, it was found that the profit, which is achieved by the researched company on the sale of 1 ton of finished product, is PLN 184.69. Economic efficiency was then 0.56, and the total production costs 1 ton of dried pomace amounted to PLN 235.29. Profitability of sales at net prices, determined in the work for the analyzed technology indicates that 44% of profit, attributable to each PLN 1 obtained from sales, was achieved. The paper also analyzed the efficiency of dried pomace production technology in the context of energy consumption in the process. It was found that for the production of 1 ton of dried material, with a relative humidity of 10.5%, 9.13589 GJ of

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total energy was used, of which 96.33% was energy obtained from the combustion of coal dust. It was also found that to reduce the moisture of the pomace by 1% it was necessary to use 142.08 MJ of energy in various forms. The comparison of the two aspects of dried pomace production assessments, which was examined in the paper, indicates that the improvement in the efficiency of the drying technology used is to reduce the consumption of solid fuel or to obtain apples with lower moisture, because after the juice pressing process, pomace still contain a large amount of juice. The problem of rational utilization of apple waste is not a simple matter, and the way to handle it in a production plant depends on the technical and organizational capabilities and the strategy adopted by the company. For the company, it is profitable to sell dried apple pomace, even if it is associated with its storage. On the other hand, when the processing possibilities is not available periodically, the dried product produced from stored fresh-pressed marc is used for its own needs as a biomass in solid fuel.

References 1. F. Abdollahzadeh, R. Pirmohammadi, P. Farhoomand, F. Fatehi, F.F. Pazhoh, The effect of ensiled mixed tomato and apple pomace on holstein dairy cow. Ital. J. Anim. Sci. 9, 212–216 (2010) 2. J. Adamczyk, Efektywność przedsiębiorstw sprywatyzowanych, AE Kraków, p. 33 (1995) 3. J.H. Ahn, I.H. Jo, J.S. Lee, The use of apple pomace in rice straw based diets of Korean native goats (Capra hircus). Asian-Aust. J. Anim. Sci. 15, 1599–1605 (2002) 4. A. Akhlaghi, Y. Jafari Ahangari, M. Zhandi, E.D. Peebles, Reproductive performance, semen quality, and fatty acid profile of spermatozoa in senescent broiler breeder roosters as enhanced by the long-term feeding of dried apple pomace. Anim. Reprod. Sci. 147(1–2), 64–73 (2014) 5. X. Alibes, F. Munoz, J. Rodriguez, Feeding value of apple pomace silage for sheep. Anim. Feed Sci. Technol. 11, 189–197 (1984) 6. S. Bhushan, K. Kalia, M. Sharma, B. Singh, P.S. Ahuja, Processing of apple pomace for bioactive molecules. Crit. Rev. Biotechnol. 28(4), 285–296 (2008) 7. S.T. Cargnin, S.B. Gnoatto, Ursolic acid from apple pomace and traditional plants: a valuable triterpenoid with functional properties. Food Chem. 220, 477–489 (2017) 8. H. Charun, Podstawy gospodarki energetycznej (Politechnika Koszalińska, Koszalin, 2004) 9. S.B. Cho, J.H. Cho, O.H. Hwang, S.H. Yang, K.H. Park, D.Y. Choi, Y.H. Yoo, I.H. Kim, Effects of fermented diets including grape and apple pomace on amino acid digestibility, nitrogen balance and volatile fatty acid (VFA) emission in finishing pigs. J. Anim. Vet. Adv. 11(18), 3444–3451 (2012) 10. B. Dobrzański, L. Mieszkalski, Właściwości fizyczne suszonych surowców i produktów spożywczych. Wyd. Nauk. FRNA, Lublin (2007) 11. K. Fujiwara, S. Nakashima, M. Sami, T. Kanda, Ninety-day dietary toxicity study of apple polyphenol extracts in Crl: CD (SD) rats. Food Chem. Toxicol. 56, 214–222 (2013) 12. Issue 4, 623–631.Mały Rocznik Statystyczny Polski (2016) 13. M. Kalinowska, A. Bielawska, H. Lewandowska-Siwkiewicz, W. Priebe, W. Lewandowski, Review apples: content of phenolic compounds vs. variety, part of apple and cultivation model, extraction of phenolic compounds, biological properties. Plant Physiol. Biochem. 84, 169–188 (2014)

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14. M. Kennedy, D. List, Y. Lu, L.Y. Foo, R.H. Newman, I.M. Sims, P.J.S. Bain, B. Hamilton, G. Fenton, Apple pomace and products derived from apple pomace: uses, composition and analysis, in Analysis of Plant Waste Materials. Modern Methods of Plant Analysis, ed. by H.F. Linskens, J.F. Jackson, vol. 20 (Springer, Heidelberg, 1999) 15. R.R. Madrera, R.P. Bedriñana, A.G. Hevia, M.B. Arce, B.S. Valles, Production of spirits from dry apple pomace and selected yeasts. Food and Bioprod. Process. 91 (2013) 16. R.R. Madrera, R.P. Bedriñana, B.S. Valles, Enhancement of the nutritional properties of apple pomace by fermentation with autochthonous yeasts. LWT - Food Sci. Technol. 79, 27–33 (2017) 17. D. Nowak, P.P. Lewicki, Infrared drying of apple slices. Innov. Food Sci. Emerg. Technol. 5 (3), 353–360 (2004) 18. R. Shalini, D.K. Gupta, Utilization of pomace from apple processing industries: a review. J. Food Sci. Technol. 47(4), 365–371 (2010) 19. F. Vendruscolo, P.M. Albuquerque, F. Streit, E. Esposito, J.L. Ninow, Apple pomace: a versatile substrate for biotechnological applications. Crit. Rev. Biotechnol. 28(1), 1–12 (2008) 20. S.G. Villas-Boas, E. Esposito, M.M. De Mendonça, Bioconversion of apple pomace into a nutritionally enriched substrate by Candida utilis and Pleurotus ostreatus. World J. Microbiol. Biotechnol. 19(5), 461–467 (2003) 21. Z. Wang, J. Sun, F. Chen, X. Liao, X. Hu, Mathematical modelling on thin layer microwave drying of apple pomace with and without hot air pre-drying. J. Food Eng. 80(2), 536–544 (2007)

Characteristics of Commercially Available Charcoal and Charcoal Briquettes in the Light of Petrographic Studies Zbigniew Jelonek

Abstract As of today, petrographic studies on charcoals and charcoal briquettes in Poland are rarely used as a source of information on the quality of fuels used for grilling. It should be noted that, according to the Polish Standard PN -EN 1860-2, petrographic analyzes of coals and briquettes are obligatory before placing the discussed fuels on the market. However, in the case of the majority of coal and briquette producers, these tests are carried out only once in order to receive a long-term certificate for the entire range of products. Most entrepreneurs believe that the process of producing grill fuels is stable and the parameters of wood used for their production are characterized by a very low variability. The same opinion prevails among the producers of charcoal briquette and is the reason why the tests, which should be carried out for each batch of a product entering the market, are rarely performed. Another argument in favor of the mentioned tests is the fact that fine coal and coal dust of both domestic and foreign origin are used in the production of briquettes. The presented article, based on petrographic analysis of coals and charcoal briquettes, pays special attention to the differences in the content of impurities in the analyzed material from different production periods. The research material was obtained from producers at the beginning of the calendar year (previous year’s production) and in autumn of the year in which the analysis was carried out (current-year production). In addition to the petrographic analysis, showing the percentage of solid contaminants, TOC, analyzes were performed for individual coals and briquettes. Furthermore, petrographic examination of grill ash was carried out. Additional examination of the material in terms of carbon content (TOC) has shown differences between the individual batches from different production periods. Supplementary petrographic analysis of ashes was carried out in order to show the amount of remaining solid impurities in the obtained material after the grilling process.

Z. Jelonek (&) Faculty of Earth Sciences, University of Silesia in Katowice, Będzińska 60, 41-200 Sosnowiec, Poland e-mail: [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_12

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The determination of the amount of remaining solid impurities in the ash was aimed at demonstrating their suitability as additives to gardening soil. The ash admixture in soil is associated with its deacidification in the case of an unwanted pH change during the production of gardening soil and with additional mineralization of the product intended for balcony garden. Keywords Charcoal


Charcoal briquette
Solid waste
Waste management

1 Introduction Charcoal has been used by humans since the dawn of time. Rock paintings are the first tangible proof of the use of charcoal. The finds of this type of art made using dyes derived from blood, compounds of iron, and coal from wood-fired furnaces date back to thirty two-thirty thousand years BC [1]. It can be assumed, however, that charcoal has been known for its healing properties long before its use in art. Currently, as a result of clinical trials, dry wood distillation products are widely used in the treatment of poisoning, ulcers, internal bleeds, external wounds, and fevers. They have also been used for centuries, although less consciously and more accidentally, by previous generations for alleviating these health problems [2]. It is difficult to clearly determine when the production of charcoal started. Perhaps this happened with the first use of fire, or maybe 5000 or 2700 years BC. The evidence of the use of charcoal, in e.g. copper production and iron smelting, date back to the mentioned periods [3]. It should be mentioned that in addition to the heating function, the discussed product is used in cosmetics, metallurgy (despite the introduction of more efficient fossil fuels), food industry, as a dye and as a component of filters, in medicine, and gastronomy. The unbreakable bond with charcoal has come full circle from campfires in caves and savannas, through the heavy industry, to grills. The growing awareness of the impact of heat treatment on food products is the reason why researchers started to study the effects of grilling methods. Most researchers, however, focus on analyzing the processed food itself, not taking into account the need to test the used grill fuels. Petrographic analysis of charcoal and charcoal briquettes can be a quick and reliable method for determining the quality of these fuels, contributing to the improvement of the quality of the meals consumed. At present, charcoal is produced in three basic technological lines, while in the case of Poland, the production of charcoal in charcoal piles was abandoned in the 80s of the last century [4]. However, some charcoal briquettes available on the market contain fine coal produced by this method in African countries and Ukraine.

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Therefore, this type of production cannot be omitted when correlating the content of solid impurities during the petrographic analysis and the origin of intermediate products when it comes to manufacturing methods. The second method of the charcoal production is the so-called retorting technology using portable steel cylinders of large diameter. The share of coal produced in this way in retail sales is slowly decreasing in favor of products obtained using the third method, that is the production of charcoal through dry distillation in stationary installations [5]. The charcoal briquette is made of fine charcoal fractions, usually residues after the production, selection, and final charcoal packaging. Fine coal and coal dust are mixed with water and starch binder; then, briquettes are formed and dried to a moisture content of 8%. Chemicals are added to some products in order to increase the compactness of the briquette mass and to facilitate its combustion. Chemically treated briquettes were not included in this study; only briquettes with natural starch binder with a binder content of up to 3% were tested. The quality of grill fuels directly translates into the quality of the grilled food and the quality of the air we and our neighbors breathe when grilling. In light of the above, demonstrating the need to carry out petrographic analysis of the content of contaminants in each new batch of goods entering the market will be of crucial importance to minimize the dangers of food preparation during the grilling process. This can be obtained thanks to the use of tested grill fuels, which produce the least air pollution.

2 Methodology Eight charcoal samples and eight charcoal briquette samples were subjected to analysis. The material for the analysis was produced in 2016 and 2017 (4 packages with a net weight of 2.5 kg of coal and 4 packages with a net weight of 2.5 kg of briquettes from each calendar year). The material for the analysis was collected from large, labeled commercial batches (with the name and address of the manufacturer, serial number, production year, composition, and qualitative parameters of the product) entering the Polish market. 16 microscopic preparations from each package were ground and prepared separately in accordance with the PN-ISO 7404-2: 2005 standard [6]. The samples were subjected to microscopic analysis in reflected white light according to the PN-EN 1860-2 [7] standard. The remaining part of the coal and briquette (1 kg of fuel per one package) was grilled, the grill was cleaned before each subsequent use. The ash obtained as a result of the combustion of coal and briquette was used to prepare 16 microscopic preparations.

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The ash samples were analyzed using a Zeiss Axioskop-20 microscope in order to determine the percentage of remaining impurities in the ash by counting 1000 elements determined at the intersection of the crosswire of the eyepiece. During the combustion process, dust emissions from individual parts of coal and briquettes were measured using a Testo 380 fine particle analyzer and a Testo 330 flue gas analyzer. The measurements was carried out for each tested fuel separately after 20 min from the lighting of the grill. The material derived from charcoal and charcoal briquettes was further analyzed for total carbon (TC) and total inorganic carbon (TIC) content. The analysis was performed using an Eltra CS-530 IR with a TIC module. Total carbon (TC) was measured using an infrared CO2 detector. The total inorganic carbon content (TIC) was measured during the reaction of the sample with 15% hydrochloric acid using an infrared CO2 detector. Total organic carbon (TOC) was calculated from the difference between TC and TIC.

2.1

Materials

Charcoal and charcoal briquette samples were coded due to the fact that consent for publication of data was not obtained from the manufacturers. Table 1 shows the symbols assigned to products, producers, and the production year. The assigned numbers for coals and briquettes were maintained for samples derived from the ashes by adding the letter P.

Table 1 The summary of the examined charcoal and charcoal briquettes

Charcoal Manufacturer

Production year 2016

Production year 2017

1 WD-1 2 WD-5 3 WD-7 4 WD-11 Charcoal briquette Manufacturer Production year 2016

Production year 2017

5 6 7 8

B-9 B-13 B-20 B-28

B-2 B-6 B-11 B-15

WD-18 WD-10 WD-20 WD-15

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3 Results 3.1

Petrographic Analysis of Charcoal, Charcoal Briquettes, and Ashes Obtained After the Combustion of the Above Mentioned Fuels

The ash preparations obtained as a result of the combustion of the obtained materials were subjected to microscopic examination; the results are presented in Table 2. The charcoal preparations were subjected to microscopic analysis for the presence of pollutants, i.e. fossil fuels, crude oil, coke, pitch, plastics, glass, slag, rust, metals, stone powder, and mineral matter; the obtained results have confirmed that they have a low content of impurities (Table 3). Table 4 presents the results of the petrographic analysis of charcoal briquette samples, where a significant increase in the contamination of products compared to charcoal can be observed. All of the above analyses have been made according to the guidelines contained in the PN-EN 1860-2 standard. In addition, in Tables 3 and 4, column 11, the percentage content of biomass in the polished sections was demonstrated for each sample by carrying out additional microscopic analysis of the examined coals and briquettes. Table 2 The percentage content of the components determined in ashes resulting from the combustion of charcoal and charcoal briquettes Column number Sample no.

1

2

3

4

5

Changed organic matter

Unchanged organic matter

Inorganic compounds

Metals, rust

Columns 1–4

WD-1-P WD-5-P WD-7-P WD-10-P WD-11-P WD-15-P WD-18-P WD-20-P B-2-P B-6-P B-9-P B-11-P B-13-P B-15-P B-20-P B-28-P

2.9

2.3 3.1 3.8 3.4 2.6 3.4 2.3 4 2.1 2.2 2.3 1.9 2.1 2.2 2.3 1.9

94.8 96.6 95.2 95.2 97.2 94.3 97.7 94.9 92.4 95 94.8 95.2 89.1 94.9 97.7 95.1

1.4 2.3 1.1 5 1.6 2.2 1.9 2 2.4

0.3 1 0.2

0.5 1.2 0.7 1 6.8 0.5 3

100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100

WD-1 WD-5 WD-7 WD-10 WD-11 WD-15 WD-18 WD-20

Column number Sample no.

0.1

0.2

0.1

0.1

Plastics

Fossil coal

0.3

2

1

0.1

Glass

3

0.1

0.1

Rust

5

0.1 0.2

Metals

6

2.1 1 0.3 0.5 0.6 1.2 0.8 0.6

Mineral matter (including stone powder)

7

2.4 1.1 0.6 0.6 0.7 1.4 0.8 0.9

The total content (%) of P impurities in the sample ( columns 1–7)

8

Table 3 The percentage content of the components determined in the examined charcoal

97.6 98.9 99.4 99.4 99.3 98.6 99.2 99.1

Charcoal

9

100 100 100 100 100 100 100 100

Columns 8–9

P

10

0.6

0.5

1.8 3.2

The biomass per 100% of the sample

11

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B-2 B-6 B-9 B-11 B-13 B-15 B-20 B-28

Column number Sample no.

0.3

Plastics

Fossil coal

0.6 0.1 0.2 0.1 0.2 0.2

2

1

0.2 0.1 0.1

0.2

Glass

3

0.6

0.3 0.1 0,2 1.2 0.1

Rust

5

0.1

Metals

6

9.1 37.5 3.6 1.9 25.4 2.6 0.3 6

Mineral matter (including stone powder)

7

10.3 37.9 3.9 2.4 26.9 3 0.3 6.6

The total content (%) of impurities in the sample P ( columns 1–7).

8

Table 4 The percentage content of the components determined in the examined charcoal briquettes

89.7 62.1 96.1 97.6 73.1 97 99.7 93.4

Charcoal

9

100 100 100 100 100 100 100 100

Columns 8–9

P

10

3.6

0.5 1.4

8.8 1.6 1.8

biomass per 100% of the sample

11

Characteristics of Commercially Available Charcoal … 129

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Table 5 The results of the measurement of the grill exhaust gas Sample no.

PM g/m3

CO g/ m3

% CO2

% O2

Flue gas temperature °C

Outside temperature °C

Outside humidity Relative humidity (%)

B-2 B-6 B-9 B-11 B-13 B-15 B-20 B-28 WD-1 WD-5 WD-7 WD-10 WD-11 WD-15 WD-18 WD-20

0.029 0.014 0.017 0.005 0.009 0.018 0.005 0.019 0.008 0.011 0.020 0.004 0.007 0.008 0.006 0.012

13.996 9.820 9.163 11.409 10.943 11.430 16.354 11.682 10.018 10.448 9.982 11,284 10.046 9.874 10.140 9.683

3,44 3.42 3,26 2,71 3,99 3,96 2.96 2.31 4,18 6,01 5,22 5,47 5,52 5,78 5,01 5,84

18.5 18.9 18.1 18.1 17.9 18.2 18.4 18.3 17.7 16.9 17.9 17.1 17.8 17.4 17.8 17.2

204 198 202 204 226 208 219 225 184 199 188 186 192 186 194 183

24.4 24.4 24.4 24.4 25.0 25.0 24.9 24.9 24.9 24.9 24.9 25.0 25.0 25.2 25.2 25.2

60.9 60.9 60.8 60.1 59.4 59.2 59.3 59.6 59.5 59.1 59.5 56.9 60.1 60.7 60.5 60.2

3.2

The Analysis of the Grill Exhaust Gas

The results of the grill exhaust gas measurements are summarized in Table 5; the measurements were carried out using certified machines designed to test exhaust gases and dust produced during the combustion of solid fuels and gas.

3.3

Charcoal and Charcoal Briquettes Analysis for Total Carbon and Sulfur Content in the Manufactured Products

Table 6 presents the results of the total carbon content analysis (TC—total carbon). The test was performed in order to confirm the declared content of elemental carbon in the manufactured products.

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Table 6 The total carbon content in the analyzed coal and briquettes Sample no.

B-2

B-6

B-9

B-11

B-13

B-15

B-20

B-28

TC % Sample no. TC %

63.2 WD-1 75.6

27.3 WD-5 83.2

62.5 WD-7 75.9

72.8 WD-10 82.1

33.2 WD-11 81.9

70.4 WD-15 80.3

76 WD-18 8.2

55.7 WD-20 77.4

3.4

The Components and Impurities Determined in the Analyzed Products During Microscopic Examination

In the examined charcoal, in addition to the organic matter, processed as a result of the wood pyrolysis process (Fig. 1), biomass (Fig. 2), fossil coal (Fig. 3), rust, metals (Fig. 4), plastics, and glass (Fig. 5) can also be observed. Another important component of charcoal is the mineral matter represented mostly by fine silicate and carbonate fractions (Fig. 6), and stone powder (Fig. 6, WD-5). In the case of the examined charcoal briquettes, the dominant charcoal is accompanied by a high content of mineral matter (Fig. 7). Increased amounts of rust, metals, and glass in the examined material have also been observed (Fig. 8). Furthermore, based on microscopic images, the occurrence of fossil coals and biomass in the form of binders (bran, seeds) and small pieces of wood has been confirmed. Based on microscopic examination, it can be stated that preparations from ash obtained from the combustion of grill fuels are characterized by the presence of inorganic matter and compounds and small residues of metals and rust. The unchanged (Fig. 9) and transformed (Fig. 10) organic matter in the ash was in the range of around 3–4%. Their content was highly variable depend-ing on the examined sample.

WD-1

WD-5

WD-7

Fig. 1 Microscopic image of charcoal, immersion oil, magnification 500x

WD-10

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WD-5

WD-7

WD-15

WD-20

Fig. 2 Microscopic image of biomass in charcoal, oil immersion, magnification 500x

WD-1

WD-10

WD-15

WD-20

Fig. 3 Microscopic image of fossil coal, oil immersion, magnification 500x

WD-5 (metals)

WD-7 (metals)

WD-7 (rust)

WD-11 (rust)

Fig. 4 Microscopic image of metals and rust, oil immersion, magnification 500x

(plasƟc)

(glass) WD-20

Fig. 5 Plastics and glass particles in charcoal, microscopic image, oil immersion, magnification 500x

WD-1

WD-5

WD-7

WD-10

Fig. 6 Microscopic image of mineral matter in charcoal, oil immersion, magnification 500x

Characteristics of Commercially Available Charcoal …

B-2

B-6

133

B-9

B-11

Fig. 7 Microscopic image of mineral matter in charcoal briquettes, oil immersion, magnification 500x

B-2 (a)

B-11 (b)

B-13 (c)

B-15 (d)

Fig. 8 Glass (a, b, c) and ceramic (d) impurities in charcoal briquettes, microscopic image, immersion oil, magnification 500x

WD-1-P

WD-20-P

B-2-P

B-20-P

Fig. 9 Microscopic image of unchanged organic matter in charcoal briquettes and ashes from charcoal briquettes, oil immersion, magnification 500x

WD-1-P

WD-10-P

B-2-P

B-6-P

Fig. 10 Microscopic image of changed organic matter in charcoal briquettes and ash from charcoal briquettes, oil immersion, magnification 500x

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4 Summary and Conclusions When it comes to the content of solid impurities, in the case of 62.5% of the tested charcoals the content of the mentioned additives listed in the PN-EN 1860-2 standard is within the permissible limit of 1%. The limit values were slightly exceeded in two of the tested coals, while in the case of one product the permissible content of impurities (1%) was exceeded more than twice. It should be noted that the main undesirable components in charcoal are mineral matter and rock powder. While they increase the weight of the product, they do not have carcinogenic effects on the processed food, which is important from the point of view of the consumer. No harmful elements like crude oil, coke, coal tar, and slag were found in the tested products. Meanwhile, fossil fuels, plastics, glass, rust, and metals are present in low amounts or not at all. In the case of charcoal, based on the comparison of samples from the years 2016 and 2017 (Table 7), it can be stated that none of the products of individual producers meet the standards of previous years. The differences (in the range between 0.3–1.6%) are relatively significant; when it comes to the restrictive limit content of 1%, a 0.3% difference for products from different years may be crucial when placing a given product on the market. Therefore, in the light of the obtained results, analyzing each batch of the product entering the market becomes justified, the more so as the use of contaminated grill fuels increases the harmfulness of thermal processing of food products [8]. The results of the analysis of charcoal ashes confirm a high content of unchanged organic matter in the range of 2.3–4%. This, compared with the results for ash obtained from the combustion of briquettes, in which the content of unchanged organic matter ranges from 1.9 to 2.3%, indicates better combustion of briquettes. In addition, the measurement of flue gas temperature has shown that the temperature of gases emitted from the combustion of charcoal is lower than the temperature of flue gases from the combustion of charcoal briquettes. In addition, low oxygen level and a high level of CO2 and CO in the exhaust gases during the combustion of charcoal, compared to measurements made during the combustion of briquettes, is also observed. Since both fuels were burned under similar conditions (temperature and external humidity) and in the same device, large amounts of unchanged matter remaining in the ash resulting from the combustion of charcoal indicate its poorer heating properties compared to briquettes. An additional observation when interpreting the results from the analysis of the combustion of grill fuels is the lack of relationship between the carbon content in a given product and its efficiency (high temperature of emitted flue gases) during the combustion. The carbon content was determined in order to compare the obtained results with the carbon content declared by the producers. In the case of charcoal, the carbon content in individual products is in accordance with the content declared by the manufacturers. On the other hand, when it comes to charcoal briquette, similar (70–75%) carbon contents to those declared for the individual batches by the manufacturers were observed only in the case of three out of eight manufacturers.

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Table 7 The percentage content of impurities for charcoal in individual products Charcoal Manufacturer 1 2 3 4

Production year 2016

The percentage of impurities

Production year 2017

The percentage of impurities

WD-1 WD-5 WD-7 WD-11

2.4 1.1 0.6 0.7

WD-18 WD-10 WD-20 WD-15

0.8 0.6 0.9 1.4

In addition, grill ashes are also a valuable additive to soil for home gardens and balcony plants [9]. Based on the analysis of microscopic images, no accumulation of impurities in ash preparations has been found. The quantitative components remaining after the combustion of grilling fuels in the unaltered state are rust and metals. However, these quantities are so small that they do not affect the quality of fly ash resulting from the grilling process, which is used as an additive to gardening soil. The increased content of organic matter in the form of unburned charcoal particles, however, enriches the ashes obtained from the combustion of charcoal with additional porous material supporting the accumulation of water in the soil for seedlings. When it comes to impurities listed in the PN-EN 1860-2 standard, charcoal briquettes did not exceed the limit of 1% in only one case. Table 8 presents the relationship between the date of production and the percentage of impurities in the examined briquettes. As in the case of charcoal, the briquette is characterized by differences in the content of impurities depending on the date of production. However, in the case of charcoal briquettes, they are even bigger than in charcoal. However, as shown by exhaust gas analysis, the main undesirable component, that is mineral matter, is not affecting the quality of the combustion process and even contributes to an increase in their temperature. As has been shown in the case of the producer No. 6, the mineral matter content is at a very high level for both batches on a year-to-year basis, while the difference is up to 10%. The high content of fine sand in the discussed products does not significantly affect the quality of the thermally processed food. However, it is the reason for serious problems during the combustion of briquettes, making impatient grill users to use fire starters (usually based on paraffins, which are harmful to the environment). Large amounts of mineral matter also significantly shorten the operation of the grill, resulting in more frequent need to feed the furnace with grill fuel, thus increasing its consumption. Some of the samples examined microscopically under reflected light were found to contain biomass; while biomass is not considered as impurity according to the above mentioned standard, it should be classified as such. In order to isolate biomass, a separate analysis of each sample was carried out. The biomass is determined as a percentage ratio of biomass content to the content of charcoal in the analyzed briquette or charcoal briquette per 1000 acceptable points. An increase in particulate matter emissions, measured using a fine particle analyzer, can be

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Table 8 The percentage content of impurities for charcoal briquettes in individual products Charcoal briquette Manufacturer Production year 2016

The percentage of impurities

Production year 2017

The percentage of impurities

5 6 7 8

10.3 37.9 2.4 3

B-9 B-13 B-20 B-28

3.9 26.9 0.3 6.6

B-2 B-6 B-11 B-15

Table 9 The percentage content of impurities for charcoal briquettes in individual products Sample no. B-2 B-6 B-9 B-11 B-13 B-15 B-20 B-28 WD-1 WD-5 WD-7 WD-10 WD-11 WD-15 WD-18 WD-20

The percentage share of biomass content in charcoal and charcoal briquettes 8.8 1.6 1.8 0 0.5 1.4 0 3.6 0 1.8 3.2 0 0 0.5 0 0.6

PM g/m3 in the grill exhaust gas 0.029 0.014 0.017 0.005 0.009 0.018 0.005 0.019 0.008 0.011 0.020 0.004 0.007 0.008 0.006 0.012

observed in relation to the bio-mass content of the examined products (Table 9). Due to the fact that particulate matter emitted from grills contributes to smog formation (especially during hot summer days in sunny places with large numbers of barbecue grills, such as leisure centers), any additives leading to increase in particulate matter emissions should be legally banned. Petrographic analysis carried out in accordance with the Polish standard PN-EN 1860-2 provides a lot of information about the quality of grill fuels and is a quick and easy method to determine impurities in charcoal and charcoal briquettes. Petrographic examination of grill fuels should be used as a reliable and cheap determinant of the quality of products offered for sale, thus contributing to the elimination of harmful, contaminated products. Additionally, uncontaminated grill fuels will maximally re-duce the negative impact of this type of thermal processing of food, as described by many researchers and journalists in the daily press, on human health and the environment [10, 11].

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References 1. Malarstwo, Historia sztuki (Painting (History of Art), Jackowiak Dominika, Wydawnictwo SBM Renata Gmitrzak, 2016, pp. 6–9 2. Leczenie węglem drzewnym (Charcoal treatment) Agatha Thrash, Calvin Thrash, Wydawnictwo Fundacja Źródła Życia, 2008, pp. 10–70 3. Ze studiów nad historią techniki polskiego hutnictwa żelaznego do XVII wieku. The studies on the history of technology of the Polish steel industry until the seventeenth century, Przegląd Historyczny (Historical Review), 43/2, 1952, pp. 202, 215 4. Wypał węgla drzewnego w Bieszczadach w przeszłości i obecnie. E. Marszałek, W. Kusiak, Charcoal production in the Bieszczady Mts. in the past and at present. Roczniki Bieszczadzkie, 21, 165–175 (2013) 5. Współczesna technologia suchej destylacji drewna. G. Lewandowski, E. Milchert, Modern installation of dry distillation of wood. Chemik, 65(12), 1301–1306 (2011) 6. The Polish Committee for Standardization, Polish standard PN-ISO 7404-2:2005, October 2005. Part 2: Method of preparing coal samples 7. The Polish Committee for Standardization, Polish Standard PN-EN 1860-2, June 2006. Appliances, solid fuels, and firelighters for barbecueing—Part 2: Barbecue charcoal and barbecue charcoal briquettes—Requirements and test methods, Warsaw 8. Zasady zdrowego grillowania. J. Szczęsna, Rules of healthy grilling, OPZiOZ WSSE, Opole, 2010, pp. 4–8 9. Z. Jelonek, Perspective of the use of ashes from barbecue grills as an additive for mineral fertilizers, MEERI PAS 2017, pp. 67–78 10. A. Ciemniak, Porównanie wpływu metody grillownia na zawartość benzo[a]pirenu w mięsie kurcząt, Żywność. Nauka. Technologia. Jakość, 3(52), 54–61 (2007) 11. A. Zachara, . L. Juszczak, Zanieczyszczenie żywności wielopierścieniowymi węglowodorami aromatycznymi—wy-magania prawne i monitoring. Żywność. Nauka. Technologia. Jakość, 3(106), 5–20 (2016)

Physical and Chemical Analysis of Biomass Pellets in Terms of the Existing Standards Dorota Koruba and Jerzy Zbigniew Piotrowski

Abstract The paper presents biomass as an alternative renewable energy source for fossil fuels, the combustion of which provides neutral CO2 emission, thereby making it the potential main primary energy medium in Poland. The paper also presents the heat results of combustion, humidity, content of ash, volatile compounds and C,H,N,S in selected dry pellets (straw, hemp willow, wheat straw) with division into fractions: 0.5 mm, 0.25 mm, 0.125 mm and below 0.125 mm. In relation to the analysis of the study results, the paper includes a discussion on the requirements specified in standards regarding biomass quality research and especially concerning the basic parameters determining the energy value of biomass (combustion heat, humidity, volatile organic compounds, ash content, CHNS). Keywords Biomass pellets


Physical and chemical analysis
CO2 emission

1 Introduction As result of human activity, we are observing progressing climate change, which is especially visible in the increasing concentration of greenhouse gases (carbon dioxide, methane and nitrous oxide) in atmospheric air [1, 2]. Anthropogenic emission of greenhouse gases are caused by economic activity, but mainly by the combustion of fossil fuels, such as coal, petroleum and natural gas. The concentration of carbon dioxide has been increasing for over 200 years, since the beginning of the industrial revolution, when the CO2 concentration amounted to 280 ppm, while in 1958 it reached 316 ppm. May 2013 was the first time the CO2

D. Koruba (&)
J. Z. Piotrowski Faculty of Civil and Environmental Engineering, Kielce University of Technology, Kielce, Poland e-mail: [email protected] J. Z. Piotrowski e-mail: [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_13

139

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Fig. 1 Averaged CO2 values from the Mauna Loa observatory in Hawaii from May 2018

concentration exceeded 400 ppm, whereas in March 2016 it exceeded 405 ppm. In May 2018, the concentration exceeded 410 ppm (Fig. 1) [3]. The chart in Fig. 1 is updated daily and presents particular points, the daily and hourly average CO2 level from the last 31 days. The daily average CO2 are calculated based on the selected hourly values that meet the “background” conditions, CO2 concentration stability and durability. In the time of global warming related to the risk of continuous increase in the air’s CO2 concentration, Paris hosted the United Nations Framework Convention on Climate Change, 21st Conference of the Parties in 2015. The conference’s topic was the determination of long-term objectives of carbon dioxide zero emissions and thus acting to maintain the increase in global average temperatures at a level lower than 2 ° C. In relation to the arrangements made by countries taking part in the climate conference, Poland faces a huge challenge, because our economy is largely based on coal, but it is possible to use energy from unconventional sources, thus allowing to meet obligations and increase the country’s energy safety. The use of state-of-the-art technologies in the field of renewable energy sources allows for drawing energy from the Earth’s natural resources. Biomass is one of the potential largest renewable energy sources [4, 5]. The production of energy deriving from biomass combustion can substantially contribute to the improvement of the country’s energy self-sufficiency. In 2017, the Energy Regulatory Office presented the data on the increase of the installed capacity of the country’s renewable energy sources. The ERO does not however register all RES systems connected to the national power grid and omits,

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141

among others, prosumer micro-systems connected per notification. The highest increase in power was recorded by the ERO in the I quarter of 2017 in the biomass power engineering. The potential of biomass power plants improved from 1281.065 MW at the end of the IV quarter of 2016 to 1297.97 MW at the end of March 2017, i.e. by 16.9 MW. The potential of biogas power plants improved from 233.967 MW at the end of 2016 to 235.257 MW, i.e. by 1.29 MW. Due to the popularity of using solid biofuels in heating systems, in 2000, the European Commission established the European Technical Committee CEN/TC 335 Solid Biofuels [10], the objective of which was to standardise the solid biofuel quality system. According to the Directive 2000/76/EC, the Committee was tasked to conduct standardisation work in the scope of solid biofuels. In the years of 2003– 2006, over 30 specifications referring to solid biofuels were introduced and entered into force 3 years after their publication. In the transition period, the standards are designated as CEN/TS [10], and then are updated and elaborated on so that they can ultimately be introduced as EN European Standards. In Poland, the Coke and Processed Solid Biofuels Technical Committee no. 144 was established and introduces CEN/TC standards and eventually EN standards. During the research on biomass pellets, the question was asked whether it is possible to use a selected representative sample to make designations aimed at determining the technical quality of the studied fuel. It turned out impossible due to the fact that each standard requires different sizes of studied sample fractions.

2 Materials and Methods Testing material: willow pellet, straw pellet, wheat straw pellet. Used measuring equipment: KL-12Mn calorimeter, computer, analytical scale, LMN 100 biomass knife mill, vortex mixer. The testing material in the form of a pellet was crushed using a mill and then divided into particular fractions with the following dimensions: 0.5 mm, 0.25 mm, 0.125 mm, i > > = < hR Tliq Tsol cph;c PCM ðT ÞdT þ Lf ð1Þ Tsol \T\Tliq > > > > Tliq Tsol ; : cph;c PCM ;liq T\Tliq where: T Tsol Tliq cph,c,PCM,sol cph,c,PCM,liq

– – – – –

PCM temperature [K], Temperature limit of solid phase [K], Temperature limit of liquid phase [K], PCM specific heat of solid phase [J/kgK], PCM specific heat of liquid phase [J/kgK].

The problem with describing PCM specific heat variation as a function of temperature can be solved, which shall be presented using the example of phase change material characteristics—A44.

3 Modified Classical PCM Model Classical model of phase change material, that is presented in Fig. 1 and described by Eq. (1), was modified. The curve representing specific heat variation as a function of temperature was divided into six parts (Fig. 2) which were described using Eq. (2). The curve is plotted using three points. The first point has coordinates (x1, y1) that refer to temperature and specific heat of PCM transition from solid to transition phase respectively. The second point has coordinates (x3, y3) that refer to temperature and latent heat (maximum value) respectively. The third point has

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coordinates (x5, y5) that refer to temperature and specific heat of PCM transition from transition phase to liquid. The value of variable Pmax is crucial to modify classical PCM model. It defines the position of specific heat peak point with respect to starting and ending points of phase change. This variable is used for adding asymmetry to Gaussian curve, that shows the change in PCM specific heat as a function of temperature with respect to the point whose coordinates are (x3, y3), and adapting it to actual characteristics. If the value of Pmax is 0.5, the curve representing the changes in PCM specific heat as a function of temperature is symmetric with respect to the point whose coordinates are (x3, y3). If the value of Pmax is below 0.5, the slope of the curve is steeper towards solid phase, otherwise (Pmax > 0.5) the slope of the curve is steeper towards liquid phase (Fig. 3). Modified PCM model helps determine heat capacity of tank at constant volume and filled with PCM, perform simulation tests focusing on energy efficiency analysis of the system that combines PCM storage tank and heating or cooling source, for example, solar thermal installation, heat pump, etc. as well as enables control algorithm of this kind of system to be developed and optimise along with the algorithm that monitors the charge and discharge rate of tank in operating conditions.

cpPCM

8 y > > 1 2 > > xx1 > > y1 þ 0:5Pmax > ðy5 y1 Þ ðy2  y1 Þ > >  2 > > x3 x < 0:5  ðy3  y1 Þ þ y2  0:5Pmax ðy5 y1 Þ ðy3  y2 Þ ¼  2 > > 3 > 0:5  ðy3  y5 Þ þ y4  0:5ð1Pxx ðy3  y4 Þ > Þ ð y y Þ max 5 1 > >   > 2 > x5 x > > > y5 þ 0:5ð1Pmax Þðy5 y1 Þ ðy4  y5 Þ : y5

9 > > > > > x1 \x  x2 > > > > > > x2 \x  x3 = > > x3 \x  x4 > > > > > > > x4 \x  x5 > > ; x5 \x

x  x1

ð2Þ

Fig. 2 The curve representing PCM specific heat variation as a function of temperature for Pmax = 0.5

Modelling of Heat Storage Using Phase Change Material Tank

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Fig. 3 The curve representing PCM specific heat variation as a function of temperature for Pmax = 0.75

where: x1 y1 x2 y2 x3 y3 x4 y4 x5 y5

– – – – – – – – – –

Temperature Tsol, PCM specific heat of solid phase cpsol, Temperature calculated as Tsol + 0.5 * Pmax (Tliq – Tsol), PCM specific heat calculated as cpsol + 0.5 (cpsol + cplaten), Latent heat temperature cplaten calculated as Tsol + Pmax (Tliq – Tsol), Latent heat cplaten, Temperature calculated as Tliq – 0.5 * (1 – Pmax)(Tliq – Tsol), PCM specific heat calculated as cpliq + 0.5 (cplaten + cpliq), Temperature Tliq, PCM specific heat of liquid phase cpliq.

The coordinates of selected points of temperature (x) and specific heat (y) in this method can be also calculated using Eqs. (3) and (4). 9 8 x1 > > > > > > > = < x2 ¼ x1 þ 0:5  Pmax  ðx5  x1 Þ > ð3Þ x3 ¼ x1 þ Pmax  ðx5  x1 Þ > > > > > x4 ¼ x5  0:5  ð1  Pmax Þ  ðx5  x1 Þ > > > ; : x5 9 8 y1 > > > > > > > = < y2 ¼ y1 þ 0:5  ðy1 þ y3 Þ > y3 ¼ cplaten > > > y ¼ y5 þ 0:5  ðy3 þ y5 Þ > > > > > ; : 4 y5

ð4Þ

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4 Examples of Simulation Tests The problem with describing PCM specific heat variation as a function of temperature in operating conditions shall be presented using the examples of simulation tests that were performed for 100 dm3 PCM storage tank. Three cases were examined. Each of analysed cases is characterised by the same values of PCM specific heat of solid and liquid phase of 18000 J/kgK and 28000 J/kgK respectively, and value of latent heat of 80000 J/kgK. The difference is the value of Pmax coefficient which is 0.5 in the first case, 0.25 in the second case and 0.75 in the third case. The value of temperature change from solid phase to transition phase is 318 K and from transition phase to liquid phase 325 K in every three cases. Figure 4 shows the correlation between PCM specific heat and its temperature for the value of Pmax coefficient of 0.5. The values of points whose coordinates are (x2, y2), (x3, y3), (x4, y4) should be noted while analysing the graph as they are starting and ending points of curves limiting the area of specific heat variations. The amount of energy which is possible to store in PCM tank can be calculated by integration over the area that is limited by the curve (Fig. 4) and multiplying by mass of phase change material when it changes temperature in transition phase. In this case, it is possible to store 3.332 kJ of energy in PCM tank. By changing the position of cplaten point with respect to PCM temperature (by moving it to the left – Pmax = 0.25) (Fig. 5), it is possible to store 3.643 kJ of energy. If the cplaten point is moved to the right – Pmax = 0.75 (Fig. 6) with respect to PCM temperature, it is possible to store only 3.016 kJ of energy in the same tank, which is about 18% of energy less compared to second case.

Fig. 4 The correlation between PCM specific heat and PCM temperature for Pmax = 0.5

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Fig. 5 The correlation between PCM specific heat and PCM temperature for Pmax = 0.25

Fig. 6 The correlation between PCM specific heat and PCM temperature for Pmax = 0.75

The results of presented analysis shows that heat capacity of PCM storage tank strongly depends on the position of cplaten point with respect to PCM temperature. If the potential position change of cplaten point with respect to PCM temperature is not considered, PCM storage tank may be often deeply discharged, and in consequence its service life will be significantly shortened.

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5 Summary and Conclusions Phase change materials (PCM) can store heat and cold for a long period of time. The number of deep charge and discharge cycles (complete change from solid to liquid) is a crucial parameter that has an impact on aging process of phase change material. Therefore, the monitoring of charge (discharge) rate (the control of energy stored in) of PCM storage tank is a very important issue when the system is in operation. Moreover, there is a difficulty with differences between PCM characteristics in operating conditions and those specified in catalogues. The solution of this problem is to develop an adaptive control system of PCM storage tank, which requires simulation tests based on PCM model that would be able to copy PCM characteristics in operating conditions. Thus, classical PCM model was modified by dividing the curve representing the correlation between specific heat and temperature of PCM into six parts. The modification gives the possibility to move the point of latent heat to the right or left with respect to PCM temperature. The results of presented simulation tests show that the position of latent heat point with respect to PCM temperature has a major impact on the amount of energy which can be stored in the tank (the same PCM mass). This means that if the simulation tests were performed using classical model of PCM whose characteristics would be defined by catalogue data, and the point of latent heat would be moved to the left with respect to PCM temperature in operating conditions, less energy would be stored in the tank compared to the information shown in catalogues. As a consequence of using classical model of PCM, PCM storage tank would be often deeply discharged and overcharged, which would significantly shorten service life of phase change material. The process of charging and discharging PCM storage tank can be optimised by implementing method that was presented in this article. Acknowledgements Presented research results were funded from the TESSe2b project, that is financially supported by the Horizon 2020 Research Innovation Action (RIA) of the European Commission, call EeB-Energy-efficient Buildings (Grant Agreement 680555).

References 1. J. Duffie, W. Beckman, Solar Energy Thermal Processes (Wiley, New York, 1974) 2. S. Arena, Modelling, design and analysis of innovative thermal energy storage systems using PCM for industrial processes, heat and power generation. Università degli Studi di Cagliari (2015)

Assessment of the Potential and Use of Renewable Energy Sources in the Municipality of Września Weronika Bojarska, Jacek Leśny and Monika Panfil

Abstract The following work presents the analysis of the potential of renewable energy sources in Września Municipality. Moreover, it gives an insight into the extent of their use and indicates some possibilities of their further development. The conducted analyses stipulate that this area has a great potential in terms of wind and biomass energy. As far as the former is concerned, the existing administrative limitations to all intents and purposes make it impossible to develop a high capacity wind power plant, whereas in the case of latter the barrier stems from inhabitants’ fear of the possible nuisance of biogas plants to be established. There is a great geothermal potential in the area where Września Municipality is located, however tapping into it would require more detailed research. It is useful that the city of Września has an extensive heating network, which would facilitate heat distribution coming from a geothermal facility. The remaining renewable energy sources such as solar batteries, photovoltaic cells, heat pumps and small windmills will probably be developed exclusively depending on individual entrepreneurship and financial resources of inhabitants. Keywords Renewable energy sources


Potential
Use
Municipality

W. Bojarska Graduate of Poznan University of Life Sciences, Piątkowska 94C, 60-649 Poznań, Poland J. Leśny (&) Meteorology Department, Faculty of Environmental Engineering and Landscape Planning, Poznan University of Life Sciences, 60-649 Poznan, Poland e-mail: [email protected] M. Panfil Department of Water Resources, Climatology and Environmental Management, Faculty of Environment Management and Agriculture, University of Warmia and Mazury in Olsztyn, 10-719 Olsztyn, Poland © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_79

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1 Introduction Reconciling the pace of economic development, which entails increased energy demand, with the obligation to prevent climate changes is considered one of the biggest problems of civilization. This issue is becoming increasingly important in the international politics. The European Union undertakes activities supporting enforcement of the Kyoto Protocol provisions in terms of the development of energy production from alternative energy sources [1, 7, 8]. The energy sector in Poland faces a huge challenge caused by decreasing coal resources, dependence on external supplies of resources and their price fluctuations, and also fulfilling the EU commitments [19]. According to the adopted energy package, i.e. 3  20%, Poland must increase the share of the energy coming from RES in the total energy consumption to 15% gross until 2020 [18]. It should be expected that the targets of the EU climate policy will tend to aim at further increase in RES use in the energy consumption in the following years [25, 28]. Rational use of particular energy sources constitutes one of the key components of sustainable development which will contribute to improving the condition of the environment, will lead to savings and more effective application of energy resources. Therefore, these energy sources are expected to be developed in the nearest future [20]. According to Danuta Huebner, an ex-European Commissioner for Regional Policy, local governments can play an important role in the development of energy from renewable sources because more and more investments are conducted both on the local and regional level. Moreover, local governments should insist on improving the condition of natural environment by decreasing emitted pollution and increasing energy safety in municipalities [31]. Currently Poland is divided into 2478 municipalities 3. One of them is the urban and rural Września Municipality [3]. As far as demography is concerned this municipality is considered to represent “Poland in a nutshell”, hence primary elections, both presidential and parliamentary, were often held here. Therefore, it has been assumed to be a good example of a municipality to be analysed in terms of its potential and development of renewable energy sources, because this development cannot take place without support and participation from the local community.

2 Characteristics of Września Municipality The surface of the municipality is 222 km2, 13 km2 of which are occupied by the city of Września (6% of the total municipality area), and countryside takes up 209 km2, which constitutes as much as 94% of the total surface area. In 2015 the municipality was inhabited by 45 952 people, 65% of whom lived in urban areas and 35% in rural areas.

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Fig. 1 Fluctuations in the population numbers of Września Municipality in 2011–2015 [5]

Września Municipality is an attractive place for settlement and building own house, which leads to the increase in the population numbers (see Fig. 1) [27]. The population of the municipality is also an important factor influencing its development and energy consumption [14]. According to the data from the Main Statistical Office [5], 15 995 flats were registered at the end of 2015 in Września Municipality, 11 350 of which in the city and 4 645 in rural areas. Their number is continually growing. It is predicted that by 2020 the number of flats will have increased up to nearly 17 000. This rise is connected with the population growth in the municipality. Every year 216 new flats on average appear here [15]. Thanks to a very good location near the main railway and motorway connecting Poznań with Warszawa, business activity in the municipality is steadily developing. According to the company registration numbers’ list, at the end of 2015 there were 5 695 economic entities registered in the municipality. The increase in the number of inhabitants, flats and economic development are the factors which entail growing demand on electrical energy. Table 1 presents energy consumption in 2010 and 2015 as well as the forecast for 2020 and 2030. Also the demand on heat energy is growing together with the need for electrical energy. W Table 2 presents the demand on energy needed to heat up the buildings in 2010, 2015, and also the forecast for 2020 and 2031.

Table 1 Calculations of the electrical energy demand for buildings in Września Municipality until 2031 r. [14] Balance of electricity demand

j.m.

2010

Residential buildings Public utility buildings Industrial buildings Total

kWh kWh kWh kWh

26 2 126 155

189 946 035 171

2015 280 285 910 475

27 3 130 161

846 196 032 076

2020 928 336 760 024

29 3 133 166

490 377 711 579

2031 208 976 550 734

32 3 137 174

517 706 792 016

280 976 200 456

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Table 2 Calculations of the heat energy demand for buildings in Września Municipality until 2031 [14] Balance of heat demand

j.m.

2010

Residential buildings Public utility buildings Industrial buildings Total

kWh kWh kWh kWh

196 11 44 251

419 130 194 744

2015 600 410 410 420

199 11 45 256

771 259 402 433

2020 440 820 500 760

201 11 46 258

069 259 246 575

2031 600 920 100 620

203 11 47 262

233 706 556 495

000 240 600 840

In rural areas of the municipality the heat energy is produced by using individual boiler rooms in households, whereas in the city heat energy is produced and distributed by Veolia Energia Poznań S.A, Facility East Września District, which uses heat networks. The total length of the heat network in the studied municipality is 26 245 lm. The biggest recipient of the heat energy provided by the above mentioned company is Września Housing Cooperative, which consumes almost 56% of the total heat energy produced. The second largest recipients are housing cooperatives in the city of Września, which use 18.2% of the heat energy, next are offices and institutions (8.5%) (see Fig. 2). In the buildings which have individual boiling rooms the prevailing fuels used are as follows: coal, coke, coal dust and wood. Additionally, heating oil or natural

Fig. 2 The structure of heat energy recipients in the municipality [14]

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gas are used for that purpose to a limited extent, the latter mostly in newly built houses. Unfortunately this leads to a huge increase of the so called low emission and negatively impacts air quality.

3 The Potential and Use of Renewable Energy Sources 3.1

Solar Energy

Both the studied municipality and the whole Poland, due to its location in the middle latitude, do not belong to the privileged areas in terms of the possible application of solar energy. Solar conditions in Poland are characterized by low variation and the analyzed area does not differ from the rest of the country in this respect [6, 30]. In the studied area, with an optimum setting of the surface absorbing sun rays one can obtain about 1.15 kWh/m2 of heat energy annually, while it is best to use this type of energy in the summer, whereas in another season it is good to meet energy demands by combining solar power with other energy sources [12, 13, 16]. It should be emphasized that installation of such facilities is quite expensive, therefore few people decide to use this technology without any financial support [14]. In comparison to previous years a significant increase in energy production from photovoltaic facilities has been observed. Technological progress can lead to a situation when the conditions of their development will soon become different, i.e. if the efficiency of photovoltaic cells increases, their price will drop [30]. Households in the municipality derive energy both from solar collectors installed on the buildings as well as from photovoltaic panels. However, no record of these facilities is kept [27]. Despite the fact there is a certain potential of this type of energy production, it is not predicted that the installed solar collectors might be developed here into any compact systems in the future. However, it is envisaged that in the following years the market of solar collectors will be still developing at a medium pace in a linear manner. So far the growth has been occurring without any substantial support of the state [30]. An example of an activity connected with obtaining energy from renewable sources is installing solar collectors on the building of the dormitory belonging to the School Complex and hospital (District Office) and also installing photovoltaic panels on the renovated building which will be occupied by the Special schools Complex and the Psychological and Pedagogical Counseling Centre.

Table 3 Wind power plants in Września Municipality

Localization

Power (MW)

Nadarzyce Grzybowo Kaczanowo Kaczanowo—2 electricity

0,85 0,85 0,85 1,2

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Wind Energy

The average wind velocity at the altitude of 10 m is about 3 m/s in the area of Września Municipality [2, 10, 17]. The frequency of winds which have the velocity from 4 to 9 m/s is 55% [16]. Thus, the area is quite favorable in terms of obtaining wind energy. Moreover, a big proportion of arable lands and a small proportion of protected areas indicate that Września Municipality has a great potential as regards wind energy production and use. According to the data obtained from Września Municipality and City Office there are five wind power plants in the analyzed area, which have the combined capacity of 3.75 MW (Table 3). Three of them with the combined total capacity of 2.55 MW are G58 type power plants from the Spanish company Gamesa. These turbines have high efficiency even by a relatively low wind velocity. The facilities are also equipped with a mechanism that limits the level of emitted noise as well as with innovative systems for controlling the functions of turbines. Nowadays the local development plans binding for Września Municipality do not provide for accommodating wind power plants. According to the materials obtained from the Municipality Office regarding administrative proceedings connected with wind power plants a decision was issued as to the location of a public investment facility, i.e. one wind power plant up to the height of 120 m and air blades span of up to 80 m in Otoczna. Whereas the proceedings regarding the decision about the development for foundation of one power plant of the capacity of up to 4.5 MW in Sobiesiernie were adjudicated. Also the decision regarding the development conditions for foundation of 4 turbines of 3 MW capacity each in Goniczki met with a rejection, the same as 1 turbine of 0.6 MW capacity in Sędziwojew. So far poor development of household power plants has been observed here, which is caused by legal, economic and technical limitations [4, 30].

3.3

Geothermal Energy

Września Municipality, which is located in the area of Mogilno-Łódź Basin, belongs to Szczecin and Łódź geothermal district characterized by a substantial abundance of geothermal waters and high values of heat flux. Września Municipality lies in the area where the temperature at the depth of 2000 m is about 72–80 °C. According to research results these areas have proper conditions for developing this type of energy [26]. However, the current state of analysis of geothermal waters in the studied area is insufficient to estimate the profitability of the investment connected with a possible location of geothermal heating facilities in this area [9].

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It is possible to use the geothermal energy and groundwater energy by using individual heat pumps for obtaining warm running water, water for heating buildings and air-conditioning. However, due to the lack of records of these installations in private buildings it is hard to estimate their numbers in the municipality.

3.4

Hydroelectric Power

In comparison with other regions, hydropower in Wielkopolska plays quite a small role because of the unfavorable water balance observable in this region [24]. One of the places in the municipality where hydroelectric power could be obtained is in the water basin Lipówka with the net capacity of 16.32 kW and the net potential of 143 thousand kWh [24]. It is hard to estimate the cost of constructing a hydroelectric facility and also the economic viability of such an investment.

3.5

Biomass and Biogas Energy

The analyzed area belongs to Śrem and Września agricultural and soil region [11, 17]. The analysis of land structure indicates typically agricultural character of the municipality whose area in 82% is occupied by farmland, almost 78% of which is arable land. They are dominated by a good wheat complex, which constitutes 35% of the lands. The second most common cereal is a very good rye complex, i.e. 22% of the arable land. Taking into consideration the plant production of the municipality the biggest share of crops consists of cereals. Also industrial crops, such as rape, agrimony and potatoes have a big share [16, 21–23, 29]. Due to a very big share of agricultural production and farmland in the structure of land use in Września Municipality, it can be concluded that this area has got very good conditions for using biomass for energetic purposes. The development of energy production from biomass is vital and opens new perspectives for this municipality although currently it is not a popular way of obtaining energy in the studied area. There are individual buildings with boilers using biomass but there is no record kept in terms of their numbers [16]. Taking into considerations biogas plants there are no facilities of this type in Września Municipality at the moment. However, in October 2013 a decision was issued allowing the construction of an investment known as Biomass Energy Production Facility. Currently this biogas plant is being constructed in the waste treatment plant and according to the information obtained from the manager of the plant the construction is soon supposed to be completed. The investment is conducted by a company from Poznań, i.e. Delta Power Rent. This is a mechanical and biological waste treatment plant which applies activated sludge to remove biogenic compounds. The range of the investment will involve using sewage sludge and other organic mass derived from agricultural activities as a renewable energy carrier

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(the following types of mass are planned to be used: whey, cereal straw, corn silage and potato pulp, mainly from local providers). Waste and sludge will undergo methane fermentation, and biogas will be produced in the process, which will become an energy source for the biogas heat plant providing heat and electric energy for Veolia and Enea. Basic elements of the planned investment should be as follows: a biogas plant, CHP units and facility for thermal biomass conversion. The project was financed by the National Fund for Environment Protection and Water Management and the scheduled cost of the investment is 45 ml PLN. The facility in Września has been designed according to the BAT (Best Available Technology). The designed biogas plant will not emit any notorious noises and it will improve environmental conditions around the waste treatment plant by covering digester chambers which are now open and exude unpleasant smells. The construction of the biogas plant was delayed by three years because of the protest issued by the Ecological Association of Friends of the Netze District Śmiłowo against the decision concerning the facility specificities. Additionally, in Goniczki a private investor planned on constructing an agricultural biogas plant with the capacity of 1 MW, but the project was met with public outcry because the inhabitants were afraid of the smell and nuisance connected with the biogas plant. On the other hand, in 2012 Września District Foreman gave a permission for the construction of a biogas agricultural plant with the capacity of 0.84 MW in Nowa Wieś Królewska village. Unfortunately no information has been found as to whether the investments will be implemented.

4 Discussion and Summary The economy of Września Municipality is of industrial and agricultural character. The industry is being developed in the city and its neighbouring areas, which is caused by an attractive location of the municipality. In the past it was a typically agricultural area and industry has become a unique added value. The consequence of this structure of the municipality accounts for its high potential of biomass energy and wind energy. This stems from a high proportion of arable land with good soils in the area as well as small forest surface and few protected areas which occupy merely 2.8% of the municipality and also the location in a very favorable wind energy zone. Unfortunately at the moment only one biogas plant is being constructed and even though the permission for the second one has already been issued, it is not known whether the investment is going to be implemented. The construction of the biogas plant raises social concerns and objections. It seems that a lot of educational work needs to be done or the protesters have to change personal opinions and believe that these investments are not a nuisance for the neighbourhood. In a sense one might say that Września Municipality was lucky that 5 wind power plants are active in its area. The current situation concerning selling energy obtained from RES, i.e. very low price of green certificates and administrative restrictions, dramatically decreases any chances of building new power plants.

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Perhaps a well-developed district heating network which powers many buildings in the city opens a good perspective for Września. It means that if the construction and exploitation of geothermal drillings turned out feasible, after a detailed examination, then the heat from this source could be easily put to use and serve the inhabitants. The remaining renewable energy sources such as solar collectors, photovoltaic cells, heat pumps and small wind mills will probably develop only depending on individual entrepreneurship and financial resources of the inhabitants.

References 1. K. Bańkowska, Pakiet klimatyczno-energetyczny determinantem przeobrażeń obszarów wiejskich. Roczniki Naukowe XVII(4), 16–20 (2015) 2. R. Farat, Atlas klimatu województwa wielkopolskiego. Instytut Meteorologii i Gospodarki Wodnej, Poznań (2004) 3. Główny Urząd Statystyczny, Mały Rocznik Statystyczny Polski. Warszawa (2017) 4. A. Górczewska, J. Leśny, Wind Power Engineering - Would a Well-Managed Investment Process Prevent Disputes Between the Local Authorities, the Investor and the Local Community?, in Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, ed. by K. Mudryk, S. Werle (Springer, Cham, 2018), pp. 405–412 5. GUS Homepage, http://bdl.stat.gov.pl. Accessed 15 Apr 2017 6. L.A. Hunt, L. Kuchar, C.J. Swanton, Estimation of solar radiation for use in crop modelling. Agric. Forest Meteorol. 91(3–4), 293–300 (1998) 7. Instytut Energetyki Odnawialnej, Możliwości wykorzystania odnawialnych źródeł energii w Polsce do roku 2020. Warszawa (2007) 8. Instytut Energetyki Odnawialnej, Określenie potencjału energetycznego regionów Polski w zakresie odnawialnych źródeł energii – wnioski dla Regionalnych Programów Operacyjnych na okres programowania 2014–2020 (Ministerstwo Rozwoju Regionalnego, Warszawa, 2011) 9. B. Kępińska, Przegląd stanu wykorzystania energii geotermalnej w Polsce w latach 2013-2015. Technika Poszukiwań Geologicznych Geotermia. Zrównoważony Rozwój 1, 19–35 (2016) 10. L. Kolendowicz, M. Taszarek, B. Czernecki, Convective and non-convective wind gusts in Poland, 2001–2015. Meteorol. Hydrol. Water Manage. 4(2), 15–21 (2016) 11. B. Kołodziej, M. Matyka, Odnawialne źródła energii. Rolnicze surowce energetyczne. Powszechne Wydawnictwo Rolnicze i Leśne, Poznań (2012) 12. J. Leśny, M. Panfil, M. Urbaniak, Influence of irradiance and irradiation on characteristic parameters for a solar air collector prototype. Sol. Energy 164, 224–230 (2018) 13. J. Leśny, M. Panfil, M. Urbaniak, R. Schefke, Examining technical solutions for a prototype of a solar-air collector. Technical Sci. 18(2), 125–135 (2015) 14. Miasto i Gmina Września, Aktualizacja projektu założeń do planu zaopatrzenia w ciepło, energię elektryczną i paliwa gazowe Miasta i Gminy Września. Września (2017) 15. Miasto i Gmina Września, Plan Gospodarki Niskoemisyjnej dla Miasta i Gminy Września. Września (2015) 16. Miasto i Gmina Września, Program ochrony środowiska dla Miasta i Gminy Września na lata 2014–2017 z perspektywą na lata 2018–2021. Września (2014) 17. Miasto i Gmina Września, Studium Uwarunkowań i Kierunków Zagospodarowania Przestrzennego dla Miasta i Gminy Września. Września (2017) 18. Ministerstwo Gospodarki, Krajowy plan działania w zakresie energii ze źródeł odnawialnych. Warszawa (2010)

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19. Ministerstwo Gospodarki, Polityka energetyczna Polski do 2030 roku. Warszawa (2009) 20. Ministerstwo Środowiska, Strategia rozwoju energetyki odnawialnej. Warszawa (2000) 21. M. Panfil, R. Jassal, C. Arevalo, R. Ketler, Z. Nesic, N. Grant, A. Black, J. Bhatti, D. Sidders, J. Leśny, Metody pomiaru strumieni dwutlenku węgla i pary wodnej na plantacji topoli. Przegląd Geofizyczny 2(57), 245–254 (2012) 22. Powiat Września Homepage, http://wrzesnia.powiat.pl/aktualnosci/bac-sie-biogazowni-czynie.html. Accessed 15 Nov 2016 23. Powiat Września, Program ochrony środowiska dla powiatu wrzesińskiego na lata 2013–2016 z uwzględnieniem perspektywy na lata 2017–2020. Września (2014) 24. Cz. Przybyła, R. Wojtkowiak, S. Gładysiak, J. Leśny, R. Schefke, K. Mrozik, Przegląd zasobów odnawialnych źródeł energii w województwie wielkopolskim. Urząd Marszałkowski Województwa Wielkopolskiego, Poznań (2007) 25. T. Skoczkowski, S. Bielecki, Ł. Baran, Odnawialne źródła energii – problemy i perspektywy rozwoju w Polsce. Przegląd elektrotechniczny 3(92), 190–195 (2016) 26. J. Sokołowski, K. Kempkiewicz, J. Kotyza, B. Ludwikowski, E. Pawlik, Metodyka i technologia uzyskiwania użytecznej energii geotermicznej z pojedynczego otworu wiertniczego. Instytut GSMiE PAN, Kraków (2000) 27. Strategia Rozwoju Miasta i Gminy Września na lata 2014–2020. Września (2014) 28. A. Węglarz, E. Winkowska, W. Wójcik, Gospodarka niskoemisyjna zaczyna się w gminie. Podręcznik dla polskich samorządów (adelphi research gemeinnützige GmbH, Berlin, 2015) 29. Wiadomości Wrzesińskie Homepage, http://old.wrzesnia.info.pl/tematyczne/samorzad/item/ 3083. Accessed 15 Apr 2017 30. Wielkopolska Agencja Zarządzania Energią, Strategia wzrostu efektywności energetycznej i rozwoju odnawialnych źródeł energii w Wielkopolsce na lata 2012–2020. Poznań (2012) 31. G. Wiśniewski, Z.M. Karaczun, Potencjał wykorzystania odnawialnych źródeł energii dla wzrostu bezpieczeństwa energetycznego w Europie. Heinrich-Böll-Stiftung. 21, Warszawa (2011)

Electric Cars as a Future Energy Accumulation System Józef Flizikowski, Andrzej Tomporowski, Weronika Kruszelnicka, Izabela Piasecka, Adam Mroziński and Robert Kasner

Abstract The aim of this study is to identify new opportunities for energy supply in Poland and in the world, on the basis of electric cars (EC). It was assumed that being connected to the local power systems, they can accumulate significant amounts of energy and effectively prevent from occurrence of electric power deficit. To achieve the above mentioned goals the problem has been formulated in the form of the following questions: what are the conditions and technical potentials for energy use in transport? What needs to be done in order to achieve the assumed satisfactory level of energy supply involving improving power availability in the Polish National Power System (NPS) and prosumer use of electric cars, for example in Poland? What are the examples of implementation of different sources of electricity into the electric power system? The innovation involves using mobile (car) prosumer electric power (Ee-Mobile) for battery charging, for example, they can use power from non-renewable sources of energy (RES) and/or renewable energy sources (RES). Environmental compatibility of various ways and means (according to their own evaluation methodologies), as technical solutions for

J. Flizikowski
A. Tomporowski
W. Kruszelnicka (&)
I. Piasecka
A. Mroziński
R. Kasner University of Science and Technology in Bydgoszcz, Al. Prof. S. Kaliskiego 7, 85-796 Bydgoszcz, Poland e-mail: [email protected] J. Flizikowski e-mail: [email protected] A. Tomporowski e-mail: [email protected] I. Piasecka e-mail: [email protected] A. Mroziński e-mail: [email protected] R. Kasner e-mail: [email protected]; [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_80

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charging and discharging rechargeable batteries for the car own purposes and for the purposes of the local energy systems in case of a deficit, was defined. Keywords Electric cars


Power deficit
Accumulation of energy

1 Introduction Use of electric cars in the system of electrical energy accumulation and power deficit tackling is a new issue consistent with the strategy of the EU intelligent development. The satisfactory level of electrical energy consumption/generation in Poland is estimated to be app. 150 TWh, as for technical conditions, the number of cars in Poland is defined to be more than 20 mln cars with the average power of 50 kW. The total power installed in automobiles (above 1000 Wh) is twenty five times higher than the power stored in the national power system (NPS *40 Wh), whereas, currently used cars with combustion engines and hybrid drives are absolutely not adjusted to perform prosumer tasks. Prime minister of the Republic of Poland, M. Morawiecki, thinks it is necessary to find a new, innovative solution to this problem, in Poland [1, 2]. According to Mr Morawiecki’s plan, the government of Poland intends to encourage development of such a system. One of actions to be taken is creation of a market for electric cars. The Ministry of Energy predicts that in 2025 (in 8 years), in Poland, there can be million, and ultimately, with progressive implementation of innovation, even 20 mln such vehicles. It is said that the total demand for energy of 1 mln cars is app. 4 TWh yearly, and potentially, in case of power deficit the electric power grid can be provided with the same amount of energy. Energy is also accumulated in parts of cars and can be recovered. The strength and energy tests methodology of the car elements were described in [3–5]. In Poland, electric cars, as prosumer tools, can in the future become an interesting source of electric power supply for the National Power System, at least 80 TWh yearly (4 TWhx20 mln automobiles) [1, 2]. Is this the right strategy? The goal of this study is to indicate a possibility of providing Poland with power supply safety and efficiency with the use of electric cars (EC). It is assumed that, by connecting them to local power supply systems, occurrence of electrical power deficits can be prevented more effectively. Thus, electrical cars can improve the availability of power in the local power grids of the National Power System.

2 The System Elements and Relations The concept of development, referred to as Morawiecki’s Plan, is fully consistent with the European policy which aims at supporting innovative solutions in economy. The priority of the government is to provide new industries with support

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by using results of research conducted in Polish research and development institutes [6]. The Polish Plan is based on three pillars. Flexibility and innovativeness of economy that are supposed to free the Polish economy from the constraint of medium profit and medium quality product. Industrialization 4G (fourth generation) is supposed to take into consideration all the elements of digital economy, and expansion and export are supposed to be a common goal of all the Middle and Eastern European countries which are too small to build their own economic growth on the basis of their domestic markets [6]. New possibilities that are provided by progress in motorization can connected with clean (mainly electrical) drives can be a real breakthrough. This, however, involves creating a new dedicated infrastructure prepared for cooperation with the local electric power grid [7]. Innovative sectors of economy, include: automotive industry: renewable energy sources, nanotechnologies, biotechnologies, information technologies power engineering technologies, quant engineering, spintronics, (mesoscopic electronics) and other high technology industries. One of the most attractive aspects of the contemporary innovation is a big variety of methods for perception, design, operation and use of standard transportation devices and energy machinery [8–12]. According to literature, in 2025, in Poland, the demand for heat and cold is estimated to be 240 TWh, the demand for fuel to be used by transportation— 210 TWh, for electrical energy—190 TWh. This data shows that gross demand for electrical energy in 2030 will increase by app. 54.2%, from the current level of 161 TWh up to 217.4 TWh. The highest increase is predicted in services (75%), in transportation (62%) and in households (34%). In industry the demand for electrical energy is predicted to be app. 28%, and in agriculture it will basically remain at the same level [13, 14]. The most interesting solutions concerning polymodality (multi functionality) of car operation involves providing a vehicle, and especially its drive, with a new role and a new function to be performed in different energy technologies, that is, micro combined heat and power systems (mCHP), stations for battery charging and generation of energy from batteries, conversion of solar energy into electrical or heat energy, etc. [8, 15].

3 Research Methodology Used for the System Development Finding a mathematical identity for the Car System for Energy Accumulation and Electric Power Deficit Tackling, (CSEAEPDT) is the research effect and it performs a useful service for the development, progress and global innovation of engineering objects. Some transformations apply to control of vehicle and machine operation effects, others regulate disturbances, pollution, waste amounts or waste products, and finally there are ones which compensate disruptions [16, 17]. Then the system of

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electric passenger cars and environmental development will be referred to as a set of operation potentials of elements E1, E2, … , Em, interrelated with each other according to a defined systemic concept, along with relations between these elements R1, R2, … , Rm, whereas, energy and information streams flow through the channels of these connections according to the action plan. Characteristics of ele and time H, as an ments and their relations are the functions of size of conditions W independent variable of development and time of dynamic process t. Besides, relations Ri also depend on control signals  SðH; tÞ:  H; tÞ E1 ¼ E1 ðW;

ð1Þ

 H; tÞ E2 ¼ E2 ðW;

ð2Þ

 H; tÞ Em ¼ Em ðW;

ð3Þ

R1 ¼ R1 ðW; s; H; tÞ

ð4Þ

R2 ¼ R2 ðW; s; H; tÞ

ð5Þ

Rn ¼ Rn ðW; s; H; tÞ

ð6Þ

The environmental-functional potentials of design, research, development, manufacturing, use, service, supply (including electrical energy charging, discharging, storing), recycling, processing and modification of the technical system of passenger cars—are resources, that is, all the external operation possibilities, according to the intended purpose which include: – – – –

Human resources PL(t) Technical potential PT(t), Energy-material potential PE−M(t), Control material PS(t).

The methodological character of the research and development on electric car systems as an empirical and induction discipline is not disturbed by the fact that it is a practical discipline with application specific research. Mathematical model, function of the (CSEAEPDT) operation potential:
 Pd ðtÞ ¼ U PL ðtÞ; PT ðtÞ; PE ðtÞ; PS ðtÞ

ð7Þ

and especially [11–13, 18]: Pd ðtÞ ¼ pd ðtÞ
Md ðtÞ
e Equation of the operation potential in time [t0, T] is as follows:

ð8Þ

Electric Cars as a Future Energy Accumulation System

ZT Pd ðTÞ ¼ Pd ðt0 Þ 

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ZT pEd ðtÞdt 

t0

ZT psd ðtÞdt þ

t0

pod ðtÞdt

ð9Þ

t0

where: Md ðtÞ—number of persons, cars, amount of energy, number of controllers that are involved in real processing, e—theoretical capabilities of humans, cars, amount of energy, number of controllers, pd ðtÞ—actual capabilities and responsibility level of humans, actual capabilities of cars, amount of energy, number of controllers, Pd ðto Þ—initial potential of the operation system, PEd ðtÞ—density of effectively used stream potential, psd ðtÞ—density of lost stream potential, Pod ðtÞ—density of recreated stream potential (or one obtained from the environment). Index of electric power excess (Knm) accumulated in cars versus the power installed in the National Electric Energy System. In order to estimate the excess of power in cars, an index of excess of domestic (global) power in vehicles was applied: Knm ¼

Pcp Pcs

ð10Þ

where Knm—index of global power excess in vehicles, -, Pcp—total power installed in engines of vehicles, GW, Pcs—total power installed in the considered domestic electricity system, GW. Index of environmental compliance (ηEKO) real technical conditions for solution to the problem connected with electric power accumulation and deficit in CSEAEPDT (idea of construction of devices and processes within the system), were determined in relation to theoretical service conditions: gEKO ¼

PAD ðtÞ pd ðtÞ
Md ðtÞ
e ¼ Pd Md
e

ð11Þ

where: ηEKO—index of environmental compliance of the energy accumulation solution and power deficit tackling concept, PA+D(t)—environment-system potential of the energy accumulation and operation of power deficit tackling concept,

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Pd—environment-system potential of theoretical, perfect energy accumulation and power deficit tackling, Md—theoretical number of persons, cars, energy amount, number of controllers determined for energy accumulation and power deficit tackling. Technical conditions WTj, including power accumulation and availability, depend on human creation (engineering). Creation, man’s vocation, (can be partly substituted by artificial cognitive-executive systems) involves discovering new, better ideas, solutions, actions, and technical conditions Wt(Ck(E, R, s, t): Ideas, concepts: transport means, methods, operation, e.g. electric car, front wheel battery drive from two electric motors, gearless drive without differential mechanism; undercarriage with battery compact, passively secured, quiet car body, etc. Structural features of the means: electric cars, machines, devices, installation of the car control, information, manufacture logistic and operation processes; geometric, material and dynamic form of components, their dimensions and tolerances, e.g., geometric of machine or car components; Process activities, parameters, component motion, material, product and relations of the process system (electric car manufacture, operation and maintenance, transportation) states of mechanization, automation, robotics, mechatronization, etc. To solve the problem, three spheres of technical conditions were considered WTj (W1–W3): W.1: Electric Cars. What technical conditions are to be provided for production of electric cars? In the Polish automotive industry innovative solutions are welcome. There is no initial or alternative state which would require competition. Many structural solutions, drive systems and results of electric car tests are available, e.g. tests of domestic MELEX cars, foreign -TESLA (whose production plant is under construction in China (investment for app. 9 billion $). W.2: Prosumer and the National Power Grid. Prosumer (consumer involved in co-creation and promotion of the national grid products, in simultaneous production and consumption of energy products and services). The program objective is: ‘supporting scattered, renewable energy sources (Part 2) Prosumer—refinancing line to be used for a purchase and montage of renewable energy sources installation —the aim is to limit or avoid CO2 emission by increasing energy production from renewable energy sources through a purchase and montage of small installations and micro-installations of renewable energy sources to produce electricity or heat for natural persons and communities or housing cooperatives. The program promotes prosumer attitudes (raising investors’ ecological and technological awareness), it also boosts development of the market of equipment suppliers and fitters increasing the number of job places in this sector. The program is a continuation and extension of the ended in 2014 program: ‘support for scattered, renewable energy sources (Part 3). Subsidies for partial repayment of bank credits for purchase and montage of solar collectors for individual persons and housing cooperatives’ (National Fund of Environment Protection and Water Management) [2].

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W.3: Management of electrical energy storage in automobiles. Technical conditions that assume cooperation and collaboration of car transportation system with the local power grid must be based primarily on reliable bi-directional power electronic converters and intelligent management platform [6, 11, 13]. Management of electric cars, within the system of electrical power availability, should take into consideration prosumer cooperation with the distribution network of the National Power Grid System e.g. by the use of active monitoring (intelligent, based on cognitive control) [18–20]. Environmental compliance was defined on the example of a passenger car (number of passengers n = 4, maximum speed pmax = 110 km h−1, range k = 300 km), for different technical conditions involved in the solution of the problem of electric power accumulation and deficit in CSEAEPDT, that is, methods and means (according to the methodology proposed in [8]), as an example of technical solutions to be used for battery charging and discharging for electric car own purposes and anti-deficit purposes of the local power grid (Table 1).

4 Example of Energy Accumulation for Power Availability Availability problem: to achieve the goal of the study a subproblem was formulated in the form of question: What conditions and technical potentials are needed for the satisfactory level of power consumption/generation to occur in the power supply system and car transportation (1–3) in order to improve power availability in the power grid and prosumer use of electrical cars in Poland? Example. The issue of technical potentials and conditions of an exemplary electrical energy production system with a power accumulator is shown in Fig. 1. Daily use of energy in an object, energy production through PV installation, energy supplied to the grid, energy taken from the grid and energy coming from energy accumulators, provide the possibility to reduce the share of power supply from the grid down to 8% (when an accumulator installation is remeasured it is possible to achieve 100% independence). This share depends on the installed system size PV + MEV + MEVi and the capacity of the mobile accumulator (number of electric cars used to improve availability of a power grid). Lithium- ion batteries based on a simple and efficient electrochemical mechanism were used for analysis. They do not need to be fully discharged, which was the case with the previous generation of nickel batteries. They well tolerate fast charging, and currently they are matchless in terms of the stored energy density (2.5–5 times more per mass unit than an acid-lead accumulator) and still show a certain development potential. The energy storage possibilities provided by particular technologies are shown in Fig. 2. The price offer of Tesla company (430 $ for kWh) or Schneider Electric (500 $ for kWh) can be an example of dynamic

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Table 1 Index of environmental compliance of different charging and discharging concepts for electric car batteries including local deficit threats No.

Energy-environment analysis and assessment of charging and discharging a battery of an electrical passenger car (number of passengers n = 4, maximum speed pmax = 110 km h−1, range k = 300 km):

Environmental compliance index (ηEKO)

1.

For technology involving using prosumer power from PV + national nower grid For technology involving using common power from a wind power plant + PV For technology involving using prosumer power from PV + biogas + wind power plant For technology involving using common power from wind power plant + national power grid For technology involving using prosumer supply in the national power grid For technology involving using common power from RES + the national power system For technology of power exclusively from the power grid. For technology of using power exclusively from photovoltaic cells For technology involving using a smart grid For technology involving using common power from wind power plant + electrical energy from biogas plant For technology involving using electric power from waste incineration plant For technology involving using power from another electrical vehicle For technology involving using own combustion engine power to charge a battery For technology involving using own diesel combustion engine power to charge batteries For technology involving using own combustion bioethanol engine to charge a battery For technology involving using own combustion biogas engine to charge a battery For technology involving using own combustion engine ZI to charge a battery

0.82

2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17.

0.82 0.80 0.79 0.79 0.78 0.76 0.72 0.72 0.71 0.68 0.66 0.66 0.63 0.63 0.59 0.56

development. The offer of Tesla involves energy storage equal to 7 and 10 kWh for households and 100 and 500 kWh for larger objects. Figure 3 shows an example of implementation of an electrical energy system with the use of different electrical energy sources. Innovativeness of such a solution is a mobile prosumer of electrical energy (Ee-Mobile), which as an accumulator, uses nonrenewable energy sources (NES) or/and renewable energy sources for battery charging, e.g. during energy supply shortage. Prosumer of an electrical

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Fig. 1 Scheme of electrical energy demand and supply in a household equipped with a system of energy generation and accumulation (own work)

Fig. 2 Possibility of energy accumulation of selected electricity battery, accumulator technologies (own research)

vehicle (PEV), generates energy accumulated in batteries (energy storage units) to the electrical energy system during the peak demand for power supply, threatened by power deficit. According to this solution the system is equipped with standard devices: main transformer (Mt), converters/controllers (C), system of control, regulation, compensation and supervision (SM), additional energy sources (AES), circuit breakers (Wx) and it well cooperates with the electrical energy system. An example of a modal solution. Use of electric power of all cars in the country, as a prosumer solution, has been estimated (Table 2) on the basis of an index of national (global) power excess in vehicles, according to dependence (11).

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Fig. 3 A scheme of a block of electric power system with mobile sources of electric energy: Ee-Mobile—mobile prosumer of electric energy; NES—nonrenewable Energy sources; RES— renewable energy sources; Tr—main; P—converter/controller; SM—control and supervision system; IZE—other energy sources; Wx—circuit breakers; SEE (EPS)—electric power system (own research)

Table 2 Power and relations: national power grid—drive systems in vehicles in Poland (own research) Number of vehicles, l, mln

Average power of drive system, Pśrp, kW

Total power of drive systems, Pcp, GW

Power in national power grid, Pes, GW

Index of power excess in vehicles, Knm

20

50

1000

40

25

Table 3 Comparison of the amount of Energy stored in accumulators of vehicles versus the demand for electric power from the national power grid (own research) Number of vehicles e-mobile, l, mln

Number of charges, llp, pcs

Average amount of electric power in accumulators for one charging, Aśrp, kWh

Total power of drive systems, Acp, GWh

Demand for energy in national power grid in 2015, Acs, TWh

Percentage share of e- mobile in yearly demand of the power grid, e, %

0,8 0,8 20 20

1 100 1 100

35 35 35 35

28 2800 700 70000

161 161 161 161

0.02 1.74 0.43 43.48

Tables 2 and 3 include an example of data for assessment of the proposed solution. The average value of electric power system of 50 kW and the average amount of energy stored in accumulators 35 kWh were accepted. According to Table 2 there is a 25-fold excess of power installed in car engines in Poland as

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compared to the power installed in the National Power Grid. 800 000 motors of electric cars provide 40 GW of electric power. If the average amount of energy stored in car batteries is *35 kWh, 800 000 vehicles (Ee-Mobile) can provide 28 GWh of electric energy for one time battery charging and for 20 mln cars this would be 700 GWh. Theoretically, for 100 charges/a year it is possible to achieve respectively 2.8 TWh and 70 TWh of electrical energy (Table 3). Many potential, hypothetical, solutions of electric cars utilization, in combination with SE have been considered such as: charging batteries with SEE; charging batteries with RES and SEE, or prosumer support for local grids of the National Power System. A balance model of energy-material operation efficiency Pdem ðTÞ, was proposed for an analysis of the possibilities involved in development of the Polish Energy System based on electric cars to be connected to the local electric power grids, according to the following general Eq. (10): ZT Pdem ðTÞ ¼ Pdem ðt0 Þ 

ZT pEdem ðtÞdt

t0



ZT psdem ðtÞdt þ

t0

podem ðtÞdt

ð12Þ

t0

For the concept of providing the power grid with prosumer support using photovoltaic systems for car battery charging, with an assumption, in a simplified way, for the model with the number of 800 000 electric cars cooperating with the local power grid and constant potential usefully and uselessly lost TR t0

pEdem ðtÞdt +

TR t0

psdem ðtÞdt = const, the potential for electrical energy demand can T

be reduced by þ R podem ðtÞdt ¼ 2:8 TWh, that is. from 161 TWh do 158.2 TWh. t0

This case can also be interpreted as power demand coverage of M 2.8 TWh: Pdem ðtÞ ¼ 158:2 þ 2:8 ¼ 161 TWh

ð13Þ

Whereas, for the maximum number of 20 mln electric cars to be used to support the national power grid, to 91 TWh: Pdem ðTÞ ¼ 91 þ 70 ¼ 161 TWh

ð14Þ

We assume a systematic increase in the number of electric vehicles which will enable to provide appropriate devices and infrastructure for electric cars charging, modernize or create suitable electric power infrastructure (distribution networks) and create legislation for the electro mobility market.

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5 Summary and Conclusions The solution to the problem involves indicating the possibility of providing electric power supply efficiency and reliability in Poland, on the example of Car Energy Accumulation and Electrical Power Deficit Tackling System, with the use of electric cars (EC), for a predicted number of 800000 to provide significant coverage of electrical energy deficit in the amount of 2.8 TWh. It was assumed that by connecting them to local electrical power systems, it is possible to tackle power and electrical energy deficit in a more effective manner. Electric cars can thus significantly support power availability of local power grids. The solution to the specified problem is to find an answer to the question as to what conditions and technical potentials of power technology and car transportation (W1-3) are to be provided, and what needs to be done for the postulated satisfactory level of power consumption/generation to occur in order to improve the power availability of the National Power System and encourage prosumer use of electric cars in Poland. To enable creation of innovative, ecologically compliant technical conditions (WTð117Þ , Table 1) to fit the concept of energy accumulation and power deficit prevention, that is, achieve the research goal, the following factors have been indicated: conditions of the investment localization, electric cars production volume in Poland (W1), current conditions of KSE particularly in Prosumer programs (W2), conditions of cooperation, collaboration, control, regulation and compensation basing on the rules of active monitoring (W3). These factors are essential for development of the power industry in Poland basing on electrical systems. It was assumed that by connecting them to local electric power systems it is easier to balance power demand and supply and prevent from its deficit occurrence. SE can significantly contribute to electric power and energy availability in local power grids of the national power grid. Active monitoring (W3) is used to provide control of availability of electric power stored in batteries of electric cars in the time of peak power demand or when the National Power Grid lacks power. A strategy for making decisions with regard to localization of a battery (Ee-Mobile), the level of its charge, day/night time, electric power price and the charging requirements needs to be used. Thanks to such a solution, the National Power Grid can be provided with better power supply reliability and availability. It guarantees that, even during heat waves, the system will not lack electric power.

References 1. Ministry of Energy of the Republic of Poland, National framework for the policy development of alternative fuels infrastructure. ATTACHMENTS, Warsaw (2016). (in Polish) 2. NFEP&WM, Priority Program NFEP&WM: Supporting distributed, renewable energy sources-Part 2 (2015). (in Polish)

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3. J. Flizikowski, W. Kruszelnicka, M. Michałowski, G. Szala, A. Tomporowski, Bulkhead door - critical evacuation states. Pol. Marit. Res. 24(1), 66–71 (2017) 4. P. Maćkowiak, B. Ligaj, Damage to adhesive single lap joint made of materials with different properties under static loading conditions, in Proceedings of the 23rd International Conference on Engineering Mechanics (Svratka, Czech Republic, 2017), pp. 598–601 5. A. Marczuk, J. Caban, P. Savinykh, N. Turubanov, D. Zyryanov, Maintenance research of a horizontal ribbon mixer. Eksploatacja i Niezawodnosc-Maintenance and Reliability 19(1), 121–125 (2017) 6. Polish Ministry of Development, Plan for responsible development, Warsaw (2016). (in Polish) 7. S. Habib, M. Kamran, U. Rashid, Impact analysis of vehicle-to-grid technology and charging strategies of electric vehicles on distribution networks – A review. J. Power Sources 277, 205–214 (2015) 8. J. Flizikowski, K. Bieliński, Technology and Energy Sources Monitoring: Control, Efficiency, and Optimization (IGI GLOBAL, USA, 2013) 9. A. Tomporowski, I. Piasecka, J. Flizikowski, R. Kasner, W. Kruszelnicka, A. Mroziński, K. Bieliński, Comparison analysis of blade life cycles of land-based and offshore wind power plants. Pol. Marit. Res. 25, 225–233 (2018) 10. M. Macko, J. Flizikowski, Z. Szczepański, K. Tyszczuk, G. Śmigielski, A. Mroziński, J. Czerniak, A. Tomporowski, CAD/CAE applications in mill’s design and investigation, in Proceedings of the 13th International Scientific Conference (Springer, Cham, 2016), pp. 343– 351 11. J. Guziński, M. Adamowicz, J. Kamiński, Electric vehicles - technology development. Charging systems and cooperation with the power grid. Autom. Electr. Disturb. 5(1), 71–84 (2014). (in Polish) 12. J. Flizikowski, T. Topoliński, M. Opielak, A. Tomporowski, A. Mroziński, Research and analysis of operating characteristics of energetic biomass mikronizer. Eksploatacja i Niezawodność 17, 19–26 (2015) 13. M. Jarnut, G. Benysek, Application of power electronics in SmartGrid and V2G technology (Vehicle to Grid). Electrotech. Rev. 86(6), 93–96 (2010). (in Polish) 14. J. Popczyk, M. Zygmanowski, J. Michalak, P. Kielan, M. Fice, The concept of prosumer energy microinstallation (PME) according to iLab EPRO, BŹEP Report (2013). (in Polish) 15. Y. Ma, T. Houghton, A. Cruden, D. Infield, Modeling the benefits of vehicle-to-grid technology to a power system. IEEE Trans. Power Syst. 27(2), 1012–1020 (2012) 16. B. Ligaj, Effect of stress ratio on the cumulative value of energy dissipation, Trans Tech Publications, Key Engineering Materials, vol. 598 (Zurich-Dyrnten, Switzerland, 2014), pp. 125–132 17. A. Marczuk, W. Misztal, T. Słowik, Chemical determinants of the use of recycled vehicle components. Przem. Chem. 94(10), 1867–1871 (2015) 18. J. Flizikowski, J. Sadkiewicz, A. Tomporowski, Functional characteristics of a six-roller mill for grainy or particle materials used in chemical and food industries. Przemysł Chemiczny 94, 69–75 (2015) 19. A. Tomporowski, J. Flizikowski, W. Kruszelnicka, A new concept of roller-plate mills. Przemysł Chemiczny 96, 1750–1755 (2017) 20. A. Tomporowski, J. Flizikowski, R. Kasner, W. Kruszelnicka, Environmental control of wind power technology. Rocznik Ochrona Środowiska 19, 694–714 (2018)

Optimisation Methods in Renewable Energy Sources Systems—Current Research Trends Sławomir Francik , Adrian Knapczyk , Artur Wójcik and Zbigniew Ślipek

Abstract The objective of the work was to determine the research trends and carry out a bibliometric analysis of publications concerning the application of the computational intelligence method in the research area renewable energy sources optimization. In this study the Scopus database has been used as a data source. Articles and conference papers published in the years 2011–2017 were analysed. The research consists of two research tasks: bibliometric quantitative analysis and bibliometric thematic analysis of publications. On the basis of the analyses conducted, one can state that: In years 2011–2017, the number of scientific publications regarding RES optimisation, indexed in the Scopus database, increased by 340%. However, it does not mean that optimisation studies become prevailing, since the number of RES-related publications increased as well (by 199%). A percentage share of publications concerning RES optimisation, in relation to all publications dedicated to RES, grew in years 2011–2017 by 177%. The authors of the highest number of publications (in the set of articles and conference materials searched, for years 2011–2017) were researchers from the USA, China, India and Italy. The majority of the studies described in the publications set concerned optimisation of solar energy and wind energy systems, often hybrid systems. For optimisation by means of artificial intelligence computational methods, algorithms belonging to a group of Evolutionary Computations (mainly Genetic Algorithms) and Swarm Intelligence (especially PSO) were applied most frequently. Neural networks and fuzzy systems were applied three times less frequently. The authors suggest new optimisation algorithms combining several artificial intelligence methods.




Keywords Optimization Renewable energy sources RES Computational intelligence Bibliometric analysis







S. Francik (&)
A. Knapczyk
A. Wójcik
Z. Ślipek Faculty of Production and Power Engineering, Department of Mechanical Engineering and Agrophysics, University of Agriculture in Krakow, Krakow ul Balicka 120, 30-149 Kraków, Poland e-mail: [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_81

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1 Introduction Growing requirements concerning protection of the natural environment and growing demand for energy have caused a higher interest in renewable energy sources (RES) using biomass energy, sun, wind, water, sea, and geothermal energy [1]. It has caused intense development of scientific studies on RES. In Poland, such studies relate mainly to using biomass energy [2–4], solar energy [5] and wind energy [6]. There are also studies concerning energy use of waste [7–13]. In recent years, due to popularisation of practical application of renewable energy sources [14, 15], some optimisation issues appeared; research studies have developed in the area of optimum RES application. Studies are run on applying more and more effective optimisation methods. Publications within this scope can be found in renowned scientific journals [16–19]. In order to use optimisation methods effectively, it is necessary to be aware of the current knowledge status in this area and development tendencies in studies concerning RES-related optimisation [16–19]. In recent years, optimization algorithms using artificial intelligence tools have been developing particularly fast. A comprehensive overview of methods of this type are included in the publication by Sinha and Chandel [18]. One of the ways of determining tendencies in a given area of science is bibliometric analysis [20], which is also applied in the area of RES [16, 17, 19]. In bibliometric analyses, WoS and/or Scopus databases are used most frequently, indexing publications with the highest scientific quality [16, 17].

2 Aim of the Study The objective of the work was to determine the research trends and carry out a bibliometric analysis of publications concerning the application of the computational intelligence method in the research area renewable energy sources optimization. In this study the Scopus database has been used as a data source. Articles and conference papers published in the years 2011–2017 were analyzed. The research consists of two research tasks: Task I

bibliometric quantitative analysis of publications regarding the optimization of processes occurring with the use of renewable energy sources. Task II bibliometric thematic analysis of publications describing the use of artificial computational intelligence methods to optimize issues related to RES.

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3 Materials and Methods The bibliometric quantitative analysis of a publication concerning the application of the optimization methods in the renewable energy sources (research task I) was curried out by the determination of the trend concerning changes in the number of scientific publications. A search in the Scopus database was carried out—criteria of searching: – – – – –

Keywords: “renewable energ*”, Title: “optimization”, Publication years: 2011–2017, Limit to Document type: Article and Conference Paper, Limit to Language: English.

Next, a quantitative analysis was conducted. It consisted in determining the number of searched publications (both articles and conference materials) published in particular years, identifying journals in which most publications were included and identifying the authors from which countries published the highest number of articles and conference materials. Another stage (research task II) was thematic analysis of the publications. Since in recent years the interest in optimisation methods belonging to artificial intelligence computational methods has been growing, a search was conducted in Scopus database to find publications dedicated to this topic. A search in the Scopus database was carried out again—criteria of searching: – Keywords: “renewable energ*”, – Title: “optimization”, – Title - Abstract - Keywords: “neur*” OR “swarm” OR “evolutionary” OR “fuzzy” OR “genetic” OR “bee” OR “bat” OR “ant”, – Publication years: 2011–2017, – Limit to Document type: Article and Conference Paper, – Limit to Language: English. From the set of documents found (articles and conference materials) publications not referring directly to RES or optimisation by means of artificial intelligence computational methods were removed. For each publication found, the analysis was conducted to identify which RES it concerns and what methods have been applied in it. On this basis, modified key words were identified for each document. The VOSviewer freewere was used to create maps of terms in the version of “thermic maps”. The modified keywords with the highest occurrence frequency are displayed in a bigger size font and they are placed in the “hot” area (yellow, orange, red range of colours). The modified keywords with the lower frequency of occurrence are presented in “colder” areas (green colour range) [20]. Maps were developed independently for articles and conference materials.

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4 Results As a result of searching in the Scopus database for the concepts “renewable energy sources” and “optimization” in the period 2011–2017, 1296 scientific publications (628 articles and 668 conference papers) were found—Fig. 1. In the following years the number of publications increased. In 2011 this number was 82 publications and in the 2017 it was 283. The percentage of publications concerning the optimization of renewable energy sources in relation to all scientific publications devoted to RES (their number also increased in subsequent years) was also calculated—Fig. 2. 300 Conference Paper 250

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The analysis of the percentage of publications in particular years also shows an upward trend, but it is not so big as in the case of the number of publications. The percentage of the number of publications, in 2011 year, was 4.3% and 8.2%, in 2015 year (in 2017 it decreased to 7.6%). The biggest number of articles was found in the journals titled: Energy (50), Applied Energy (47), Renewable Energy (44), Energy Conversion And Management (29), Energies (27) and Energy And Buildings (13)—in total number of 628 articles from 2011–2017. The biggest number of conference papers was published in Energy Procedia (48), Applied Mechanics And Materials (12) and Lecture Notes In Computer Science Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics (10)—in total number of 668 conference papers from 2011–2017. Identification of countries, from which scientists come from (affiliation shown in articles and conference papers) who carry out research on the optimization in RES (publications from 2011–2017) proved that majority of authors were scientists from United States (203 publications), China (170) and India (123)—Fig. 3. Further position was taken by Italy (92 publications), Germany (70), United Kingdom (55), Iran (54) and Canada (49). Authors from Malaysia and France published 47 documents each. There were only 7 publications of the Polish authors. For research task II, as a result of finding documents in Scopus database, a set of 335 scientific publications was collected. After review of their topical scope, 297 documents were classified for further analyses, which referred directly to RES and optimisation by means of artificial intelligence computational methods. Based on modified key words two thermal maps (for articles and for conference materials) of the frequency of particular terms occurrence were prepared by means of VOSviewer program (Fig. 4). Both in case of the articles and conference materials, topics related to optimising systems utilising solar energy (photovoltaics) and wind (turbines) prevailed. These are very often hybrid systems, which use several RES. Optimisation is most frequently performed by means of Swarm Intelligence (particularly PSO algorithm) and Evolutionary Computations. In the set of publications, the topic of optimising solar energy systems prevailed (149 documents) and wind energy (144 documents)—Fig. 5. 19 publications were dedicated to the topic of optimising systems utilising bio-energy. The lowest number of documents concerned optimisation of hydroenergy systems (10), ocean energy (6) and geothermal energy (1). A high number of publications regarded optimisation of RES hybrid systems (93 documents) and optimisation of network systems (smart/micro grid—63 publications). In the set of documents, most publications concerned using algorithms belonging to the group of Evolutionary Computations for optimisation (153 documents)—Fig. 5. Second most frequently used methods for optimisation were

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0 United States China India Italy Germany United Kingdom Iran Canada Malaysia France Spain Japan South Korea Egypt Saudi Arabia Netherlands Australia Denmark Indonesia Greece Portugal Taiwan Switzerland Sweden Singapore South Africa Tunisia Algeria Brazil Turkey Romania Pakistan Hong Kong Morocco Poland Other countries

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Fig. 5 Number of documents related to particular modified key words

Swarm Intelligence methods (134). In 38 publications, fuzzy system methods were used, and in 29, ANN. One can see a tendency to use hybrid algorithms, combining several CI methods for optimisation (23 documents). In the group of Evolutionary Computation methods, the highest number of publications regarded genetic algorithm (122). For example, genetic algorithm has been used to economically optimize the management of energy storage systems taking into account their degradation costs [21]. The aim of the proposed by authors methodology was the optimization of the usage profiles of energy storage systems and controllable generators in a power system. In 16 publications, Evolutionary Algorithms were used, while in 6 publications, Multi Objective Evolutionary Algorithms. Researchers implemented Multi-Objective Evolutionary Algorithm which supports to obtain the minimized energy usage cost and delay time for home appliance execution in the home area network [22]. The proposed approach gives an idea to maintain the load balancing mechanism, which helps to avoid the additional charges for consumers in the off-peak hours if threshold is applied for electrical appliance energy usage. One publication concerned utilising the Flower Pollination Algorithm, belonging to a group of Evolutionary Computation methods [23]. Authors developed a new evolutionary based optimization technique, namely hybrid Flower Pollination

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Algorithm and Simulated Annealing (FPA/SA) algorithm, in order to maximize reliability and minimize costs of PV/Wind/Battery system [23]. In the group of Swarm Intelligence methods, the highest number of publications regarded the PSO algorithm (109). One of the last publications describes the use of the Particle Swarm Optimization algorithm to select the hourly optimal load flow with renewable distributed generation integration under different operating conditions in the solar PV and wind power plants [24]. In 19 publications, the Ant Colony Optimization was applied, while in 5 publications, Bees Algorithms were used. Ant colony optimization (ACO) and artificial bee colony (ABC) algorithm have been used as a hybrid algorithm to optimize the placement and sizing of distributed energy resources (i.e., gas turbine, fuel cell, and wind energy) [25]. The main goal of optimization distributed energy resources have been to determine the best location and size of new energy sources with minimized specific objective functions. The objectives consisted of minimizing power losses, total emissions produced by substation and resources, total electrical energy cost, and improving the voltage stability. Also other methods were used to optimise RES, belonging to SI: Grey Wolf optimization and Firefly Algorithm (for each method 5 documents) [21], Bat Algorithm (4 documents) [26], Artificial Fish Swarm Algorithm (2 documents) [27]. Single publications was concerned Bacterial Foraging Algorithm [28], Whale Optimization [29] and Ant Lion Optimization [30]. In the group of Fuzzy Systems methods, fuzzy logic (15) and Fuzzy optimization (7) were used most frequently. For example, a fuzzy logic controller has been applied to optimization of performance characteristics of hybrid wind photovoltaic system with battery storage [31]. The Fuzzy logic controller takes the input from Solar (irradiation), Wind (speed), Power demand and the battery voltage which controls the respective subsystem and formulates into different operational modes of energy management. Whereas, fuzzy optimization has been used to develop a comprehensive decision model for sustainable design of biomass supply chains and district heating systems with thermal energy storages [32]. The main purpose was to find the optimum configuration of the supply chain and district heating systems to meet the heat demand of a particular locality. The model combines cost and service level objectives and accounts for biomass supply, material flow, capacity, demand and technical constraints. To optimise RES by means of artificial neural networks, mainly multi-layer one-directional neural networks were applied (9 documents). Mohandes used multilayer feedforward neural networks for forecasting global solar radiation [33]. The inputs to the networks were: month of the year, latitude, longitude, altitude, and sunshine duration, and the output was the monthly mean daily global solar radiation at the specified location. A neural network was trained using the standard backpropagation algorithm. Recurrent neural networks are also used, e.g. for prediction [34]. The authors developed and implemented a new recurrent neural network for optimization as applied to optimal operation of an electrical microgrid. The

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proposed neural network determines the optimal amount of power over a time horizon of one week for wind, solar, and battery systems.

5 Conclusions On the basis of the analyses conducted, one can state that: In years 2011–2017, the number of scientific publications regarding RES optimisation, indexed in the Scopus database, increased by 340%. However, it does not mean that optimisation studies become prevailing, since the number of RES-related publications increased as well (by 199%). A percentage share of publications concerning RES optimisation, in relation to all publications dedicated to RES, grew in years 2011–2017 by 177%. The authors of the highest number of publications (in the set of articles and conference materials searched, for years 2011–2017) were researchers from the USA, China, India and Italy. The majority of the studies described in the publications set concerned optimisation of solar energy and wind energy systems, often hybrid systems. For optimisation by means of artificial intelligence computational methods, algorithms belonging to a group of Evolutionary Computations (mainly Genetic Algorithms) and Swarm Intelligence (especially PSO) were applied most frequently. Neural networks and fuzzy systems were applied three times less frequently. The authors suggest new optimisation algorithms combining several artificial intelligence methods. Acknowledgment This work was supported by Higher Education in Poland (statutory activities DS-3600/WIPiE/2018, Faculty of Production and Power Engineering, University of Agriculture in Krakow).

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An Attempt to Use Kohonen Networks to Find Similarities in the Process of Convective Drying of Wood Biomass Szymon Głowacki, Weronika Tulej, Mariusz Sojak, Andrzej Bryś and Bartłomiej Pokojski

Abstract This work presents statistical analysis of dried wood biomass using Statistica Neural Networks 8.0. program. The goal of the work was to find similarities and possible difference between convective drying of different types of wood biomass. Wood of five different varieties, i.e. poplar, oak, acacia, willow and rosewood, in three different sizes of size reduction: 29-cm shoots, slices and chips was selected for the analysis using Kohonen networks. The material for experiments was dried in the following temperatures: 50, 60, 70 and 80 °C. The analysis of data related to the process of biomass drying using Kohonen network proved correct in the majority of cases. The interpretation of the topological map, developed as the final effect of the analysis, allowed for the assessment of its correctness at the level of 60%.







Keywords Kohonen network Wood biomass Convective drying Statistical analysis Topological map Neural networks










1 Introduction Kohonen networks algorithm used for the analysis of experiments presented in this work is widely used in many fields. Despite being very simple, its possibilities are almost unlimited [1]. So far, the advantages of this type of neural networks have been used in numerous domains of life, i.a. for the analysis of the number of passengers. Kohonen networks were used to analyse images from monitoring cameras installed at the underground stations, and specify the required number of carriages. S. Głowacki (&)
W. Tulej
M. Sojak
A. Bryś
B. Pokojski Department of Fundamental Engineering, Warsaw University of Life Sciences (SGGW), Warsaw, Poland e-mail: [email protected] W. Tulej e-mail: [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_82

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Kohonen networks were also used in other programs and projects such as speech synthesizers, writing recognition or graphical editors. Due to so rich and varied applications of this neural network algorithm, it was selected for the analysis of the drying process of biomass [2], as it seemed that the application of Kohonen network was both the best and the simplest method of the optimization of the process, which is indispensible in the technology of obtaining wood biomass-derived energy [3, 4]. The goal of this work is the indication of similarities and possible differences between convective drying of different types of wood biomass. Based on available results of drying research conducted at the Faculty of Production Engineering of the Warsaw University of Life Sciences (SGGW), wood of five different Varieties was selected, i.e. poplar, oak, acacia, willow and rosewood, in three different sizes of size reduction: 29 cm shoots, slices and chips was selected for the analysis using Kohonen networks. The material for experiments was dried in the following temperatures of the drying agent: 50, 60, 70 and 80 °C. This work involved analysis of the data obtained during the convective drying process using Statistica Neural Networks 8.0 program, and the obtained results were presented in the form of a topographical map. It is a typical method of presentation of results in the analysis performed using Kohonen networks. The obtained map allowed for the determination of similarities in the process of drying different types of biomass for the same period of time and at the same drying temperature. Please note that the first paragraph of a section or subsection is not indented. The first paragraphs that follows a table, figure, equation etc. does not have an indent, either. Subsequent paragraphs, however, are indented.

2 Methodology of Research The analysis involved the best possible presentation of the obtained data in one table, indicating the most significant features of each type of drying. The research material was divided into 60 cases. The examinations of wood biomass involved moisture, susceptibility to convective drying, and differences in size reduction. The following types of wood biomass were analysed: oak, willow, poplar, acacia and rosewood. Each of these plants has different characteristics, which determines its behavior in the process of drying at different temperatures. The table of data was analysed using Kohonen networks, which are self-learning networks, i.e. networks that learn exclusively by analysing the input data, and whose internal structure and unknown relations hidden in the structure decide about the final result of classification and the final functioning of the network. It was assumed that in Kohonen network, individual neurons’ task was to identify and recognize different types of individual clusters of data. Data clusters should be understood as types of biomass identified in the process of self-learning, grouped in

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closely located places on the topological map [5]. This property of Kohonen networks is extremely useful for the assessment and analysis of data. The application of Kohonen networks results in the development of the topological map with tags indicating respective types of size reduction, drying temperatures and wood varieties [6]. Kohonen networks consist of two layers: the input layer, in this case it is a table of data that contains characteristic features of individual tags, and the output layer, used to present the classification in the form of a topological map. The distinguishing feature of the output layer of the Kohonen network is its two dimensionality. It means that the results of grouping are presented on the map that consists of only two variables, e.g. X and Y. Neurons of this layer are not interconnected, but for the convenience of results interpretation, let us imagine that the neurons are arranged in adjoining columns, and form a regular grid. The results of grouping are nodes of this grid. The visualization allows for observing places of cluster formation corresponding to the highest frequency of occurrence of similar types of biomass on the map [7]. High frequency of similarities, so called wins, indicates the centres of clusters on the topological map, while neurons with the number of wins equal zero indicate inaccurate learning. The following assumption is made, as the neurons with the number of wins equal zero are not used at all. It means that the network does not sufficiently utilize all available resources. Clusters with the number of wins equal zero are then arranged quite randomly [8]. During presentation of individual neurons, each of them indicates its similarity to the input data. The information is presented graphically, mainly using a filled black square. A square on the map generated in Statistica Neural Networks represents greater similarity, and the strongest (winner) neuron is framed. By testing the cases of biomass drying on the basis of the method of activation, numerous groups of interconnected neurons may be observed [9]. In this work, they indicate a similar course of the drying process. After the correct assignment of tags, the values may be read from the topological map, by interpreting data available in individual clusters found by individual neurons. In the case of biomass, if two tags have the same position on the topological map, the result is obtained by reading the tags, e.g. if tags v30 and v6 have the same position, we read their value. Tag v30 means oak-slices-60, and tag v6 means willow-slices-60, which indicates that for the slices of oak and willow the process of drying at the temperature of 60 °C is very similar. If we additionally take into account that fir has the same density as the two above mentioned wood varieties (oak and willow), we can safely assume that fir slices will behave in a similar way during drying at the temperature of 60 °C [10]. The existing data were obtained as a result of drying of chips, slices and shoots of the five above mentioned wood varieties. The process was conducted in four different drying temperatures (50, 60, 70 and 80 °C) for a specified period of time. The biomass was dried using the convection method in a flow dryer. The data obtained were analyzed, followed by the selection of masses and water contents for each type of biomass for each of the drying temperatures. The experiments results are presented in Table 1 (an example) that contains measurements for oak, together with a short description of the obtained results.

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Table 1 Measurements for drying oak at the temperature of 80 °C. Drying temperature 80 °C Time Slices Water sample content weight slices (kg/ (g) kg)

Chips sample weight (g)

Water content chips (kg/ kg)

Shoots sample weight (g)

Water content shoots (kg/ kg)

0 15 30 45 60 90 120 150 180 210 240 300 360 420 480 540 600

703.81 664.46 620.46 594.17 556.84 513.81 487.1 469.98 463.22 461.31 460.37 459.75 459.05 458.75 458.62 458.59 458.55

0.765 0.666 0.556 0.49 0.396 0.289 0.222 0.179 0.162 0.157 0.154 0.153 0.151 0.15 0.15 0.15 0.149

821.99 817.03 811.49 808.44 803.58 792.82 782.8 774.3 764.33 755.76 749.22 735.19 723.65 711.35 700 690.08 681.67

0.765 0.754 0.742 0.736 0.726 0.702 0.681 0.663 0.641 0.623 0.609 0.579 0.554 0.527 0.503 0.482 0.464

703.33 669.08 627.95 609.95 584.88 539.19 500.38 477.59 460.57 452.26 448.99 446.42 445.53 444.86 444.54 444.53 444.47

0.765 0.679 0.576 0.531 0.468 0.353 0.256 0.198 0.156 0.135 0.127 0.12 0.118 0.116 0.116 0.116 0.115

The measurements were the results of drying in the temperature of 80 °C. The measurements were taken for the period of 600 min. The dry mass was determined, and amounted to 393.73 g for slices, 385.01 g for chips and 379 g for shoots. However, great efficiency of drying shoots could be observed, as the mass decreased by 140.32 g of water. Great decrease in mass was also recorded for slices and chips, and amounted to 258.86 g of water 245.26 g of water, respectively. Analyzing all the results, it is necessary to consider the fact that the differences in the biomass grammages have similar values, and are calculated as the ratio of the initial mass to the mass at the end of the drying process. It is a significant factor, as the differences in time of measurements for respective drying temperatures were as follows: 2040 min for the temperature of 50 °C, 1440 min for 60 °C, 720 min for 70 °C, and 600 min for 80 °C. Similar differences also occur in the process of drying of other materials. The example of oak shows the method of presentation of the results for the analysis. The obtained measurements were used to develop a tool for statistical analysis of wood biomass drying. In order to standardize the data analysed by the program, representative measurements were selected around the 300th minute of drying. The neural network was generated in Statistica Neural Networks 8.0 program. It is a universal, integrated system for statistical data analysis, graphs generation,

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databases manipulation, data transformation and application development. It contains a wide range of sophisticated analytical procedures used in scientific research, business and technology as well as data mining. One of the most important and unique options offered by the application is the customization of the program’s environment to the requirements of the currently performed task and user’s preferences [11], which allowed for the application of the program for the analysis of data described above. The data were selected and summed up in the table presented below (Table 2). All data were collected in the 300th minute of the drying process, due to the necessity to standardize the drying time in order to obtain a neural network of better quality. In the second column, each type of biomass was assigned its own

Table 2 Sample data used for the analysis using Kohonen networks No

Type

1 w 2 w 3 w 4 w 5 w 6 w 7 w 8 w 9 w 10 w 11 w 12 w 13 a 14 a 15 a 16 a 17 a 18 a 19 a 20 a 21 a 22 a 23 a 24 a 25 o 26 o Source Own

Density kg/m3 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 850 850 850 850 850 850 850 850 850 850 850 850 1000 1000 elaboration

Size reduction

d.s.

Water content

Mass g

Tag

Biomass

c c c c s s s s sh sh sh sh c c c c s s s s sh sh sh sh c c

301.32 304.35 301.1 298.4 302.93 303.37 303.14 301.85 301.33 303.83 303.29 296.42 383.08 383.38 383.38 383.38 377.2 377.2 377.2 377.2 377.16 377.16 377.16 377.16 385.01 385.01

0.1770 0.1415 0.0887 0.0677 0.0660 0.0460 0.0430 0.0180 0.8635 0.7939 0.6903 0.4686 0.0544 0.0181 0.0132 0.0784 0.1211 0.0760 0.0166 0.0312 0.5879 0.5397 0.4410 0.2513 0.2722 0.2202

354.66 347.43 327.81 318.6 322.93 317.32 316.19 307.29 561.52 545.03 512.66 435.31 386.95 379.51 376.67 265.25 414.36 399.28 377.36 382.45 584.24 573.8 535.67 463.67 487.42 479.95

v1 v2 v3 v4 v5 v6 v7 v8 v9 v10 v11 v12 v13 v14 v15 v16 v17 v18 v19 v20 v21 v22 v23 v24 v25 v26

willow - chips - 50′ willow - chips - 60′ willow - chips - 70′ willow - chips - 80′ willow - slices - 50′ willow - slices - 60′ willow - slices - 70′ willow - slices - 80′ willow- shoots - 50′ willow- shoots - 60′ willow- shoots - 70′ willow- shoots - 80′ acacia - chips - 50′ acacia - chips - 60′ acacia - chips - 70′ acacia - chips - 80′ acacia - slices - 50′ acacia - slices - 60′ acacia - slices - 70′ acacia - slices - 80′ acacia - shoots - 50′ acacia - shoots - 60′ acacia - shoots - 70′ acacia - shoots - 80′ oak - chips - 50′ oak - chips - 60′

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abbreviation: W—for willow, A—for acacia, O—oak, P—for poplar, and R—for rosewood. The third column contains wood varieties, which were assigned their average densities. Poplar and acacia, whose densities range between 800 kg/m3 and 900 kg/m3 were assigned the average value of 850 kg/m3. The average density of willow and oak were determined at the level of 1000 kg/m3, and rosewood— 915 kg/m3. All densities are assigned to freshly cut down trees. The fourth column contains the type of biomass size reduction: c—chips, s—slices and sh—shoots. Column 5 contains information about the value of dry substance, while columns 6 and 7 contain water content and the mass of biomass in the 300th minute of drying, respectively. Column 8 contains the information about the tag, which is used for identification of the appropriate type of biomass on the topological map, and column 9 contains the information about the type of biomass, size reduction and drying temperature is assigned to each tag.

3 The Results and Analysis of the Examinations Tags in the first column (VAR1) were set as w, a, r, p and o for willow, acacia, rosewood, poplar and oak, respectively. VAR2 column did not require any tags as it only contained numeric value. In the column VAR3 the respective tags were c, s and sh for chips, slices, and shoots. The next three columns also contained numeric data, and did not require tag pre-assignment. The last column containing tags v1, v2, v3 …. v60, presented the output values. It means that each row is assigned one of tags vn, and the final data on the topological map will be labelled accordingly. The next stage of the analysis was Kohonen network generation using the obtained data. The information about the input and output columns (in this case 6 input columns and one output column is contained in Create network window. The next stage was the selection of the type of network in Type window (Kohonen network was selected). Layer 2 (the number of nest on the topological map) was set at the level of 49 square units, and the length of the side of the map’s square at the level of 7 units. Optionally, Advise option may be selected, which helps to select so called Convents—denoting the ranges of properties of each table. The value of variables is automatically set by the program. They are visible in the window Inputs (input data), i.e. the variables that will be used by the program to generate the topological map, and Outputs (output variables), i.e. tags, which will appear on the topological map as the result. The Kohonen network is displayed in the form of 6 input data recalculated and shown in the result network, as presented below. After selecting the option Create, the program presents graphical image of the Kohonen network, with 6 input variables. They were presented by the program in the form of arrows on the left hand side of the diagram. The program also created the image of output variables in the form of a square with the side equal 7 units, which contained 49 nodes. The image of the network helps the used understand the

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mechanism of the program operation. It may be noticed that each input node is connected with each of the 49 output nodes. It means that the network analyses all input variables, one by one, and then compares them, which is possible due to the fact that each element of the output variables is assigned the tag after their grouping. The network describes their location on the topological map. A network created as described above must be trained. A graph of training correctness and the trainer must be selected for that purpose. The graph illustrating the process of learning shows the trainer irregularities resulting from differences in data. If the graph is straight line, it means that the network’s training is sufficient and the training process may be finished. Kohonen training window is used for starting the process of training. In the first stage, the training width is selected, in this case, at the level of 0.6. The network neighbourhood is set at the level equal 5, and it specifies the grouping power of neurons close to one another. In subsequent stages of training, the training width is decreased to 0.1, and the neighbourhood decreases from level 5 to 1. This allows for initiating primary learning, followed by refining the value of training with the decreased parameters. The number of epochs is set at the level of 100, which results in the graph showing the training process with the greatest possible accuracy. The next stage is verification of the accuracy of tag assignment (classification) following the training. Classification statistics in the program shows the quality of the assigned data. The printscreen also shows clearly the training error graph. The first period of learning (quire ‘jagged’) shows the result of training with the values of the parameters width and neighbourhood set at their highest levels. It also shows how the process of learning stabilized after decreasing the values of the above parameters, which resulted in low deviations from the norm. Classification statistics is divided into two basic sections. The first contains the tags and the information whether they were assigned correctly, incorrectly, or whether they were not assigned at all, while the second shows the location of each tag on the topological map. The example presented in Fig. 1 shows that the first three tags were not assigned. The network is correct when at least half of tags are correctly assigned to the position on the topological map. The tab Class Labeling of Radial Units shows the user the exact position of each case in relation to the topological map. As shown in Fig. 1, it may be noticed that the tag v49 is located in the top left corner of the map, i.e. the position 1,1. It is, however, necessary to remember that the final results may be different from the results presented above, as the presented images show the process of learning. The process was repeated more than ten times, until the satisfactory level of correctly assigned cases was achieved. This stage is the final stage of the training process. This concise description of network generation and its training illustrates its method of operation, and the calculations, which the data were subjected to repeatedly, it order to be presented as reliable. The important element of the analysis using Kohonen network is the correct reading of the topological map. Summed up results, placed in the appropriate cell

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Fig. 1 Class labeling Source Own elaboration

Table 3 Reading of the topological map v1, v2, v3, v4, v25, v26, v27, v28 v13, v14, v15, v16 v21, v22, v23, v24 v9, v10, v11, v12, v33, v34, v35, v36 Source Own elaboration

v49, v50, v51, v52 v37 v38, v39, v40 v45, v46, v47, 48

v17, v20 v41, v44 v53, v58,

v18, v19, v42, v43,

v29, v30, v31, v32 v5, v6, v7, v8

v54 v59, v60

v55, v56 v57

are shown in Table 3, which presents the distribution of clusters on the topological map, where 60 tags formed 16 data clusters. To provide an example, the two most numerous clusters of the cases were described. The first one, located in the top left corner, includes eight different types and size-reduction of biomasses, i.e. v1—willow, chips, dried at the temperature of 50° C, v2—willow, chips, dried at the temperature of 60 °C, v3—willow, chips, dried at the temperature of 70 °C, v4—willow, chips, dried at the temperature of 80°, as well as v25, v26, v27 and v28 oak, chips, dried at respective temperatures of 50 °C, 60 °C, 70 °C and 80 °C. The second most numerous nest after 1,1 is located at the position 7,1. It contains tags from v9 to v12, and from v33 to v36, with the first group being willow

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shoots dried at the temperatures in the range between 50 and 80 °C, and the second one including oak shoots dried in the same temperature range.

4 Summary Statistical analysis of the drying process of wood biomass is correct in the majority of cases. Reading of the topological map, which is the final effect of the analysis, allowed for the assessment of its correctness at the level of 60%. Although certain nest were not assigned any tags, it was possible to observe tag clusters in others, with equal distances from each other. It would also be useful to conduct the research using a greater dataset. Analysing the results, certain regularities may be observed, which provide valuable information for wood biomass drying industry. Certain wood varieties have similar drying profile. The process of willow and oak chips proved to be similar (cluster 1,1). Therefore, their simultaneous and equally efficient course may be used to optimize the process of drying. Moreover, immediate neighbour clusters 1,7 and 3,7 confirm this thesis, proving that willow and oak slices also have similar properties as regards drying. This is also true of willow and oak shoots, as the parameters of their drying process are also in one cluster (7,1). The topological map also allows for making a highly probable assumption that, for different wood varieties with similar parameters of drying and size-reduction, as well as similar properties will behave in a similar way during drying. This observation will certainly facilitate planning and increase the efficiency of the convective process of drying different types of wood biomass. The method of computer data analysis presented in this work has a widespread application in drying other biological products. Enrichment of conclusions based on the analysis presented in this work by further research on a larger set of data, will directly contribute to enlargement of the topological map, and, consequently, to filling the gaps in the distribution of clusters and increasing its efficiency by more than ten or even over twenty percent, thus transforming into a self-organizing system.

References 1. L. Fausett, Fundamentals of Neural Networks (Prentice Hall, New York, 1994) 2. B. Janowski, Pattern Recognition and Neural Networks (Warszawa 2006) 3. A. Gendek, Sz. Głowacki, Convectional drying of chips for energy purposes. Annals of Warsaw University of Life Sciences - SGGW. Agriculture No 53 (Agricultural and Forest Engineering) (2009), pp. 67–72 4. Sz. Głowacki, A. Gendek, Application of forced drying methods in preparation of forest chips for energy purposes. Annals of Warsaw University of Life Sciences – SGGW. Agriculture 58 (Agricultural and Forest Engineering) (2011), pp. 29–34

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5. B.S. Everitt, S. Landau, M. Leese, Cluster Analysis (Oxford University Press, London, 2001) 6. S. Haykin, Neural Networks: A Comprehensive Foundation (Macmillan Publishing, New York, 1994) 7. V. Vapnik, The Nature of Statistical Learning Theory (Springer 1995) 8. R. Tadeusiewicz, Siecie Neuronowe (Akademicka Oficyna Wydawnicza, Warszawa, 1993) 9. B.D. Ripley, Pattern Recognition and Neural Network (Cambridge University Press, Cambridge, 1996) 10. M. Krzyśko, Analiza dyskryminacyjna (WNT, Warszawa, 1990) 11. R. Tadeusiewicz, Elementarne wprowadzenie do sieci neuronowych z przykładowymi programami (Akademicka Oficyna Wydawnicza, Warszawa, 1998)

Application of Methods for Scheduling Tasks in the Production of Biofuels Adrian Knapczyk , Sławomir Francik , Artur Wójcik and Zbigniew Ślipek

Abstract This work analyses possibilities of applying task prioritization methods in the production of biofuels, based on bibliometric analysis. The results of the bibliometric analysis have shown that studies on applying task prioritization methods in biofuels production have not been conducted on a large scale so far (only 96 indexed works have been published in the Scopus database). In the documents being analysed, the application of prioritization methods concerned mainly production (raw material optimisation and processing, classical and new production technologies, cost reduction, environmental impact reduction, and the like) and logistics (supply chain optimisation, including planting, harvesting, transport, storage, distribution etc.). Mainly advanced task prioritisation methods have been used: MILP (mixed-integer linear programming), Linear Programming Model, Stochastic Sequential Programming and Multi-Objective Genetic Algorithm.








Keywords Scheduling problem Scheduling application Bibliometric analysis Research topic Scientometric Literature review VOS viewer










1 Introduction Renewable Energy Sources become more and more important. It has to do with the change in regulations and world tendencies. One of the main renewable energy sources is biofuels. Biofuels can be divided into solid, liquid and gaseous (Fig. 1). In terms of generation, they show features of both agricultural production (growing of energy plants, harvesting of raw materials etc.) and industrial production (raw material processing). Numerous studies are conducted on determining A. Knapczyk (&)
S. Francik
A. Wójcik
Z. Ślipek Faculty of Production and Power Engineering, Department of Mechanical Engineering and Agrophysics, University of Agriculture in Krakow, Krakow ul. Balicka 120, 30-149 Kraków, Poland e-mail: [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_83

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Fig. 1 Classification of biofuels [11]

physico-chemical properties of various raw materials for producing biofuels [1, 2], as well as the possibility of their processing for energy purposes [3–6]. The production of biofuels from waste is becoming more important [7–10]. That is why, it is necessary to set main directions of studies within the scope of biofuels production in terms of indicating decision making issues, in which task prioritisation is used. The issue of task prioritisation is a current optimisation problem in different industries (e.g. production engineering, agricultural engineering, logistics and the like). To solve task prioritisation issues, different computing tools are applied (e.g. operational study methods and artificial intelligence). It relates to the nature of various areas. There is a tendency to develop prioritisation algorithms for particular groups of issues/problems with similar features and a similar complexity level. Such procedure enables to apply different prioritisation methods to particular problem groups, or different parts of a larger system [12]. Prioritisation methods can be divided into simple and complex ones (Fig. 2). Within simple ones, we can distinguish priority rules. Priority rules, in turn, can be divided, due to the number of factors taken into account, into one-attribute and multi-attribute ones. It should be noted that multi-attribute rules can be derived from the combination of multi-attribute rules. On the other hand, advanced prioritisation methods can be divided into classical ones, in which advanced mathematical models are used (e.g. simulated annealing, tabu search or distributed search) and those using artificial intelligence (e.g. artificial neural networks, genetic algorithms or fuzzy systems) [13]. A large number of the existing methods and new methods being developed cause that the decision to select a prioritisation technique becomes difficult. It is necessary to continuously update knowledge on the current status of research and

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Scheduling methods

Simple (Static)

Advanced (Dynamic)

Priority rules

Univariate

Multifactorial

FIFO

MOR

LIFO

LOR

FEFO

EDD

SPT LPT

Classic

EMODD

Using AI

SA

EC

TS

ANN

AMS

FS

S/RPT+SPT

SS

SI

PT+WINQ

ect.

ect.

CR+SPT S/OPN

PT+WINQ ect.

Legend: FIFO (First in first out), LIFO (Last in first out), FEFO (First expired first out), SPT (Shortest procesing time), LPT (Longest processing time), MOR (Most operations remaining), LOR (Least operations remaining), EDD (Earliest due date), EMODD (Earlies modified operational due date), CR+SPT (Critical ratio + the shortest process time), S/OPN (minimum Slack time per remaining Operation), S/RPT+SPT (Slack per remaining process time + the shortest process time), PT+WINQ (Process time + work in the next queue), PT+PW (Process time + wait time), SA (Simulated Annealing), TS (Tabu Search), AMS (Adaptive Memory Search), SS (Scatter Search), EC (Evolutionary Computation), ANN (Artificial Neural Networks), FS (Fuzzy Systems), SI (Swarm Intelligence) Fig. 2 Classification of task scheduling methods [14]

development tendencies in prioritisation methods; the only possible solution is bibliometric analysis. Bibliometric analysis is a mathematical and statistical analysis, which can serve setting research trends [15] etc. This method is characterised by a possibility of conducting extended quantitative analyses in an objectivised way. Bibliometric analyses are based on available, coherent, objectivised data. This tool is widely used especially in setting trends and research topics in dedicated areas [16].

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2 Aim of the Study The goal of this work was to determine decision making problems and task prioritisation methods used in biofuels production. In order to achieve the said goal, the status of research work was identified, together with decision making issues relating to a task prioritisation problem in biofuels production, on the basis of the bibliometric analysis.

3 Materials and Methods The research was carried out in six stages, using elements of bibliometric techniques: 1:a. Creation of a set of documents based on searching for indexed items in the Scopus database for search: TOPIC: (“biofuel*”) AND TOPIC: (“production”) AND TOPIC: (“schedu*”). The search was carried out from 1945 to 2017 documents in English. 1:b. Uploading all publications of the selected journal in the analysed period of time and extracting bibliometric data (authors, title, year of issue, key words, additional key words, publishing house). 1:c. Construction and analysis of term maps (VOSviewer software). 1:d. Verification of documents’ compliance with the scope of work—creation of a set of documents for further analysis. Classification of documents into appropriate groups according to the adopted division criterion: A. the document raises the problem of task scheduling, B. the research problem is within the scope of biofuel production, Groups have been created: • Responding to the scope of this work—fulfilled the conditions: A and B, • Not responding—none of the conditions are met. 1:e. Quantitative analysis of the set of documents created in the aspect of: number of publications and number of citations, main research areas, major countries. 1:f. Thematic analysis for documents strictly corresponding to the scope of work. The analysis of the content of documents in terms of: • subject matter, • area of application, • used optimization tools. VOS viewer is a free program that is used by researchers for bibliometric analysis, including analysis of research trends [17–20], but also to visualize selected areas of knowledge [21]. In this work, the program was used to create a map of terms: years of publication, intensity of quoting.

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4 Results 4.1

Bibliometric Quantitative Analysis

In the examined period, 96 documents were analysed in total (according to Scopus database). In the analyzed period the main authors were: Jackson, K.M (3 documents), Yacobucci, B.D. (3 documents).The authors come from United States (32 documents), Brazil (15 documents), Spain (4 documents) and Germany, India (3 documents). In the analyzed period, the most documents it was located in the research areas: Energy (51 documents), Engineering (36 documents), Chemical Engineering (29 documents, Material Science (21 documents) and Environmental Science (19 documents). The most-cited publications include: • • • •

Behera S.K. et al. (2010)—Total Citation: 107 [22], Zhu X. et al. (2011)—Total Citation: 68 [23], Spinelli R. and Picchi G. (2010)—Total Citation: 55 [24], Hernández, J.J. et al. (2012)—Total Citation: 51 [25].

In the next stage, the most frequently occurring key words were determined for the analysed periods. For each period the analysis of all key words (Author Keywords, Index Key words) was performed (VOS Viewer). The analysis was limited to the key words which occurred minimum 2 times. Results of the simulations are presented in Fig. 3a and b. The display of results was limited to some 50 key words. Figure 3 presents a summary of keywords depending on the adopted criteria. The first criterion was the published period (Fig. 3a). The main keywords in particular intervals of the year: 2006–2010 were—’renewable energy resources’, ‘synthetic fuels’, ‘plants (botany)’, ‘diesel fuels’, ‘ethanol fuels’, ‘biodiesel plants’, 2010–2014—’biofuels’, ‘biomass’, ‘biodiesel’, ‘profitability’, ‘bioenergy’, ‘greenhouse gases’, ‘harvesting’, ‘forestry’, ‘biomass production’, ‘numerical model’, biorefineries’, 2014–2017—’transportation’, ‘bioconversion’, ‘energy planning’, ‘storage’, ‘energy crop’, ‘biorefinery’, ‘sustainable development’, ‘optimal production schedule’. One can notice transition from liquid biofuels production, through the production of solid biomass, and ending with planning and scheduling. Recently, researchers have been highly interested in optimisation issues, including optimum production scheduling. Considering the number of citations (Fig. 3b) the main keywords were: ‘irrigation’, ‘solar energy’, environmental effects’, supply chain management’, ‘biomass production’, models theoretical’ and ‘numeral model’. Also, this criterion indicates the highest researchers’ interest in optimisation issues. Optimisation tools, in this case, are used to increase biomass production efficiency. The issue of watering energy plants plantations is a huge challenge. Among research topics we can see the application of algorithms and optimisation methods, which can be elements of decision supporting systems.

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Fig. 3 Maps of terms: a Occurrence of keywords in individual years of publishing b The most-cited keywords

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Bibliometric Qualitative Analysis of Literature

Under a qualitative analysis, abstracts of the collected documents (96 titles) were analysed, and next, classified into documents corresponding to publication topics (58 titles) and those not corresponding (other documents). Rejected documents: they did not deal with the topic of biofuels production and/or did not concern the issue of task prioritisation. As a result of documents analyses, two parts have been distinguished: Part I—decision-making problems concerning the issue of task prioritisation in biofuels production (Table 1), Part II—optimisation tools being applied (Table 2). Documents being analysed (Table 1) belong to two areas, namely, production and logistics. Under production, researchers were mainly concerned with energy plant production (new plants, cultivation technology optimisation and the like), biomass processing optimisation and biofuels production (minimisation of energy consumption, a negative environmental impact, improvement of economic efficiency etc.). Researchers also assessed the quality of biofuels produced. The issues of watering optimisation were touched upon as well. Some documents described new, test, demonstration biofuels production installations in different countries. Next, only those documents (14 titles) were indicated, in which task prioritisation methods had been applied, optimisation tools to solve the above-mentioned decision-making problems (Table 2). When analysing specific decision-making problems (Table 2), one can notice that the authors use mainly classical organisation methods. The most frequently applied ones include: priority indicator, MILP, Linear Programming Model, Stochastic Sequential Programming and algorithms implemented in simulation models. In one publication, Genetic Algorithms appeared, which belong to smart optimisation methods. It can be seen that advanced prioritisation methods are used Table 1 Main decision problems regarding the problem of scheduling tasks in the production of biofuels Theme groups

Main decision-making problems

#Production

– Classical technologies of biofuels production, prospects and forecasts of biofuels production in different countries, use of new energy plants and production residuals (e.g. olive pomace and others), biomass production optimisation and processing (reduction of energy consumption, reduction of greenhouse gas emissions, higher efficiencies etc.) into biofuels (solid, liquid and gaseous), quality control of biofuels – New test, demonstration plants for biomass processing of different origin (forest biomass, algae and other) into biofuels in the following counties: Japan, Hawaii, Italy, Malaysia, China, France, Peru, Spain, UK, Finland etc. – Optimisation of energy plants watering – A project of an integrated energy production system based on different renewable energy sources – Optimisation of biomass supply chain, deployment of processing plants, plant planting, biomass harvesting, transport, storage, packing, distribution, dedicated decision supporting systems

#Logistics

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Table 2 Selected decision problems with the method for scheduling task Part 1 Decision problem • A project of an integrated energy production system based on different renewable energy sources • Approach to plan and schedule the production of a biochemical lignocellulosic biorefinery while managing financial risk • Optimisation of energy plants watering • The optimal harvesting unit for ethanol biorefinery and estimate harvesting, storage and transportation costs of switchgrass under various harvesting schedules • Optimization of the biomass supply chain, plant planting, biomass harvesting, transport, storage • A mathematical programming model to design a biomass-to-biofuels supply chain (BTBSC) by maximizing the net present value of the chain • Optimization model was developed to minimize annual biomass– ethanol production costs by optimizing both strategic and tactical planning decisions simultaneously • Planning of Biodiesel Supply Chain • Simulated the harvest and filling of a Satellite Storage Location (SSL)

• Optimization production and processing of biomass

Method of scheduling task

References

• MILP (mixed-integer linear programming)

[26]

• Stochastic Sequential Programming

[27]

• Multi-Objective Genetic Algorithm, Priority indicator • Priority indicator

[28]

• General Algebraic Modeling System (GAMS) using the CPLEX solver on the Georgia Institute of Technology Joe cluster • MILP (Mixed-Integer Linear Programming)

[29]

[30]

[31]

• Priority indicator

[32]

• Linear Programming Model • A simulation model. The model evaluated the impacts of four harvest scenarios (ranging from short, October–December, to extended, July–March), on baler equipment requirements, baler utilization, and the storage capacity requirements of round bales, across a harvest production region • Several experimental schedules have been carried out in order to study the effect of the addition ingredients per priority level

[33] [34]

[25]

(continued)

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Table 2 (continued) Part 1 Decision problem • The supporting logistics system for the dedicated biomass-to-bioenergy industry involves ground preparation and planting, cultivation, harvesting, preprocessing, and storing in production fields of switchgrass; necessary transporting, gathering, loading and unloading, and storing; preprocessing, storing, and conversion at biorefinery sites; and the handling of residues (by-products) after refining bioenergy from biomass • The impact of an intermodal facility on location and transportation decisions for biofuel production plants • Developing a systematic procedure for the design along with the associated scheduling and operating schemes for a biodiesel plant which employs multiple feedstocks

Method of scheduling task

References

• MILP (mixed-integer linear programming)

[23]

• MILP (mixed-integer linear programming)

[35]

• A multi-period optimization formulation is developed to provide a framework for process synthesis and scheduling

[36]

very rarely. The distinguished decision-making problems (optimisation of production, supply chain, storage and the like) indicate a possibility of applying advanced prioritisation methods to a higher extent.

5 Conclusions 1. The decision-making issues regard mainly production (raw materials optimisation and processing, classical and new production technologies, cost reduction and environmental impact reduction, etc.) and logistics (supply chain optimisation, including planting, harvesting, transport, storage, distribution and the like). 2. The main optimisation methods include, first of all, advanced task prioritisation methods. One can distinguish: MILP (mixed-integer linear programming), Linear Programming Model, Stochastic Sequential Programming and Multi-Objective Genetic Algorithm. 3. The analyses conducted have shown the appropriateness of using bibliometric methods (analysis of key words, term maps) to indicate decision-making problems and task prioritisation methods in biofuels production.

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Acknowledgements This research was financed by the Ministry of Science and Higher Education of the Republic of Poland (statutory activities DS-3600/WIPiE/2018, Faculty of Production and Power Engineering, University of Agriculture in Krakow).

References 1. M. Wróbel, K. Mudryk, M. Jewiarz, S. Głowacki, W. Tulej, in (Springer, Cham, 2018), pp. 671–681. https://doi.org/10.1007/978-3-319-72371-6_66 2. M. Niemczyk, A. Kaliszewski, M. Jewiarz, M. Wróbel, K. Mudryk, Productivity and biomass characteristics of selected poplar (Populus spp.) cultivars under the climatic conditions of northern Poland. Biomass Bioenergy 111, 46–51 (2018) 3. M. Jewiarz, J. Frączek, K. Mudryk, M. Wróbel, K. Dziedzic, in (Springer, Cham, 2018), pp. 661–670. https://doi.org/10.1007/978-3-319-72371-6_65 4. M. Wróbel, J. Hamerska, M. Jewiarz, K. Mudryk, M. Niemczyk, in (Springer, Cham, 2018), pp. 691–700. https://doi.org/10.1007/978-3-319-72371-6_68 5. K. Kubica, M. Jewiarz, R. Kubica, A. Szlęk, Straw combustion: pilot and laboratory studies on a straw-fired grate boiler. Energy Fuels 30, 4405–4410 (2016) 6. R. Wąsik, K. Michalec, K. Mudryk, Variability in static bending strength of the “Taborz” Scots pine wood (Pinus Sylvestris L.). Drewno 59, 153–162 (2016) 7. B. Brzychczyk, T. Hebda, J. Giełżecki, in (Springer, Cham, 2018a), pp. 613–622. https://doi. org/10.1007/978-3-319-72371-6_60 8. B. Brzychczyk, T. Hebda, J. Giełżecki, in (Springer, Cham, 2018b), pp. 451–462. https://doi. org/10.1007/978-3-319-72371-6_44 9. K. Grzesik, M. Malinowski, Life cycle assessment of refuse-derived fuel production from mixed municipal waste. Energy Sources Part A Recover. Util. Environ. Eff. 38, 3150–3157 (2016) 10. K. Dziedzic, B. Łapczyńska-Kordon, M. Malinowski, M. Niemiec, J. Sikora, Impact of aerobic biostabilisation and biodrying process of municipal solid waste on minimisation of waste deposited in landfills. Chem. Process Eng. 36, 381–394 (2015) 11. ISO 17225-1:2014 - Solid biofuels – Fuel specifications and classes – Part 1: General requirements 12. V. Vinod, R. Sridharan, Simulation modeling and analysis of due-date assignment methods and scheduling decision rules in a dynamic job shop production system. Int. J. Prod. Econ. 129, 127–146 (2011) 13. A. Knapczyk, S. Francik, Z. Ślipek, The concept of algorithm supporting the process of scheduling production tasks. BIO Web Conf. 10, 02009 (2018) 14. A. Knapczyk, S. Francik, in Innowacje w Zarządzaniu i Inżynierii Produkcji, ed. by R. Knosala (Oficyna Wydawnicza Polskiego Towarzystwa Zarządzania Produkcją, 2017) 15. X. Yaoyang, W.J. Boeing, Mapping biofuel field: a bibliometric evaluation of research output. Renew. Sustain. Energy Rev. 28, 82–91 (2013) 16. S. Francik et al., Bibliometric analysis of multiple criteria decision making in agriculture. Tech. Sci. 20, 17–30 (2017) 17. F.T. Gizzi, Worldwide trends in research on the San Andreas Fault System. Arab. J. Geosci. 8, 10893–10909 (2015) 18. O. Tabatabaei-Malazy, R. Atlasi, B. Larijani, M. Abdollahi, Trends in publication on evidence-based antioxidative herbal medicines in management of diabetic nephropathy. J. Diabetes Metab. Disord. 15, 1 (2015) 19. S.H. Zyoud, W.S. Waring, W.M. Sweileh, S.W. Al-Jabi, Global research trends in lithium toxicity from 1913 to 2015: a bibliometric analysis. Basic Clin. Pharmacol. Toxicol. 121, 67– 73 (2017)

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20. A. Watad et al., Is autoimmunology a discipline of its own? A big data-based bibliometric and scientometric analyses. Autoimmunity 50, 269–274 (2017) 21. J. Zhu, W. Hua, Visualizing the knowledge domain of sustainable development research between 1987 and 2015: a bibliometric analysis. Scientometrics 110, 893–914 (2017) 22. S.K. Behera, P. Srivastava, R. Tripathi, J.P. Singh, N. Singh, Evaluation of plant performance of Jatropha curcas L. under different agro-practices for optimizing biomass – a case study. Biomass Bioenergy 34, 30–41 (2010) 23. X. Zhu, X. Li, Q. Yao, Y. Chen, Challenges and models in supporting logistics system design for dedicated-biomass-based bioenergy industry. Bioresour. Technol. 102, 1344–1351 (2011) 24. R. Spinelli, G. Picchi, Industrial harvesting of olive tree pruning residue for energy biomass. Bioresour. Technol. 101, 730–735 (2010) 25. J.J. Hernández, G. Aranda, J. Barba, J.M. Mendoza, Effect of steam content in the air–steam flow on biomass entrained flow gasification. Fuel Process. Technol. 99, 43–55 (2012) 26. Q. Zhang, M. Martín, I.E. Grossmann, Integrated design, planning, and scheduling of renewables-based fuels and power production networks. Comput. Aided Chem. Eng. 40, 1879–1884 (2017) 27. L. Cheng, C.L. Anderson, Financial sustainability for a lignocellulosic biorefinery under carbon constraints and price downside risk. Appl. Energy 177, 98–107 (2016) 28. R.G. Perea, E.C. Poyato, P. Montesinos, J.A.R. Díaz, Optimization of irrigation scheduling using soil water balance and genetic algorithms. Water Resour. Manag. 30, 2815–2830 (2016) 29. Y. Jin, P. Illukpitiya, Cost minimization of supplying biomass for ethanol biorefineries. Energy 96, 209–214 (2016) 30. K. Yeh, C. Whittaker, M.J. Realff, J.H. Lee, Optimal harvest management adaptation for a new biorefinery investment in a timberlands supply chain using a modified cyclic scheduling model. Comput. Aided Chem. Eng. 36, 521–554 (2015) 31. C. Li, S. Cremaschi, Optimum facility location and plant scheduling for biofuel production. Comput. Aided Chem. Eng. 37, 2435–2440 (2015) 32. T. Lin, L.F. Rodríguez, Y.N. Shastri, A.C. Hansen, K.C. Ting, Integrated strategic and tactical biomass–biofuel supply chain optimization. Bioresour. Technol. 156, 256–266 (2014) 33. M. Valizadeh, S. Syafiie, I.S. Ahamad, Optimal planning of biodiesel supply chain using a linear programming model, in 2014 IEEE International Conference on Industrial Engineering and Engineering Management (IEEE, 2014), pp. 1280–1284. https://doi.org/10.1109/ieem. 2014.7058844 34. D. McCullough, R.D. Grisso, J.S. Cundiff, Discrete event simulation of switchgrass harvest schedules, in 2013 Kansas City, Missouri, 21–24 July 2013 (American Society of Agricultural and Biological Engineers, 2013), p. 1. https://doi.org/10.13031/aim.20131595732 35. S.D. EkşioğLu, S. Li, S. Zhang, S. Sokhansanj, D. Petrolia, Analyzing impact of intermodal facilities on design and management of biofuel supply chain. Transp. Res. Rec. J. Transp. Res. Board 2191, 144–151 (2010) 36. B. Show, R. Elms, G. Nworie, M. El-Halwagi, Optimal design, operation, and scheduling of biodiesel production, in AIChE Annual Meeting (2007)

Laboratory-Teaching Building Energis as the Example of Intelligent Building Dorota Koruba and Robert Piekoszewski

Abstract The article presents the teaching and laboratory building Energis as the example of an intelligent building management system (BMS), in which the Department of Environmental Engineering, Geomatics and Energy Kielce University of Technology is seated. BMS in Energis building is equipped with automatic systems and communication networks which allow for the object’s control and full monitoring. The system controls and manages integrated heating systems (heat pumps, heat center MPEC, biomass boiler), installations, ventilation and air conditioning HVAC, lighting inside and outside of the building. The second basic BMS function is continuous monitoring of all telecommunication systems of building automation and security systems (premises access control) with the registration of the individual installation parameters. BMS also allows to generate and send alarms in case of irregularities in each device operation, as well as in case of exceeding the set points. The paper also reviewed selected installations of building automation including the registration parameters possibility by BMS (Building Management Systems). We also performed a detailed analysis of the selected measurement data recorded by the system in terms of energy.

1 The Definition of Intelligent Building In the early 80s of the twentieth century in the United States, because of the need to acquire the industrial sector of modern solutions in the field of production control its automation and as a result of the very rapid microprocessor technology development(computer science, electronics), for the first time the “intelligent building”

D. Koruba (&)
R. Piekoszewski Faculty of Civil and Environmental Engineering, Kielce University of Technology, Kielce, Poland e-mail: [email protected] R. Piekoszewski e-mail: [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_84

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concept appeared. These needs have forced attempts to develop and implement a simple building management systems. Although, in the 60s the famous towers of the World Trade Center used one of the first computer systems to control heating and air conditioning, but on a large scale such solutions began to be used in the 80’s. The world’s first structure called intelligent building was opened in 1983- The City Place Building in Hartford in the United States [2, 7, 8]. Despite such a long period of building management systems operation there is not a uniform, compact and comprehensive definition of “intelligent building”. According to the Study of the Intelligent Building in Europe intelligence building is the effective use of building space and business systems to support staff in the efficient performance of the tasks. Intelligent Building Institute characterizes the intelligent building by the creation of productive and cost-effective environment as a result of optimization of systems, structures, services, management as well as the optimization of the internal relation between these elements [1, 8, 11, 12]. Intelligent building is a building that integrates different systems to manage resources effectively in a coordinated way in order to ensure the best possible functioning of its users, maximize savings in investment and operating costs and allow for maximum flexibility. Simply saying, intelligent building is a high-tech building which provides users with the comfort and safety while reducing operating costs as well as combining technological innovation [8].

2 Building Management System The consequence of the dynamic microprocessor technology development was the creation of computer systems to control over the building. These systems are among the fastest growing areas of technique because they provide a very high possibility of reducing the building’s operating costs. An analysis of the published data show that the use of such systems, for example in a large office building, can reduce the utilities and electricity supply cost in the range of 10 to 45%. The development of building management systems developed in individual years in the following stages: introduction of digital controllers for building automation, creation of building automation systems BAS (Building Automation System), the rise of building management systems intelligent BMS (Building Management System)/ BEMS (Building Energy Management Systems), the emergence of buildings’ integrated technical infrastructure management IB (Intelligent Building) [3, 4, 6]. BMS (Building Management System) is a computing environment providing a friendly (most often graphic) way to centrally manage and automatically supervise technical installations and the safety of the building, providing comfort, safety and minimizing operating costs. BMS building should oversee the following installations: Automatic air conditioning and ventilation, automatic heating, electrical installations, lighting control, access control, monitoring external and internal information system.

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3 Energis General Description—The Teaching and Laboratory Building Energis building for teaching and laboratory at Kielce University of Technology was built in 2012. Floor area of 5121m2, cubature 23367m3. Energis building design goals was to design a passive object with laboratory and teaching function using all possible technologies to minimize building’s energy consumption. The 25 cm insulation on the outside walls are made, triple glazed window are applied mounted in the surface of the insulation [5]. The heat gain in the building is fully used and the mechanical ventilation installation has a heat recovery. The building does not require a energy supply from conventional sources it is supplied from renewable energy sources. The main heat source for the building is the cascade heat pump built in such a way as to enable conducting research on the use of renewable energy sources. Heat pumps, due to the excellent soil conditions and large water resources are powered by a ground temperature/ground water. For heating the building there are four heat pumps: 2xVitocal 300-G WW129 with power 2x30 kW and 2xVitocal 300 G-BW129 with power 2x25 kW. For the first two heat pumps 16 vertical probes as a heat source are set in depth of 80 meters down. Each pump has its own autonomous system powered with 8 vertical probes. By the applied switching valves node we can change a group of probes in relation to the heat pumps, the change can be implemented from the BMS. The other two heat pumps are powered from drilled wells with a depth of 92 meters down located next to the building. The return water discharge is made for two discharge wells each with a depth of 70 m down, located about 170 m from the extractor well. Due to the use of low temperature heat source in 90% of the building floor heating systems were made with the exception of the premises where the heaters were used. The lower source of the heat pumps are used to power the cooling system in the building during the summer. The installation of floor heating is also used as the radiant cooling loop in the summer [5, 9]. In addition to the heat pump heat demand is covered alternatively with a biomass boiler and the heat exchanger supplied by heating network at Kielce University of Technology. The building Energis also has the installation to obtain and store the solar energy (photovoltaic modules-stationary system and follow-up system) or the heat from the ground.

4 BMS System Managing Energis Building For the BMS system installed in Energis the laboratory and didactic building three access routes were prepared: • local and remote access via software Smart Struxure Workstation • local and remote access via a web browser

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• local and remote access to the report server through a web browser. Below there is a brief overview of selected installations in Energis building integrated and available in the BMS system along with the ability to manage these installations. Menu system BMS has been organized into a group of installations for easier management and because of similar environment settings. In the “stories” group for example, the preview of the actual temperature of all rooms on each floor is placed, the temperature set point from the BMS, the rooms lightening state (On/Off.), the intensity of light in the corridors and in the toilets and the general, pictorial, graphic information if the room is “warm” or “cold.” What is important from this level, you can turn on or off the light in a specific room and display the temperature history in the graph form. In this group, it is possible to configure external lighting around the building, ie. control lighting lamps, lighting poles, lighting balconies, University logo’s backlit, elevation mode LED and the animation displayed on a building with a colors choice. These settings are synchronized with the measurement of external lighting (in 4 different directions) and any specific schedule. In the menu item “Electrical Installations” there are all the basic and advanced information about the electrical network parameters which are constantly analyzed by the device PM800. In this settings group it is also possible to read all counters counting the electrical energy consumption of air conditioning systems (on each floor) all air conditioning units, photovoltaic installation, fans, germicidal UV lamps, individual heat pumps and MPEC heating central distribution. The menu item called “technical installations” gives the ability to view and set the heating central distribution, installation of CT, the Central Heating, the preparation of CWU, land water and preview the combustion parameters in the biomass boiler. It is worth mentioning that the displayed parameters of these installations can be configured at any time to the position of the user interface, for example by controlling the circulation pumps and valves. The intake-exhaust ventilation with heat recovery in the Energis building is being implemented with the participation of five central ventilation units. BMS supervises the work of the ventilation system by measuring all parameters of ventilation and also allows for any configuration and smooth operation of the system. BMS responds to the measured parameters set points (eg. the CO2 concentration in the premises), the state of the filters in the ventilation ducts, supply air temperature to the building is synchronized with weather station installed in the building. During the transitional period when the heat pump does not heat the building and the outside air temperature is too low to implement them to the premises BMS allows alternative heating air through the MPEC central heating distribution, the heat from the biomass boiler or in extreme cases (eg. the damage) by the electric heater. Also worth mentioning is the fact that BMS allows for full adjustment of the settings for the amount of air supplied to the individual rooms. This can be achieved by introducing into the settings base system (as required by applicable law), and the amount of air in the normal range freely adjusted, then we avoid the phenomenon of “draught” (Figs. 1 and 2).

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Fig. 1 Menu system BMS, central ventilation units

Fig. 2 Menu system BMS, VRV controller

The heat pumps installation, because of the function which meets, is the most complicated. Also in the BMS has the primary role its settings are the most configurable. From the menu “heat pump” can also be a quick and uncomplicated way to go to the viewing/setup/configuration for other critical strategic settings from the building’s energy efficiency point of view. The user interface in the “heat pump” is

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Fig. 3 Menu system BMS, heat pump

directly linked and associated with other items on the menu. The system ensures economical operation of the pumps, as well as a performance by a building heating factor was optimal from the savings level point of view. The “heat pump” is shown below (Fig. 3), [9, 10]. The photovoltaic panels installation located on the roof of the Energis building (Fig. 4). It allows to acquire the electricity and storing it in batteries. The system consists of a fixed circuit and trailing panels. The stored electrical energy is used eg. for emergency lighting in the building and building’s electricity. BMS allows to view real-time status of the installation and simple analysis with a daily, monthly and yearly resolution (Fig. 5). The electricity share from photovoltaic system in the whole Energis building energy is about 6%. It is worth noting that all the parameters of individual technical installations in the building measured by the BMS system are continuously recorded and analyzed. BMS is configured in such a way that all the measurement data of the building is

Fig. 4 The photovoltaic panels, a located, b circuit and trailing

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Fig. 5 View real-time status of the installation and simple analysis with a daily, monthly and yearly resolution

Fig. 6 The system analyze on-line

available to the user. It is possible to analyze the system on-line (Fig. 6) and to export measurement data in one of several file formats possible for later editing and analysis of statistical programs. BMS server makes a copy of the data and a copy of the system for preventing a data loss. An important feature of the BMS is also user’s access control to the individual rooms. The system allows to define any users groups, premises groups and assign them any permissions. Access to the premises is carried out by means of magnetic cards. Any access and exits are recorded in the system and possible further analysis. It is also possible to set the reports for a particular user, for a room or for groups previously defined in the system.

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5 The Analysis of the Electricity and Heat Costs A very important element of BMS Energis building from the view of energy efficiency is the ability to create work schedules of individual installations or devices. Schedules are developed on two equivalent levels; First they are put into the system due to the holidays from the calendar and teaching distribution (separately for offices, classrooms separately). Then the premises groups are created which are attributed to the exact time and the permitted work of individual installations and devices. Schedules include following installations and equipment: the heating installation, air conditioning system, the ventilation work as well as the external and internal building installation. The operation time sample periods of the plant and equipment is characterized by the fact that, for example after 4 o’clock p.m (when there are no people in the offices and after 8 o’clock p.m when the classes are not held) the building heating operates on the minimum parameters, the rooms’ air conditioning it is not possible and air handling units do not work. Before starting the work by the employees all the installations and equipment enter to the optimal level of work. It is worth noting that the programming device RCU is also subjected to the schedule. Setting the level of BMS is superior to the set with the RCU. This is related to the need of avoiding a situation where programming device is adjusted by users in the individual rooms during the weather extremes, for example in winter the temperature ranges from 19 to 25 °C and in summer from 17 to 23 °C. Well-developed schedule allows optimally adjust the temperature in individual rooms. The condition for the schedule application is its correct scientific description (including days off, the supervision system over the BMS settings of individual room programming devices). In the Energis building the saving electricity and heat system is used independently from the installations and equipment work schedules application. In rooms designed for people working and in the classrooms the human presence sensors are installed. Sensors allow to clearly identify the presence of people in the room. It is worth mentioning that the configuration of the room sensors can be separated into classrooms and offices. In the case of the offices sensors configuration, we can set the time of inertness (usually is such places people often enter/leave). In the human absence the sensors indicate to the BMS system and it reduces the level or switch off the individual systems. During the first year of use the building the schedules have not been described in details (because of the need to control the operation of all equipment and installations). In the second year of use the building was supervised by a schedule. At the same time they introduce a so-called energy saving system by the use of human presence sensors in the rooms. Below the difference in electricity consumption is shown in both building operation periods along with the use of energy saving system. From the above chart it can be concluded that the work systems schedule and electrical equipment will significantly reduce the electricity consumption of all

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building systems. The graph (Fig. 7) shows the electricity consumption in the Energis building using energy saving system. When analyzing the data collected by the BMS system it must be stated that the schedule application of the installation and the electrical equipment in the Energis building has reduced electricity consumption on average by over 12%. The greatest reduction in consumption was recorded in the month of July and it amounted to over 23%, while the least saving was in December—a little over 6%. In contrast, by the use of energy saving system we also managed to save annually average of more than 6%. The biggest energy saving was recorded in June (over 14%) and October (10+%). The smallest energy saving was recorded in February (just over 1%). Below the above analysis of electricity consumption are graphically presented in the Energis building (Fig. 8).

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Electric power usage in the building Energis percent usage, [%]

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Fig. 8 Graph of the electricity consumption based on the schedule and the energy saving system in relation to consumption without schedule and energy saving system [%]

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6 Summary and Conclusions The use of computer systems to intelligent building management has created new opportunities of objects “configuration”. It allows for optimal use of electricity and heat in order to obtain the best performance of the building and obtain maximum savings while maintaining comfort and safety of the users. Described BMS in Energis educational and laboratory building integrates various building utilities to effectively, in a coordinated way to manage resources in order to ensure the best possible functioning of its users, maximize savings in operating costs and allow maximum flexibility. The article shows the real economic savings that were feasible thanks to the BMS and the use of modern technologies including renewable energy sources.

References 1. M. Bojic´, Optimization of heating and cooling of a building by employing refuse and renewable energy. Renew. Energy 20, 453–465 (2000) 2. H. Doukas, K.D. Patlitzianas, K. Iatropoulos, J. Psarras, Intelligent building energy management system using rule sets. Build. Environ. 42(10), 3562–3569 (2007) 3. W. Feist, J. Schnieders, V. Dorer, A. Haas, Re-inventing air heating: convenient and comfortable within the frame of the passive house concept. Energy Build. 37, 1186–1203 (2005) 4. M. Holuk, Intelligent building - home control capabilities in the XXI century (in Polish), Scientific Bulletin of Chełm, Section of Technical Sciences, No. 1/2008 5. M. Nowak, Zintegrowane systemy zarządzania inteligentnym budynkiem, Efektywność wdrażania technologii informacyjnych - z cyklu Komputer w ochronie środowiska, VII Ogólnopolska Konferencja Naukowo-Techniczna, Poznań - Gniezno, 14–16 września 2005 r., (67–174) 6. R. Kangari, T. Yoshida, Automation in construction. Robot. Auton. Syst. 6(4), 327–335 (1990) 7. G. Mihalakakou, M. Santamouris, D.N. Asimakopoulos, A. Argiriou, On the ground temperature below buildings. Sol. Energy 55, 355–362 (1995) 8. I.F. Owajionyi, Intelligent building concept: the challenges for building practitioners in the 21st century. AARCHES J6(3), 107–108 (2007) 9. J.Z. Piotrowski, M. Olenets, A model of heat and air transfer in a ventilated, rectangular space. J. Build. Phys. 40(4), 334–345 (2016) 10. J.Z. Piotrowski, Pompy ciepła jako podstawowe urządzenia ciepła i chłodu w instalacjach OZE; Budownictwo energooszczędne w Polsce - stan i perspektywy (Wydawnictwo Uniwerytetu Technologiczno – Przyrodniczego, 2015), ISBN: 978-83-64235-74-0 11. W. Shengwei, Junlong X. Autom. Constr. 11(6), 707–715 (2002) 12. S.B. Sadineni, S. Madala, R.F. Boehm, Passive building energy savings: a review of building envelope components. Renew. Sustain. Energy Rev. 15, 3617–3631 (2011)

Calculation of Thermal Energy Storage System Capacity Dependent on Climate and Building Structure Anna Kozikowska , Tomasz Bakoń

and Paweł Obstawski

Abstract This paper contains description of the smart database with usage profiles and technical data for main thermal energy storage system (TESS) components: solar thermal collectors, compressor heat pump with vertical ground heat exchanger without and with phase change material (PCM) in boreholes, hot and cold PCM tanks, domestic hot water (DHW) tank and building with low temperature heat receivers such as underfloor heating and fan coils. Usage profiles that were created in the database depend on climate data, building type and structure information which are the basis for calculations of building energy demand. The database uses the examples of devices that are available on the market and, most importantly, gives user a smart tool to select solution for the TESS from the technical and economical point of view. Keywords Thermal energy storage system Smart database


Phase change material


1 Introduction TESSe2b Project—Thermal Energy Storage Systems for Energy Efficient Buildings is a EC financed Horizon 2020 four years project that develops an integrated solution for residential building energy storage using solar and geothermal energy with the purpose of correcting the mismatch that often occurs between the supply and the demand of energy in residential buildings. That can be achieved by integrating compact thermal energy storage tanks with phase change materials A. Kozikowska
T. Bakoń (&)
P. Obstawski Warsaw University of Life Sciences, Nowoursynowska 166, 02-787 Warszawa, Poland e-mail: [email protected] A. Kozikowska e-mail: [email protected] P. Obstawski e-mail: [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_85

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(PCM TES) coupled with enhanced phase change materials inside the borehole heat exchangers (BHEs) and using an advanced energy management self-learning control system. Demonstration and on-site monitoring of small scale TESSe2b solution will be implemented in residential buildings in three pilot sites (Austria, Cyprus and Spain) in order to evaluate the system integration into buildings space, to assess the impact of TESSe2b solution in different climates, and also to provide results of technical and economic aspects of system feasibility. This paper contains description of the smart database with usage profiles and technical data for main thermal energy storage system (TESS) components: solar thermal collectors, compressor heat pump with vertical ground heat exchanger (without and with PCM in boreholes), hot and cold PCM tanks, domestic hot water (DHW) tank and building with low temperature heat receivers such as underfloor heating and fan coils. Usage profiles, that were created in the database, depend on climate data, building type (private—public, all day—partially use) and structure information (cubature, insulation, etc.) which are the basis for calculations of building energy demand. Besides the standard model of the building, the application also uses models created in DesignBuilder. The database uses the examples of devices that are available on the market and, most importantly, gives user a smart tool to select solution for the TESS from both technical and economical sides.

2 Programming Environment The database was implemented in Microsoft Excel 2007 using programming language Visual Basic for Applications and precalculated models from dedicated software DesignBuilder. The calculations in Excel are not as accurate as they are in Matlab or CFD simulations, but it should be noted that Excel enables user to obtain results much quicker (similar to online) than in those two applications (minutes, hours of calculation time). Database uses EnergyPlus Weather Data which is represented by more than 300 meteorological stations located in whole Europe and some parts of Asia. Users have a possibility to enter their own data into proper spreadsheets, but they do not have an access to calculation processes as well as programme codes. It should be also noted that Excel is well-known, cheap and commonly used application in business environment as well as by domestic users, and is available almost on every device including PC, tablets and smartphones, which makes it user-friendly.

3 Software Interface and Input Data Figure 1 shows an interface of database menu that gives the user an access to six spreadsheets: location, building and TESS parameters, heat pump and solar collectors, energy prices, technical results and economic results. User select input data from four of these spreadsheets as follows:

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Fig. 1 Interface of database main menu

Fig. 2 Structure of example spreadsheet building and TESS parameters

– location with selection of: country and meteorological station; – type of building with selection of: type of building, building parameters, energy use parameters, energy storage parameters and heat exchanger parameters; – producer and type of heat pump and solar collector with selection of: producer and type of heat pump and solar collector; – energy prices that depend on country and tariff of electrical energy with selection of: country, electrical energy and other energy sources. Figure 2 shows the structure of example spreadsheet Building and TESS parameters.

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Location

There are more than 300 meteorological stations available in the database that consider different climate including Mediterranean, Central European and Scandinavian. The following countries were chosen: Austria, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Cyprus, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Lithuania, Netherlands, Norway, Poland, Portugal, Romania, Russian Federation, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, Ukraine and United Kingdom. After selecting country and meteorological station, the following parameters are downloaded: average hourly statistics for dry bulb temperatures, average hourly statistics for direct normal solar radiation and monthly calculated “undisturbed” ground temperatures. After selecting the building, parameters are loaded into proper spreadsheets and listed in the table. These parameters are: 1. Building parameters: power demand of the building [W/m2], building area [m2], inner temperature [°C], design temperature [°C], hot water tank volume [dm3], temperature of the water supply [°C], DHW temperature [°C], temperature of the water flow system [°C], flow temperature of the hot water tank [°C]; 2. Energy use parameters: energy use for heating—day [%], energy use for heating —night [%], energy use for cooling—day [%], energy use for cooling—night [%]; 3. Energy storage parameters: energy stored in hot PCM tank [%], hot PCM tank energy [kWh], hot PCM tank efficiency [%], energy stored in cold PCM tank [%], cold PCM tank energy [kWh], cold PCM tank efficiency [%]; 4. Heat exchanger parameters: heat exchanger power—without PCM [W/m], heat exchanger power—with PCM [W/m], max length of boreholes [m].

3.2

Heat Pump and Solar Collector

The most commonly used devices as well as leading producers of heat pumps and solar collectors were implemented in the database. Users have also a possibility to choose another producers and models. If another type of heat pump or solar collector is selected for the TES system, it is also implemented in the database. After selecting heat pump, parameters such as power of the compressor [kW], cooling power [kW] and price [EUR] are loaded into proper spreadsheets. Parameters which are necessary to start calculations for heat pump and are available in producers data sheets with heat pump characteristics, are shown in Fig. 3 (x1, y1, x2, y2). For solar collector these parameters are: absorber area [m2], optical efficiency [%] and price [EUR].

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Fig. 3 Heat pump characteristic (based on Viessmann online data sheet)

3.3

Energy Prices

Prices of energy sources, that are presented in the database, depend on country and energy supplier if considering electricity. Users can select prices of energy for countries that are TESSe2b partners (Austria, Cyprus, Denmark, Germany, Greece, Poland, Portugal, Spain and United Kingdom) and for a representative of Scandinavia—Denmark (as the most promising for the TESSe2b system). There is also a possibility to enter another country into database. Energy prices for electricity are divided into two tariffs—single tariff and dual tariff in order to increase TESSe2b system energy efficiency. After selecting country and tariff of electrical energy, parameters are loaded into proper spreadsheets and listed in the table. These parameters are: 1. Electrical energy: day-time [EUR/kWh], night-time [EUR/kWh], heating energy moved to the night period [%], cooling energy moved to the night period [%]; 2. Other energy sources: natural gas [EUR/m3], coal [EUR/t], oil [EUR/dm3], LPG [EUR/dm3].

4 Results All of the results are presented in four spreadsheets in form of diagrams and analyses considering two solutions for the system—without and with solar installation.

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Fig. 4 Technical results

4.1

Technical Results

Figure 4 shows spreadsheet with technical results where diagrams and analyses (3 from 7 listed below) for each of the two solutions are presented. 1. Power demand for heating and cooling as a function of an ambient temperature; 2. Energy demand for heating, cooling and DHW per month (red column—heating, green column—cooling, blue column—DHW); 3. Energy demand: energy demand for DHW [kWh/year], energy demand for heating [kWh/year], energy demand for cooling [kWh/year], total energy demand [kWh/year]; 4. Solar installation: energy production [kWh/year], number of collectors; 5. Heat pump: average value of COP for DHW_58 °C, average value of COP for heating_45 °C, SCOP, electrical energy used by HP for DHW [kWh/year], electrical energy used by HP for heating [kWh/year], electrical energy used by HP for cooling [kWh/year], electrical energy used by HP [kWh/year], reduction coefficient for heating [%], reduced energy used by HP for heating [kWh/year], reduction coefficient for cooling [%], reduced energy used by HP for cooling [kWh/year], number of operation hours of HP [h/year]; 6. Heat exchanger: length of boreholes_without PCM [m], length of boreholes_with PCM [m], number of boreholes_without PCM, number of boreholes_with PCM; 7. PCM tank: number of hot PCM tanks, number of cold PCM tanks.

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Fig. 5 Economic results

4.2

Economic Results

Figure 5 shows spreadsheet with economic results where diagrams and analyses for each of the two solutions are presented. 1. Comparison of the operation cost without solar installation (first column— electrical energy, second column—natural gas, third column—coal, fourth column—oil, fifth column—LPG); 2. Comparison of the operation cost with solar installation (as above); 3. Economic analysis: price of heat pump [EUR], price of solar collector [EUR], cost of main components (heat pump and solar installation) [EUR], operation cost of HP [EUR/year], savings on heating [EUR/year], savings on heating [%], savings on cooling [EUR/year], savings on cooling [%].

4.3

Graphs Without Solar Installation

Figure 6 shows spreadsheet with solution for the system without solar installation where technical results and diagrams are presented. 1. Technical results; 2. Electrical energy used by heat pump per month (blue column—DHW, red column—heating, green column—cooling); 3. Average monthly value of COP (red line—COP for heating, blue line—COP for DHW);

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Fig. 6 Graphs without solar installation

4. Demand for heating and DHW per month (red column—demand for heating and DHW, blue column—max power of heat pump); 5. Demand for cooling per month; 6. Average daily demand for heating; 7. Average daily demand for cooling.

4.4

Graphs with Solar Installation

Figure 7 shows spreadsheet with solution for the system with solar installation where technical results and diagrams are presented. 1. Technical results; 2. Demand for DHW covered by solar installation per month (red line—demand for DHW, blue line—DHW covered by solar installation); 3. Energy production from solar installation per month (red line—demand for heating and DHW, blue line—energy from solar installation); 4. Electrical energy used by heat pump per month (red column—heating, blue column—DHW, green column—cooling); 5. Demand for heating and DHW covered by Heat pump per month (red column— demand for heating and DHW covered by heat pump, blue column—max power of heat pump); 6. Average daily demand for heating; 7. Average daily demand for cooling.

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Fig. 7 Graphs with solar installation

5 Summary and Conclusions This paper presents the results of developing a tool (smart database) that calculates capacity of TES system using climate and technical data. This database helps estimate energy demand of the building and shows how the TESSe2b system works if user changes input parameters referring to technical and economic aspects. It gives a possibility to test any type of building in various locations, which makes it versatile as it can be used by different users in many countries. What is more, it has an open structure, which means that users can create their own buildings with suitable parameters as well as they can add other types of heat pumps and solar collectors in order to test their own preferences. The software that was used to create the database, Microsoft Excel, is a very practical application as it is commonly used in business environment and, which is more important for domestic users, it is cheap. This all makes the database a user-friendly tool that helps find the best solution for a complex system. Acknowledgements Presented research results were funded from the TESSe2b project, that is financially supported by the Horizon 2020 Research Innovation Action (RIA) of the European Commission, call EeB-Energy-efficient Buildings (Grant Agreement 680555).

Substantiation of the Working Surface Parameters of the Screw Press Drawing Block of Plant Materials Dmytro Kuzenko, Oleh Krupych, Stepan Levko and Krzysztof Mudryk

Abstract This paper addresses the problem of biomass processing relevance into alternative solid biofuels, related primarily to issues of economic feasibility of agro-industrial production waste recycling, rising prices for fossil fuels, minimizing transportation costs and enhance environmental requirements. It is noted that a new innovative sector of the economy—bioenergetics, based on the production of biomass fuel and energy, but its further development requires improved technology, machinery and equipment used, in order to reduce energy intensity and improve the quality of machines derived products. Analysis of recent researches in this area has shown that reduction of the energy intensity of biomass pressing process with a screw press can be achieved by changing the configuration of the drawing block working surface that will reduce quantities of mass movement harmful resistance in the working channel. The carried out studies of the drawing block working channels wear character and existing curved surfaces made it possible to recommend a curved surface as a working surface a screw press drawing block which is a tractrix. The work imposes the results of the analysis of the tractrix parametric equation and the graphical dependences of the working surface parameters on the tractrix characteristics. The analysis of the displacement nature of the plant mass in the working channel of the drawing block of the proposed design gave an opportunity to obtain the differential equation of the plant mass pressure on the length of the working channel. The paper describes the graphic solutions of the equations in MATLAB D. Kuzenko
O. Krupych
S. Levko Department of Power Engineering, Lviv National Agrarian University, 1, V. Velykyi Str., Lviv-Dubliany 80-381, Ukraine e-mail: [email protected] O. Krupych e-mail: [email protected] S. Levko e-mail: [email protected] K. Mudryk (&) Faculty of Production and Power Engineering, University of Agriculture in Krakow, Balicka str. 116 b, 30-149 Krakow, Poland e-mail: [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_86

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environment for various tractrix parameters features and made appropriate conclusions about the nature of relationships and future research directions.







Keywords Biomass Compression process Screw press Working channel Tractrix Decrease in energy intensity








Drawing block


1 Introduction The main reserve of alternative renewable fuels is biomass, which is produced in large quantities as waste from the agro-industrial complex. So the question biomass processing is of great relevance, related primarily to issues of economic feasibility —pellets/briquettes from biomass are goods, while agricultural waste, which represent the bulk of the biomass product is practically not. On the other hand, the rapid rise in prices for fossil fuels, the desire to minimize transportation costs, increasing environmental requirements and other issues also increase interest in the biomass of plant origin processing in solid fuels. In fact, a new innovative sector of the economy—bioenergetics—has emerged, based on the production of biomass fuels and energy. As a result of thermochemical and biotechnology use to transform biomass energy of plants and renewable resources we receive heat, electricity, biofuels (ethanol, butanol fuel, biodiesel, etc.). Currently, biomass is mainly used as solid fuel (firewood, sawdust, wood chips, fuel briquettes and pellets), which replaces hydrocarbon raw materials in boilers, heat and power plants. When using wood fuel, there is no need for serious modifications of technological equipment for combustion of fuel, while emissions of harmful substances into the environment are significantly reduced. It should be noted that the maximum heat output is achieved by combustion of granular and pressed biomass, however, an increase in the production of fuel briquettes and pellets requires the improvement of technologies, machines and equipment used in the direction of reducing the energy intensity of machines and improving the quality of products received.

2 Description of the Biomass Utilization Technology by Means of Methane Fermentation The conducted review and analysis of literature sources shows that many scientists and designers [1–3, 5, 7, 10] devoted their research to ways of plant materials energy intensity processes reduction, improving the perfection and reliability of constructions of machines used. The majority of the authors of these publications devote their work to the study of the structural parameters influence of presses (pistons, screws, roller-matrix pairs) on the qualitative indicators of the pressing

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process. It should be noted that the vast majority of studies are devoted to the suppression of fodder crops, therefore, when developing the equipment for pressing straw and wood, they use the classic technology of feed processing with partial adaptation to the type of biomass. But the production of mixed fodder by technology differs significantly from the manufacture of solid fuel, it is necessary to recycle a porous organic polymer of vegetable origin containing moisture. For example, the technology of production of fuel pellets with the exception of drying operations is similar to the technology of preparing granulated feed with the use of press granulators, but there is a need to granulate a sufficiently large assortment of materials, and most of the existing presses do not have a mechanism for regulating the pressing channel, due to which the level of energy consumption in them is inflated. At the same time, despite the fact that the properties of crushed biomass differ significantly from the properties of fodder, in the world market, machine manufacturers produce press granulators without taking into account these features. In well-known information sources, information on the physical-mechanical properties of crushed biomass, which is important for the implementation of the granulation process, is insufficient. It is necessary to investigate the dependence of the useful resistance power forces and the productivity of the pressing mechanism on the angular velocity and size of the executive bodies. To date, the choice of the parameters of the executive bodies of the press has not sufficient scientific justification. Particularly noteworthy is the problem of the drawing block structures imperfection, which have a significant impact on the biomass compaction process, and hence on the energy intensity and quality of the production of solid fuel. But in most cases little attention has been paid to the drawing block’s design, in particular to the outlet channels parameters. When designing extruders, most authors apply channels of outlet drawing blocks either cylindrical or rectangular [3, 7]. Although extruders used in the food industry have other forms of outlet channels. From the analysis of literature sources we made an attempt to generalize the drawing blocks’ designs used in the plant materials processing, namely, their outlet channels. In particular, they should be distinguished due to the form of a cross-section: round; ring; curly rectangular; with a variable section. Using drawing blocks to compress different materials, some press constructions provide the use of replaceable nozzles, although it seems expedient to develop designs for a universal adjustable drawing block. When designing a drawing block, almost all authors emphasize the need to maintain a ratio of length of the drawing block to a diameter of 3/1, and the inlet channel must be made with an angle of not less than 45°, which allows the material to flow faster to the forming part of the drawing block. Although, these ratios are not theoretically justified. Based on the analysis of literature sources, we have formulated the working hypothesis: the reduction of energy intensity of biomass pressing process with screw press can be achieved by changing the configuration of the working surface of the drawing block, which will reduce the size of the harmful resistance to the displacement of the mass in the working channel.

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Therefore, the purpose of the work is to substantiate the shape and parameters of the drawing block working surface of the biomass screw press for the manufacture of solid fuel.

3 Results and Discussion As already noted above, the problem of selecting the pressing equipment depends on the properties of the material being processed. Due to the fact that the processing subjected to a polymer that possesses the properties of the Bingham body (non-fluidity), only the screw specialized presses [9] should be used. The application of the impact action for pressing the plant mass is low-efficient, and does not take into account the rheological properties of the processed material. The effectiveness of the roller press is reduced when processing materials with low bulk density. When processing fodder, it is 70%, wood—less than 30%, straw—less than 10% [5]. In order to substantiate the shape of the drawing block working surface, we studied the nature of its working channels wear, which showed that during a certain period of operation, channels of different shapes from cylindrical to conical with a variable section as a result of wear are smoothed and acquire the form of elongated torus (see Fig. 1). This indicates that the presence of various stress concentrators in

Fig. 1 The nature of the wear of the drawing block working channels: a the shape of the unworn drawing block channels; b, c, d a form of worn out channels; e, f is the character of wear of the channels of working channels’ inserts; g the nature of the ring matrix channels wear of the granulator

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the working channel (belts, transitional edges, etc.) leads to the creation of zones with increased values of normal stresses which are subject to faster wear, this is also accompanied by the emergence of unproductive forces of material movement resistance. Consequently, it seems expedient to develop a drawing block with a working surface, which is close to that which is formed during wear for a long exploitation. To the same conclusion came Sokolov A.Ya. and Polishchuk V.Yu. [7], who proposed to increase the durability of the molding matrix of the herbal flour press-granulator, by making the channels (drawing blocks) of the ring matrices in the inlet part of the toroidal form, which in their opinion is more suitable for use in the molding heads, due to the increase wear resistance. However, the authors of the work did not substantiate either, their constructive parameters nor the effect of the form on the energy usage figures. Proceeding from the above and analysis of the peculiarities of the behavior of known curves used in various branches of engineering for the production of working bodies [6, 8] such as the exponent, the Archimedean spiral, the logarithmic spiral, the chain line, etc., we propose to use a tractrix as a generant of a working surface drawing block [4, 6]. The proposed curve is the so-called “natural curve with the least resistance” and the shape most resembles the shape of the drawing block worn surface during the operation. The use of the tractrix as a generant will give the possibility to create a cone-shaped surface of the variable section during rotation, which most closely meets the conditions of the task. A tractrix (from the Latin verb trahere “pull, drag”; plural: tractrices) is the curve along which an object moves, under the influence of friction, when pulled on a horizontal plane by a line segment attached to a tractor (pulling) point that moves at a right angle to the initial line between the object and the puller at an infinitesimal speed. This line describes an object that stretches on a rope of constant length along a moving point along the abscissa (Fig. 2) [6]. The basic equation of the tractrix has the form x ¼ a ln

Fig. 2 View and parameters of a tractrix

aþ

pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi! pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi a2  y 2  a2  y 2 ; y

ð1Þ

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and a parametric equation 

  x ¼ a ln tg 2t þ a cost; y ¼ a sint;

p  t\p 2

ð2Þ

The surface formed by the rotation of the tractrix around the axis is called the pseudo-sphere [6]. It is widely used for the manufacture of horn loudspeakers, wind musical instruments. Tractrix is also used as a generant to make the surface of an antifriction footstep mechanism of a vertical turning and boring machine. In a channel of this form, the biomass is partly covered by a curve during the movement. Figure 3 shows the constructive scheme and the general view of the experimental drawing block with the working surface formed by the tractrix. Since the radius of curvature at each point is different, respectively, the reactions and forces of friction will have different magnitudes and directions. The moving mass moves through the channel and is densified by reducing the cross-sectional area of the channel and the displacement resistance. The length of the molding head channel will depend on the density required of the material and the diameter of the screw (the initial diameter of the working channel of the head) [4]. Using the parametric Eq. (2) we made a constructive analysis of the working channel and constructed the relationship between the ratio of the screw diameters and the outlet hole of the head working channel (D is the diameter of the screw, d is the diameter of the outlet hole of the working channel of the molding head) and its length l (Fig. 4). As we see from the graph (Fig. 4), the growth of the head length, depending on the ratio of the screw diameter and the outlet hole, is smooth and decreases with increasing this ratio. For different values of the initial diameters (the diameter of the channels of screw presses), these dependences are different, and the dependence of the length l of the part of the working channel, where the compression occurs to the initial diameter D has a hyperbolic character. In particular, for the initial diameter

Fig. 3 Experimental drawing block: a design scheme; 1—body of the head; 2—internal surface of the head (pseudo-sphere); 3—working camera; 4—outlet cylindrical hole; 5—molding head mounting; 6—press body; 7—press screw; b general view

Substantiation of the Working Surface Parameters … Fig. 4 Dependence of the working length of the drawing block l on the ratio of the inlet and outlet diameters k at values of the inlet diameter D: 1—D = 80 mm; 2— D = 120 mm; 3— D = 160 mm; 4— D = 200 mm

901

l, мм 140

4

120 3

100 2

80 60 1

40 20 0

1

1,5

2

2,5

3

3,5

4

4,5

λ

    D ¼ 80 mm l ¼ D
1:162  1:574 ; for D ¼ 120 mm  l ¼ D
1:015  1:35 ; k k   1:303 etc. Therefore, to substantiate the for D ¼ 160 mm  l ¼ D
0:949  k parameters of the drawing block, it is worth examining in more detail the dependence of the density (pressure) of the plant material on the diameter of the outlet hole and the length of the working channel, which requires consideration of the process of mass transfer in the molding head. To develop a mathematical model for moving the plant mass in the molding head with the channel, generant of which is the tractrix, consider the scheme of the load action on the elementary volume of the material in the length dx (Fig. 5). We will assume that the plant material moves uniformly and the pressing forces are distributed equally across the plane of the cross section at the end of the screw body. On the selected elemental volume of the material there act forces of pressing F1, the force of resistance F2, directed opposing the force of pressing, distributed normal forces qn, directed perpendicularly to the tangent curvature of the channel wall and distributed forces of the material friction along the channel wall qs . Forces of pressing F1: F1 ¼ p
S;

ð3Þ

where p pressure; S cross-sectional area of the channel, S ¼ p
y2 ðtÞ. Force of resistance F2 is defined as:    dp dS dS dP dx S þ dx  pS þ p dx þ S dx; F2 ¼ p þ px dx dx dx where

dS dx

y_ dt ¼ dS dt dx ¼ 2pyðtÞ x_ .

ð4Þ

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Fig. 5 Scheme of forces’ action on the elemental volume of material

Distributed forces of the material friction along the channel wall qs : qs ¼ fm
qn ;

ð5Þ

where qn distributed normal forces; fm the coefficient of friction of the material on the wall of the chamber. We believe that the acceleration that arises during the mass transfer is small, and therefore we will neglect the forces of inertia. Also, we neglect the forces of its own weight of the element on the qn effort. Then the equation of equilibrium of the selected element in the projections on the axis 0x. P

Fx ¼ 0: F1  F2  qn
2pyðtÞdx
sina  qs
2pyðtÞdx
cosa ¼ 0;

where

x_ cos a ¼ pffiffiffiffiffiffiffiffiffiffiffiffiffiffi ; 2 x_ þ y_ 2 _y sin a ¼ pffiffiffiffiffiffiffiffiffiffiffiffiffiffi : x_ 2 þ y_ 2

ð6Þ

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2

cos t _ ¼ dy Since x_ ¼ dx dt ¼ a sint , and y dt ¼ a cost (here a—tractrix parameter), and taking into account that the distributed load qn ¼ g
p þ q3p —depending on the operating pressure and the residual deformations of the material, after certain transformations and simplifications, we obtain an equation for determining the pressure of the plant mass in a certain area along the length of the molding head channel in this form

0 pðtÞ ¼

e

ðhðtÞ4gfm Þ

sin2 t



2g tg 2t

B @p0  2q3p

Zt

1 C uðzÞehðzÞ dzA;

ð7Þ

p 2

 1  where hðtÞ ¼ cost þ fm sint þ sint 2g;  z 2g uðzÞ ¼ cos2 zðsinz  fm coszÞ tg ; 2 g lateral pressure factor q3p pressure created by the residual deformations of the material. The analysis of Eq. (7) was carried out in the MATLAB environment, where the graphic pressure dependences on the length of the working channel of the drawing block were obtained (Fig. 6). In the calculations were taken: - initial axial pressure p0 = 12 MPa; - residual lateral pressure qзл = 0.24 MPa; - coefficient of lateral pressure η = 0.35; - coefficient of friction of vegetative material on the surface of the head fm = 0.32. As you can see from the graphs of the intensity, the increase in pressure occurs throughout the length of the drawing block working channel. At the final part, the intensity of growth decreases, which is explained by considerably less curvature of the surface per unit of the channel length, and therefore less intensity of change in mass volume and its effect on pressure variation. The obtained graphic

Fig. 6 Dependences of the pressure variation of the plant material on the length of the molding head for different values of a parameter

р, МПа

а=40 мм а=60 мм а=80 мм а=100 мм

50 45 40 35 30 25 20 15 10 0

20

40

60

80

100

120

х, мм

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dependencies (Fig. 6) can be used to substantiate the parameters of the working channel in the form of a surface formed by the tractrix at given values of the final density of the compressed mass, the speed (intensity) of the increase of pressure, and other parameters of the pressing process. It should be borne in mind that a tractrix parameter and the initial diameter D of the drawing block are determined by the equation D = 2a (see Fig. 2).

4 Conclusions The obtained analytical and graphic dependencies create the preconditions for determining the structural parameters of the working channel of the screw press drawing block with the working surface, generant of which is the tractrix. In this case, we require values of the coefficients of lateral pressure, residual pressure of the plant mass and the coefficients of mass friction on the working surface. The dependence of the length of the working channel of the drawing block l on the outlet channel diameter D of the screw press has a hyperbolic character and is determined for each value of D separately. In this case, the received dependences of the pressure change along the length of the working channel in accordance with (7) are provided. Further research should be directed to the development of rheological models of biomass at different stages of compaction and their study should be conducted taking into account the conditions of mass transfer (7) for determining the values of the coefficients of lateral pressure, residual pressure of the plant mass and the coefficients of friction.

References 1. S.A. Alferov, Regularities in the compression of straw, S.A. Alferov, Leningrad: Selkhozmashina, vol. 3 (1957) 2. A.V. Bragin, Ganapolsky S.G., Investigation of the process of pressing wood briquettes from wood waste. Actual problems of the forestry complex, in Collection of Scientific Papers on the Results of the International Scientific and Technical Conference, no. 22, BGITA, Bryansk, 2009, 299 p. [Electronic resource] http://waste.ua/cooperation/2004/thesis/index.html 3. V.V. Karmanov, Energy-saving technology and equipment for obtaining fuel pellets, profiles (briquettes) from waste of plant raw materials, in Problems of Light and Textile Industry of Ukraine, vol. 1, no. 16, ed. by V.V. Karmanov, V.D. Mikhaylik, N.L. Kostyunin (2010), pp. 72–76 4. D.V. Kuzenko, Justification of the design of the forming press head for plant materials, ed. by D.V. Kuzenko, S.I. Levko. Visnyk Lviv. NAU “Agroengineering research”, Lviv, vol. 16 (2012), pp. 246–253 5. Z.M. Kuchinskas, Equipment for Drying, Pelletizing and Briquetting Feeds, ed. by Z.M. Kuchinskas, V.I. Osobov, Y.L. Freger (Agropromizdat, Moscow, 1988), 208 p

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6. A.A. Savelov, Flat curves. Systematics, properties, applications. (Reference Guide), Gos. Published Physico-Mathematical Literature, Moscow, (1980) pp. 294 7. A.Y. Sokolov, Perfection of the Design of Matrices of Granulators, ed. by A.Y. Sokolov, V. Y. Polischuk, M.L. Ovdienko. Mechanization and electrification of agriculture, vol. 11 (1983) 8. S.S. Tishchenko, Design of Pointed Cultivator Pinchers with a Curved Blade. Naukovii visnik LNAU. Ed. 73 (2004) pp. 304–309 9. I.Y. Fedorenko, I.A. Naumov, Method for determining the coefficients of the basic equation of pressing. Bull. Altai State Agrar. Univ. 8(34), 52–55 (2007) 10. J. Grochowicz, Wpływ Wilgotności i Stopnia Rozdrobnienia na Energię Zagęszczania i Wytrzymałość Brykietów Łubinowych, ed. by J. Grochowicz, D. Andrejko, J. Mazur. MOTROL. Motoryzacja i energetyka rolnictwa, Lublin, Tom. 6 (2004), ss. 96–103

Development of Renewable Energy Sources in Big Cities in Poland in the Context of Urban Policy Aleksandra Lewandowska, Justyna Chodkowska-Miszczuk and Krzysztof Rogatka

Abstract Development of renewable energy sources (RES) is a crucial factor, influencing diversification of energy sector. Popularization of renewable energy projects has a key significance in building energy security system in Poland, therefore most of strategic decisions concerning RES are taken on the country level, and basing on EU directives, general development directions are also formed there. Implementation of assumptions referring to RES is conveyed to administrative organs of lower level. Due to the fact that the most important challenges concerning energy sector transformation, including RES projects, refer to multifunctional urban areas, it is crucial to analyze, what way urban self-government authorities put these tasks of initiating and implementing pro-ecological enterprises of RES sector in practice. Taking into account the fact that renewable energy development in cities is a leading element of urban policy, implementing directives of sustainable development and the fact that actions for RES promoting are indispensable factor influencing low carbon economy development, it is assumed that renewable energy is an important pillar of low-carbon economy in cities. Taking the above into account, the research purpose is to make analyze of initiatives and actions within renewable energy development in big cities, taken up by self-government authorities, outlined in strategic documents. Present research will be carried out in reference to real RES structure and dominant directions of RES development in cities selected for tests. Study results will enable to predict RES sector development in urban areas, as necessary condition of low-carbon economy in Polish cities. Keywords Renewable energy


City
Urban policy
Poland

A. Lewandowska (&)
J. Chodkowska-Miszczuk
K. Rogatka Faculty of Earth Sciences, Department of Urban and Regional Development Studies, Nicolaus Copernicus University, Lwowska 1, 87-100 Toruń, Poland e-mail: [email protected] J. Chodkowska-Miszczuk e-mail: [email protected] K. Rogatka e-mail: [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_87

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1 Introduction Intensive development of urban areas is one of civilization progress signs. Population inflow to cities, related with better standard of living and more possibilities of personal development generates a lot of benefits, but also threats and challenges, like additional costs (environmental, financial), being a consequence of urban areas proper functioning [1, 2]. At present, providing energy security, not neglecting environmental aspects is one of key question. The problem of energy security in urban areas is crucial in Central European countries, which face changes connected with energy sector transformations and search for new development impulses [3, 4], but their range and speed is determined by complicated historical-political past of this part of Europe, what currently is expressed by the dominance of one energy source (e.g. hard coal in Poland), as well as energy centralization and energy dependence on Russia [5, 6]. Polish presence in European Union (EU) is related with the necessity of implementing changes within the energy sector, meeting EU Policy of cohesion, expressed by diversification of energy sources and growing role of RES [7]. Following the regulations of the Directive 2009/28/WE, EU Member States are obliged to raise the share of RES in energy production structures of 20% by 2020; for Poland the target is estimated for 15%. Moreover, long-term energy policy of EU (by 2050) assumes total decarbonization of energy sector [8]. Taking all this into account, renewable energy development in Poland requires institutional, administrative and financial support. Hence, implementing the EU climatic-energy policy in Poland is connected with legislative framework, planning, organizational and investment actions on various levels—state and self-governmental. Some of these actions are defined in state legislation and strategic documents specifying emission decrease and increase of Polish energy sector efficiency, as well as more effective use of RES. Successful transformation of Polish energy production from high-carbon to low-carbon energy should start first of all with local levels. In order to complete the task Polish government worked out National Program for the Development of a Low-carbon economy (in Polish—NPRGN). In 2013 the Ministry of Economy put forward the conception of local plans for low-carbon economy (LCEP, in Polish PGN), referring to NPRGN. They were based on European ‘Covenant of Mayors’, functioning since 2008 under the auspices of European Commission and associating voluntarily communes declaring the will of implementing the targets of the EU climate & energy frameworks on local levels (reaching the package 3  20) [9, 10]. Therefore, the problem concerning actions for renewable energy development on lower administrative levels seems to be an important question. The paper goal is to analyze initiatives and actions for renewable energy development in big cities in Poland, taken up by self-governments, following strategic documents, including low-carbon economy. The study was made basing on present RES structure and leading development directions in examined cities.

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2 Materials and Methods All data on renewable energy are collected in Poland by The Energy Regulatory Office (in Polish Urząd Regulacji Energetyki—URE), and in more generalized form by Local Data Bank of the Central Statistical Office (LDB CSO, in Polish Bank Danych Lokalnych Głównego Urządu Statystycznego—BDL GUS). Information obtained from the Base concerned mainly a number and kind of RES power plants and total installed capacity. Data from LDB CSO enabled to select cities for analyze. Taking into consideration the fact that large multifunctional cities generate the biggest challenges for energy sector transformation, 10 biggest Polish cities were appointed for the survey (cf. Fig. 1 and Table 1). They have population from 299,910 in Katowice to 1744,351 in Warsaw, and relatively high population density from 1765 in Gdansk to 3372 in Warsaw (cf. Table 1). Energy consumption per capita in these cities between 2005–2017 fluctuated around 645.81 in Bydgoszcz, up to 1000.76 in Cracow. It can be stated then that it is a representative group of cities, proper for studies on renewable energy development. We should point out that big cities, not only in Poland are growth centers, matching development tendencies, passed to other urban centers, and also rural areas. To evaluate self-governments action for RES development, one should study strategic documents of these cities. This question appears the most often in low-carbon economy plans (LCEP) of gminas (LAU2, NUTS5), between 2014– 2018. LCEP is a strategic document defining general target and detailed solutions leading to low-carbon economy on local level. It is obligatory, while applying for financial means from EU budget for 2014–2020 to raise the energy effectiveness in gminas obtained by, among the others, thermo-modernization of buildings, raising the share of RES, limiting public transport emission, etc. Final plans of low-carbon Fig. 1 Cities discussed in the paper located in the country (Source Author’s research)

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Table 1 Basic cities characteristics No.

City

Voivodeship

Population

2015

Population density (per 1 km2) 2015

1 Warsaw Mazowieckie 1744,351 3,372 2 Cracow Małopolskie 761,069 2,328 3 Lodz Łódzkie 700,982 2,390 4 Wroclaw Dolnośląskie 635,759 2,171 5 Poznan Wielkopolskie 542,348 2,071 6 Gdansk Pomorskie 462,249 1,765 7 Szczecin Zachodniopomorskie 405,657 1,350 8 Bydgoszcz Kujawsko-Pomorskie 355,645 2,021 9 Lublin Lubelskie 340,727 2,310 10 Katowice Śląskie 299,910 1,822 Source Own author’s draft basing on data from LDB CSO [11]

Electricity consumption (kWh per capita) Average 2005–2015 964.81 1000.76 824.86 840.01 829.61 872.43 734.61 645.81 696.77 842.45

economy are to contribute to reach targets defined in EU climate & energy package by 2020 (among the others: reducing greenhouse gases, raising the share of RES, energy efficiency and improving air quality).

3 Results 3.1

Renewable Energy in Big Cities of Poland

Poland has 2936 power plants producing energy from RES, with total capacity exceeding 8.5 GW, i.e. 8538,347 MW (state: 30th Sept. 2017). Comparing a number of RES power plants in big Polish cities, we observe their largest quantity in Katowice (17), the smallest number (5) in Lublin and Szczecin. The other aspect —city plants number is not directly proportional to total installed capacity, which is the highest in Warsaw—177.734 MW, while the lowest in Katowice 1.118 MW, hence—Katowice possessing many plants produce relatively small capacity (cf. Fig. 2). Analyzing types of RES power plants in Poland, we observe the biggest number of wind power plants, what was related with dynamic development of this kind of installations as a result of European funds for business activity. Wind farms are generally located in rural and suburban areas of northern, western and partially central Poland [7], which is conditioned by wind power and speed, land orography and the density of settlement network [13, 14]. Due to location limitations, the examined cities are nearly completely deprived of wind farms (with the exception of Gdansk with its wind power station—0.15 MW).

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MW 200 180 160 140 120 100 80 60 40 20 0

Fig. 2 Total installed capacity of RES power plants in big cities in Poland (state: 30th Sept. 2017) (Source Own authors’ survey on the base of URE data [12])

Solar energy power plants (42) are the most popular urban facilities. Solar cells (PV), i.e. devices using solar energy, are situated the most often in Katowice, and next in Warsaw (cf. Fig. 3). Their popularity in urban areas results from easy installing. Solar installations are located the most frequently on existing or just being erected building roofs. They do not require extra space and are composed into building architecture. As they base on solar energy, PV distinguish from other sources with the best public perception [7]. Significant concentration of these solutions in Katowice, and generally in the Upper Silesia (Katowice is the capital city of the region Upper Silesia) results from local concentration of firms distributing and installing the facilities using solar energy. It should be remarked that power produced in urban installations is low, from 0.006 MW in Poznan to 1.118 MW in Katowice (cf. Table 2). Next popular RES power plant type are facilities producing biogas of sewage treatments and they are located in nearly all studied cities, with Katowice exception. Total installed power balances between 0.938 MW in Szczecin to 6.653 MW in Warsaw (cf. Table 2). As Szymańska and Lewandowska observe [15], in 2013 Poland reported 231 biogas power plants, 102 of which produced gas of municipal solid waste (44%), 85 produced gas from sewage treatments (36%), and 42 worked basing on agricultural substrates (biogas plants—in last year’s anaerobic digestion power plants increasing numbering almost up to 100 [4]) and 2 mixed biogas plants. In 2017 their number in Poland increased to 305, majority of which were biogas plants and plants producing biogas of sewage treatment (the last ones are in majority at present, comparing to other types). Biogas plants situated with sewage treatments development is a result of introducing in Poland in 2016 regulations forbidding storing sewage sludge (from the treatment), containing more than 6% of organic mass [16]. The sludge is perfect material for biogas production. Restrictions in storing sludge resulted in more profitable biogas plants installing within the area of

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16 14 12 10 8 6 4 2 0

A

B

C

D

E

F

G

H

I

J

Fig. 3 Number of RES power plants in big cities in Poland (state: 30th Sept. 2017). Explanations: A—producing from biogas of sewage treatment, B—from landfill gas, C—from mixed biomass, D —from biomass of municipal solid waste, e.g. sewage treatment, E—onshore wind power plant, F —hydro power plant up to 0.3 MW, G—hydro power plant up to 1 MW, H—hydro power plant up to 5 MW, I—using co-firing technology (fossil fuel and biomass), J—using solar energy (Source Own authors’ survey on the base of URE data [12])

sewage treatment plants. The gas produced locally is usually used for technological processes of the facilities, and only sometimes its excess is sent to central energy system [17]. Changes in the field, supported by adequate legislation depict modern world trends of social-economic development referring to circular economy [18]. The highest installed power is characteristic for plants working on mixed biomass and the plants are located in half of cities analyzed here—with power from 0.95 MW in Gdansk to 170 MW in Warsaw. Power produced by plants working on biomass obtained from municipal solid waste amounts 16.9 MW in Cracow and 18 MW in Poznan (cf. Table 2). Polish cities and not only report also hydro power plants up to 1 MW, usually of small capacity. Their situating depends of course on environmental conditions; cities located on rivers create possibilities of this kind of investment. Bydgoszcz has the most hydro plants (5), Szczecin—4 (cf. Fig. 3). Small hydro plants functioning is desirable not only due to energy production, but also in the context of effective water management of the area and industrial tourism development.

Warsaw 6.653 Cracow 2.157 Lodz 2.799 Wroclaw 1.803 Poznan 2.121 Gdansk 2.864 Szczecin 0.938 Bydgoszcz 1.490 Lublin 1.702 Katowice Explanations: see Fig. 2 Source Own authors’ survey on

A

63.000 0.950 76.000

59.000

170.000

C

the base of URE data [12]

1.150

0.520 1.908

1.341

B

18.000

16.900

D

0.150

E

0.207 0.145

0.074

F

4.000

6.400

G

Table 2 Installed capacity into the types of RES power plant in the big cities in Poland (state: 30th Sept. 2017)

1.380

1.108

H

0.000

0.000 0.000 0.000 0.000 0.000

I

1.080 0.129 0.610 0.017 0.006 1.686 0.100 1.200 0.074 1.118

J

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Table 3 Comparative studies of low-emission economy plans in big cities of Poland in the context of RES implementation City

Year of the document passing

Role of renewable energy in PGN

References in low-emission economy plan

Increase in RES final energy consumption to the level of 3 819 970 MWh by 2020 Cracow 2017 Increase in energy produced in high-efficiency cogeneration and renewable energy Lodz 2017 Strategic target Increase in participation of renewable energy of 0.12% (23 090,00 MWh/a year) in the area of Łodz by 2020, comparing to basic year 2013 Wroclaw 2014 Detailed target Increase by 2020 participation of renewable energy up to 15% in final energy consumption Poznan 2014 Detailed target Increase of renewable energy participation in general energy balance up to 2.3% by 2020 and to 3.5% by 2040 Gdansk 2015 Detailed target 20% renewable energy participation in energy balance Szczecin 2015 Strategic target Increase in using renewable energy sources Bydgoszcz 2016 Detailed target Increase in using renewable energy sources by 2020 to at least 3% (136 120 MWh) in final energy use Lublin 2015 Detailed target Increase in RES from 2.8% to 16.92% comparing to basic year 2008 Katowice 2018 Strategic target Increase in using RES Increase and using RES productivity Source Own authors’ survey basing on low-emission economy plans [19–28] Warsaw

2015

Additional strategic target Detailed target

Discussing particular types of power plants, we should also concentrate on the ones using co-firing technologies, based on fossil fuels and biomass, as they appear in 6 of 10 analyzed cities (cf. Fig. 3). Biomass co-firing is the cheapest and the quickest way of RES introducing to energy diversification, because it bases on existing infrastructure, it does not require any extra investments or modernizing technology. Technological process itself—co-firing—is not perceived univocally, however, due to its impact on natural environment. Therefore, its dissemination is rather controversial and we observe reduction of co-firing technology in Poland. Summing this problem up, we observe that presenting a number and locations of plants using renewable energy resources is not compatible with total power installed. Some RES are characteristic for big facilities, i.e. biomass, and for instance PV refers to relatively small installations producing small energy quantity.

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Self-governments Action for RES Development

To observe successes in renewable energy development we must be sure that the impulse from country administration level in forms of general action directions in energy sector is implemented on local levels. These are self-governments which are equipped with proper tools stimulating the development and using RES. These actions are reflected in strategy documents, in low-carbon economy plans. Analyzing information on RES from LCEP we clearly observe the contrariety in defining, if RES urban development is regarded as strategic or detailed target (cf. Table 3). In majority of cities it was classified as detailed target. Starting comparisons of the development with low-carbon economy plans we observe that in Warsaw, e.g., the increase of final RES consumption to 3819,970 MWh by 2020 was approved as an additional strategic target. Furthermore, in the document of auxiliary detailed target ‘Świadome społeczeństwo’ (Aware Society) it was accepted to take up social awareness raising campaigns concerning problems of climate changes and environment protection, and change of inhabitants behavior, to promote raise in effectiveness in energy consumption and RES use, as well as air quality improvement. Particular actions planned for LCEP implementation contained financial support for RES, promoting energy effectiveness. In Cracow the Plan of low-carbon economy is set to contribute to reach climate improvement and sustainable consumption of energy defined in the Strategy “Europe 2020”, i.e. raise the share of RES or high-efficiency cogeneration. It is one of detailed targets approved by Cracow, referring to target of EU. Particular actions supporting the program were appointed: installing solar installations and heat pumps within the Program for Low-carbon economy for the Municipality of Cracow from 2014, installing lighting for school sports fields using solar energy, installing PV on bus roofs and building solar farms. Lodz formed detailed strategic target basing on EU climate & energy package, emphasizing raising the share of RES of 15%, what was estimated as increase of RES of 0.12% (23,090.00 MWh/a year) in urban area by 2020, comparing to the base year 2013. Detailed target is supporting and distributing energy of renewable energy facilities—PV, solar collectors, heat pumps, and the action towards protecting natural environment of Lodz by installing RES. Wroclaw also answering to EU climate & energy package approved detailed target of increasing by 2020 renewable source energy to 15% in final energy consumption. Using scattered urban RES is also desirable task. Poznan did not define directly strategic LCEP target, referring only to general directives concerning raise in RES participation. Detailed targets were specified in increasing RES participation in general energy balance to 2.3% by 2020 and to 3.5% by 2040, which can be achieved thanks to using RES in various forms (particularly solar and geothermal energy, bio-fuel) and building and modernizing facilities serving for energy and heat obtained from renewable sources of energy distribution, using external stakeholders.

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In Gdansk, LCEP target referred to EU 3x20 package, however, not meeting exact actions for raising the share of renewable energy in the city. Plans for low-carbon economy in Szczecin put forward RES consumption as one of strategic target. Detailed targets include supporting production and distribution of energy coming from RES in the urban area, planning and financing facilities installing in public buildings of the city, as well as creating economic and administrative encouragement for building RES in city objects. Bydgoszcz approved RES share by 2020 up to at least 3% (136,120 MWh) in final energy consumption, reduced by energy consumption decrease effect, as a detailed target. Completing urban plans for 2020, Bydgoszcz authority policy assumes reaching maximum use of technical potential of urban renewable energy. Lublin approved detailed target of raising the share of RES from 2.8% to 16.9% in comparison to the base year 2008. Six LCEP priorities included, among the others: production and distribution energy, coming from renewable/alternative sources, building PV, installing others renewable energy facilities, building new and modernizing existing facilities using biogas and facilities using biomass for energy production. Katowice see its strategic target in raising RES share and increase in effectiveness of using/producing energy from RES, to be completed by both pilot investments and promotion/education of inhabitants and investors. High participation of RES strengthens energy self-sufficiency of the city influencing economic, ecological and energy security.

4 Summary The analyses revealed that two European documents were the base for working on low-carbon economy in Poland, and these are: Europe 2020 Strategy and the Renewable Energy Directive. Generally all studied cities see their chance in thermo-modernization and increasing role of public transport to complete LCEP targets, while implementing RES as the method for obtaining low-carbon economy is treated rather as additional factor (with the biggest interest reported in Warsaw). Other cities with RES key role are: Lodz, Szczecin and Katowice, where RES development was set as strategic LCEP objective. The remained studied cities defined using RES as detailed targets, with lower rank of LCEP sectors. Lack of precision in approved directives concerning, both: kinds of RES as promoted in a city, and details, concerning energy capacity or deciding between electricity or thermal energy, is symptomatic in the survey. Avoiding decisions is probably deliberate tactics, which enables to complete the directives in the best possible way in present situation, depending on current economy condition, accessible funds, local society opinion and other factors. It is also significant that it was a kind of subject preparing low-carbon economy plan for a city, which decided on significance of RES in strategic documents. The

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survey shows that not any uniform structure of LCEP document exists, therefore all kinds of consulting firms are responsible in practice for defining such documents and they decide, if RES development is perceived as strategic target or only as one of many tasks within LCEP. Due to this fact, there is a necessity of unifying all LCEP forming process and working out conception of renewable energy in urban areas as determinant of low-carbon economy transformation. Acknowledgements This work was supported by the National Science Centre of Poland [grant numbers 2015/19/N/HS4/02586].

References 1. M. Leźnicki, A. Lewandowska, Contemporary concepts of a city in the context of sustainable development: perspective of humanities and natural sciences. Problemy ekorozwoju 11(2), 45–54 (2016) 2. D. Szymańska, M. Korolko, E. Grzelak-Kostulska, A. Lewandowska, Ekoinnowacje w miastach (Wydawnictwo Naukowe UMK, Toruń, 2016) 3. C.F. Calvillo, A. Sánchez-Miralles, J. Villar, Energy management and planning in smart cities. Renew. Sustain. Energy Rev. 55, 273–287 (2016). https://doi.org/10.1016/j.rser.2015. 10.133 4. J. Chodkowska-Miszczuk, M. Kulla, L. Novotný, The role of energy policy in agricultural biogas energy production in Visegrad countries. Bull. Geogr. Socio-econ. Ser. 35, 19–34 (2017). https://doi.org/10.1515/bog-2017-0002 5. G.H. Kats, Energy options for Hungary a model for Eastern Europe. Energy Policy 19(9), 855–868 (1991). https://doi.org/10.1016/0301-4215(91)90011-c 6. S. Buzar, Energy Poverty in Eastern Europe. Hidden Geographies of Deprivation (Ashgate Publishing Company, Burlington, 2007) 7. J. Chodkowska-Miszczuk, J. Biegańska, S. Środa-Murawska, E. Grzelak-Kostulska, K. Rogatka, European Union funds in the development of renewable energy sources in Poland in the context of the cohesion policy. Energy Environ. 27(6–7), 713–725 (2016). https://doi.org/ 10.1177/0958305x16666963 8. S. Ruester, S. Schwenen, M. Finger, J.M. Glachant, A post-2020 EU energy technology policy: revisiting the strategic energy technology plan, in EUI Working Paper RSCAS, vol. 39, San Domenico di Fiesole: European University Institute, Robert Schuman Centre for Advanced Studies, Florence School of Regulation (2013) 9. M.R. Jabłońska, J.S. Zieliński, Rozwój odnawialnych źródeł energii na poziomie gminy. Śląskie Wiadomości Elektryczne 4(97), 22–25 (2011) 10. M. Burchard-Dziubińska, Gospodarka niskoemisyjna w mieście, in ed. by A. Rzeńca EkoMiasto# Środowisko. Zrównoważony, inteligentny i partycypacyjny rozwój miasta, Wydawnictwo Uniwersytetu Łódzkiego, Łódź (2016) 11. Local Data Bank of the Central Statistical Office, https://bdl.stat.gov.pl/BDL/dane/podgrup/ temat. Accessed 07 June 2018 12. Energy Regulatory Office, https://www.ure.gov.pl/en/. Accessed 10 June 2018 13. J. Chodkowska-Miszczuk, Odnawialne źródła energii i ich wykorzystanie jako nowe trendy na obszarach wiejskich w Polsce (Renewable energy sources and their use as new trends in rural areas in Poland). Studia Obszarów Wiejskich XXXV (2016), pp. 227–240

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14. B. Ryszkowska, T. Starczewski, J. Chodkowska-Miszczuk, Rozwój energetyki wiatrowej w przestrzeni submiejskiej a percepcja krajobrazu kulturowego. Acta Sci. Polonorum 17(1), 63– 74 (2017) 15. D. Szymańska, A. Lewandowska, Biogas power plants in Poland—structure, capacity, and spatial distribution. Sustainability 7(12), 16801–16819 (2015) 16. J.D. Bień, B. Bień, Zagospodarowanie komunalnych osadów ściekowych metodami termicznymi w obliczu zakazu składowania po 1 stycznia 2016. Inżynieria Ekologiczna 45, 36–43 (2015) 17. W. Gostomczyk, State and prospects for the development of the biogas market in the EU and Poland–economic approach, in Zeszyty Naukowe Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie Problemy Rolnictwa Światowego 2017 (XXXII), vol. 2 (2017), pp. 48–64. https://doi.org/10.22630/prs.2017.17.2.26 18. D. Szymańska, M. Korolko, J. Chodkowska-Miszczuk, A. Lewandowska, Biogospodarka w miastach (Wydawnictwo Naukowe UMK, Toruń, 2017) 19. Low-emission economy plan for the city of Warsow. Urząd miasta stołecznego Warszawa, Warszawa (2015) 20. Low-emission economy plan for the city of Cracow. Update. Urząd miasta Kraków, Kraków (2017) 21. Low-emission economy plan for the city of Lodz. Urząd miasta Łodzi, Łódź (2017) 22. Low-emission economy plan for the city of Wrocław. Urząd miasta Wrocław, Wrocław (2014) 23. Low-emission economy plan for the city of Poznan. Stowarzyszenie Metropolia Poznań, Poznań (2014) 24. Low-emission economy plan for the city of Gdansk Metropolitan Area. Obszar Metropolitarny Gdańsk, Gdynia, Sopot, Gdańsk (2015) 25. Low-emission economy plan for the city of Szczecin. Urząd miasta Szczecina, Szczecin (2015) 26. Updated action plan for sustainable energy – low-emission economy plan for the city of Bydgoszcz for 2014–2020+. Urząd miasta Bydgoszcz, Bydgoszcz (2016) 27. Low-emission economy plan for the city of Lubin. Urząd miasta Lublin, Lublin (2015) 28. Low-emission economy plan for the city of Katowice – update. Urząd Miasta Katowice, Katowice (2018)

Economic Analysis of Domestic Hot Water Preparation Using Air-Source Heat Pump Wojciech Luboń, Grzegorz Pełka and Beata Krężołek

Abstract The heat pump as an ecological solution can be an option for using conventional hot water preparation. The article presents an economic analysis of domestic hot water (DWH) preparation using an air-source heat pump. The operation of the heat pump and the consumption of electricity during the one-time heating of the hot water tank were analysed. The test was carried out under real conditions. Basic parameters and test conditions were based on European Standard EN 16147:2017. Fuel and electricity prices have been determined for available energy tariffs and fuel prices in the region. Different configurations of energy tariffs were taken into account to analyse costs of DHW preparation using heat pump. Obtained costs were compared with the costs of DHW preparation using conventional heat sources: a gas boiler and an automated coal-fired boiler. Annual cost comparison were presented. The results show that average Coefficient of Performance (COP) of the heat pump working under real conditions is 2.06. The most expensive heat source for DHW heating is heat pump which works during a 24-h tariff and the best economic solution is heat pump using 100% night tariff. However, annual costs of DHW preparation are still equal to the cost of DHW preparation using gas boiler. Keywords Heat pump


Hot domestic water

1 Introduction Currently, in heating techniques are mainly used conventional energy sources. However, the growing problem of environmental pollution causes searching solutions with minimal impact on the environment. The households are largely responsible for low emission problem, which is why various subsidies for ecological W. Luboń (&)
G. Pełka
B. Krężołek Faculty of Geology, Geophysics and Environmental Protection, Department of Fossil Fuels, AGH University of Science and Technology, Mickiewicz Ave. 30, 30-059 Krakow, Poland e-mail: [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_88

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energy sources or replacement of old boilers are created. In addition, as a member of the EU, Poland is committed to achieving the climate and energy package objectives by 2020, i.e. increasing the share of energy from renewable sources and reducing greenhouse gas emissions [1]. Such aspects cause the search for alternative and economic solutions. The heat pump as an ecological and comfortable solution can be an option for using conventional solid-fuel boilers. In compressor heat pumps, the combustion process does not take place, and the emission of pollutants into the air in the place of its application does not occur. The only emission is related to the method of electricity production that is necessary to drive the compressor [2]. The relative easy installation and falling prices [3] cause a large increase in interest in air-source heat pumps, especially for preparing domestic hot water.

2 Methodology of Research 2.1

Measuring Position

The subject of the research was Galmet Easy Air 2GT air-source heat pump for domestic hot water preparation. The heat pump is installed in a single-family house since 2009 and it is located inside the building on the ground floor in the boiling room. The maximum temperature of water that the heat pump can prepare is 55 °C, the average heating power is 1.92 kW. The heat pump is integrated with a hot water tank with a capacity of 250 l. It also has a heat exchanger to which an additional heat source (gas boiler) is connected [4] (Fig. 1).

Fig. 1 Galmet Easy Air 2GT heat pump [4]

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Measurement Methodology

The test was carried out under real conditions. The basic rules of measurement and test conditions were taken from the European standard EN 16147: 2017.: • initial temperature of water in the tray: 10 °C, • indoor air temperature as a heat source: 20 °C, • ambient temperature of the heat pump: 20 °C [5]. The heating time and the corresponding amount of electricity consumed were measured from the pump being switched on until it was turned off by the hot water thermostat in the storage tank when the temperature of 55 °C was reached. In order to determine the amount of electricity consumed by the heat pump during the water heating, a simple electricity meter was used to plug into the electrical socket to which the heat pump was connected. The water temperature in the tank was read from the heat pump display. Measurements were read every 15 min.

2.3

Calculation Methodology

Comparison to other heat sources was made with assumption that each of the considered heat sources will prepare the same amount of hot water, corresponding to the storage capacity V = 250 dm3. The values needed to calculate the energy demand for heating domestic hot water was as following [6]: • • • •

initial temperature t1 = 10°C final temperature t2 = 55°C specific heat of water cw = 4.2 kJ/kg*K water density q = 1 kg/dm3.

Energy demand for domestic hot water for all cases was calculated using formula: Q ¼ V
q
cw
ðt2 t1 Þ ¼ 47:25 MJ  13 kWh

ð1Þ

Energy prices was based on the analysis of bills for the building and tariffs available on the distributors’ websites. All energy prices for compared heat sources are presented in Table 1. The electricity price for the Małopolska region in the G11 tariff was adopted at the level of 0.579 PLN/kWh. This price includes all fees: the selling price 0.2983 PLN/kWh; distribution rates: variable fees 0.2343 PLN/kWh, fixed fees in the amount of 12.85 PLN/month; 6-month circle fee 0.98 PLN/month; the RES fee in the amount of 0.0037 PLN/kWh [7]. In the case of the tariff G12- with the division into zones, the rates were adopted according to the available offer [8], referring to the average energy consumption by

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Table 1 Energy prices for compared heat sources Energy price [PLN/kWh] G11 tariff 24 h 0.579

G12 tariff Zone II-night 0.302

Zone I-day 0.657

Zone I/zone II 50/50 0.479

Gas price [PLN/kWh]

Coal price [PLN/kWh]

W-3.6 tariff

–

0.212

0.173

the household members. The price for the zone II was specified as 0.3015 PLN/ kWh, for the zone I: 0.6571 PLN/kWh. These rates include the selling price: night —0.1894 PLN/kWh, day—0.3677 PLN/kWh; distribution rates: variable fees night —0.0621PLN/kWh, day—0.2395 PLN/kWh and fixed fees in the amount of 16.61 PLN/month; 6-month cycle fee 0.98 PLN/month; the RES fee 0.0037 PLN/ kWh [8]. In the case of water heating and pump operation in 50% using the cheaper night zone energy and 50% in the day zone, the average from the night zone and day zone rates was 0.479 PLN/kWh. For the gas price was calculated on the basis of the available bills of the two-month period according to PGNiG company for W-3.6 tariff and it is 0.212 PLN/kWh [9]. It includes charges for gaseous fuel equal to 0.0939 PLN/ kWh, distribution fees: variable 0.0292 PLN/kWh and fixed—34.78 PLN/month net and fee in the amount of 6.28 PLN/month [10]. In order to determine the price of energy for 1 kWh for coal, the cost of a coal in the amount of 900 PLN/ton and a fuel calorific value of 25 MJ/kg were assumed. The boiler efficiency equal to 75% for modern solid fuel boilers [11] was also taken into account. The calculated cost is 0.173 PLN/kWh. In the calculations of operating costs, standby losses and service costs of the heating devices was not taken into account. The values of the COP coefficient determining the heat pump efficiency were calculated on the heat production and electricity consumption by heat pump.

3 Results During the test, the heat pump reached the set temperature of 55 °C after 6 h 30 min from the start of the heating process. The total electricity consumption at this time by the heat pump was 6.37 kWh. The average COP was 2.06. Table 2 shows the average heating power of the device and the calculated COP depending on the achieved temperatures of water. It can be noticed that the heating power of the heat pump decreases with the increase of the set water temperature, which at the same time causes a decrease of the heat pump’s efficiency factor. The Fig. 2 shows the rate of increase in the temperature of heated water in the tank, depending on the time of operation of the heat pump. It can be seen that in the

Economic Analysis of Domestic Hot Water Preparation … Table 2 Heating power of the device and the calculated COP

923

Temperature

Heating power of the heat pump [kW]

COP

10–20 20–30 30–40 40–50 50–55

2.33 2.33 1.94 1.94 1.75

2.75 2.52 1.99 1.81 1.36

initial heating phase the temperature rises faster. For example, the time for heating water from 10 °C to 20 °C and from 20 to 30 °C is 1 h 15 min, while from 30 °C to 40 °C and from 40 °C to 50 °C is 1 h 30 min. Beside the increasing time needed to heat water by next DT = 10 °C, the unitary electricity consumption per each 1 °C increase in temperature, also increases. This has a direct impact on the costs. According to a total electricity price of 0.579 PLN/kWh in 24-h tariff, the costs for heating water with a heat pump from 10 to 20 °C are 0.61 PLN, 20 to 30 °C— 0.68 PLN; from 30 to 40 °C—0.84 PLN; from 40 to 50 °C-1.02 PLN; and the last 5 °C of water temperature increase cost 0.54 PLN (Fig. 1). It is worth to notice that the house is inhabited by a family of four, and the daily consumption of hot water for one person is 50 dm3 [12] for water at 50 °C [13]. DHW tank has a capacity of 250l and the intensity of water consumption is not large. In this case, the reduction of DHW preparation costs may take place by lowering the set water temperature in the storage tank. For example, by reducing the

Water temperature increase depending on the heat pump operating time

60 55 50 Temperature [oC]

45 40 35 30 23

25 20 15

16 10

18

25 26

28

30

32

34 35

37

39 40

42 43

45 46

52 53 50 51 48 49

55

20

12 13

Fig. 2 Water temperature increase depending on the heat pump operating time

06:15

06:30

05:45

06:00

05:30

Time [h]

05:40

05:00

05:15

04:45

04:30

04:00

04:15

03:45

03:15

03:30

03:00

02:45

02:15

02:30

01:45

02:00

01:30

01:15

00:45

01:00

00:30

00:00

00:15

10

924

W. Luboń et al.

One-time cost of heating of the DHW tank by heat pump 4.00 3.50 3.00

Cost (G11 24-hour tariff)

Cost [PLN}

2.50 2.00 1.50 1.00 0.50 0.00

10 13 18 23 26 30 34 37 40 43 46 49 51 53 Temperature [oC]

Fig. 3 One time cost of heating DHW tank by heat pump

temperature of heated water to 50 °C, the heat pump will work more efficiently, the losses will be lower and the heating costs of 250 l of water will reduced from 3.69 PLN to 3.15 PLN (Fig. 3). The comparison of water heating costs for different heat sources is presented in Fig. 4. The most expensive heat source turned out to be a heat pump using electricity purchased in a 24-h tariff, then a heat pump using 50% energy from the cheaper zone II-night and 50% energy from zone I-day in G12 tariff. The cost of DHW preparation by coal boiler is lower than heating water by gas boiler. The best economic solution is heat pump powered with 100% of electricity purchased in the night zone of the G12 tariff. The most advantageous economic solution is a heat pump powered with 100% of electricity purchased in the night zone of the G12 tariff. Thanks to the large water tank, it is possible to accumulate enough heat by heating the water in the night tariff. Considering the fact that a condensation gas boiler is installed in the house, not only for heating the house, but also for DHW heating, because it is connected to a hot water tank, a more favourable economic solution, compared to heating the hot water tank. in G11 tariff, there will be water heating using gas fuel. To prepare DHW with a heat pump, change of the tariff to G12 divided into day and night zone should be considered. The annual consumption of electricity by the heat pump and household members was presented in Table 3. Annual costs depending on the type of tariff were compared. After multiplying the value of electricity required to the heat pump compressor operation (6.37 kWh) by the number of days per year (365 days) the

Economic Analysis of Domestic Hot Water Preparation …

925

Table 3 Annual consumption of electricity Type of electricity consumption

Annual electricity consumption [kWh/year]

Annual costs [PLN/year] G11 G12 tariff tariff

Household members Heat pump Sum

4656

2694

3059

2325 6981

1345 4039

701 3761

The difference in costs [PLN/year]

279

annual energy demand to prepare hot domestic water by heat pump amounted to 2325 kWh. The annual energy consumption by household members for daily activities calculated according to received invoices was 4656 kWh [14]. Assuming electricity consumption by residents during the daily tariff, and energy consumption by the heat pump during the night tariff, it can be expected a reduction in annual costs of electricity by about 279 PLN in relation to staying at a 24-h tariff. Additional savings can be achieved by planning the work of devices as a washing machine or a dishwasher during the night tariff.

4 Summary This paper presents the study of an air heat pump for preparing domestic hot water under real conditions. An analysis of the obtained results was carried out in order to determine the consumption of electricity and the cost of preparing domestic hot water by the air-source heat pump. The results were compared with the costs of DHW preparation by other selected heat sources. According to the adopted assumptions and energy costs (Table 1), the most economical solution for domestic hot water preparation in the tested case is heat pump powered by electricity purchased in the zone II of the G12 tariff (Fig. 4). Measured conditions of the heat pump work, like high energy consumption by the compressor and low COP, cause high operating costs compared to other conventional heat sources. Despite the change to the tariff with division into zones, in relation to gas, in the annual settlement, the costs of DWH preparation will be similar. Taking into consideration the investment and service costs of the additional device which were not included in the analysis, the choice of the hot water heating solution with a air-source heat pump, in this case, turned out to be economically unfavourable. In spite of the lack of economic justifications for using a heat pump for the tested case, it is worth noting that currently produced heat pumps for hot water preparation have higher efficiency ratios and the costs of preparing hot domestic water by an air-source heat pump can be respectively lower.

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Comparison of 250l DHW preparation by different heat sources

4.00

3.69

3.50 3.05 3.00

2.78

PLN

2.50

2.27 1.92

2.00 1.50 1.00 0.50 0.00

HP 24-h

HP zone II

HP zone II/zone

gas boiler

coal boiler

I 50/50 Fig. 4 Comparison of 250 l DHW preparation by different heat sources

Acknowledgements The paper was prepared under AGH-UST statutory research grant No. 11.11.140.031.

References 1. A. Grabos S. Zymankowska – Kumon, J. Sadlok, R. Sadlok, Przeciwdziałanie niskiej emisji na terenach zwartej zabudowy mieszkalnej. Stowarzyszenie na rzecz efektywności energetycznej i rozwoju odnawialnych źródeł energii („HELIOS” 2014) 2. W. Lubon, G. Pełka, J. Kotyza, D. Malik, Design and development of a didactic and research stand for exploitation tests under defined conditions, in Renewable Energy Sources: Engineering, Technology, Innovation: ICORES 2017 (20 June 2017–23 June 2017, Krynica Zdroj, Polska 2018) 3. G. Pelka, W. Lubon M. Szczygiel, The analysis of parameters of heating—cooling installation with ground source heat pump in heating and passive cooling mode, Geological explo-ration technology—Geothermics, Sustainable development (Poland, 2011) 4. GALMET, Technical documentation, s. 35–42 5. EN 16147.2017 Heat pumps with electrically driven compressors—testing, performance, rating and requirements for marking of domestic hot water units 6. G. Krzyżaniak, Analiza opłacalności podgrzewania ciepłej wody użytkowej za pomocą pomp ciepła, „Chłodnictwo”, tom XLII, 2007, nr 5, s. 24–29 7. https://www.tauron.pl. Tariff G11 8. https://www.tauron.pl. Tariff G12 9. PGNIG company, Invoice for gas fuel 10. www.pgnig.pl. Tariff

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11. G. Pełka, W. Luboń, B. Ciapała, A. Drabik, The analysis of operational costs for selected heat sources for domestic hot water (DHW) beyond the heating season. “CIEPŁOWNICTWO, OGRZEWNICTWO, WENTYLACJA”, 48/8, 2017, s. 315–318 12. U. Dz, Rozporządzenie Ministra Infrastruktury i Rozwoju z dnia 14 stycznia 2002r. w sprawie określenia przeciętnych norm zużycia wody, nr 8 poz. 70 (2002) 13. U. Dz, 2014 nr 0 poz. 888: Rozporządzenie Ministra Infrastruktury i Rozwoju z dnia 3 czerwca 2014r., w sprawie metodologii obliczania charakterystyki energetycznej budynku i lokalu mieszkalnego lub części budynku stanowiącej samodzielną całość techniczno-użytkową oraz sposobu sporządzenia i wzorów świadectw charakterystyki energetycznej 14. Tauron, Invoice for electricity

Effectiveness of Capital and Energy Expenditures in Organic Production Urszula Malaga-Toboła, Maciej Kuboń, Dariusz Kwaśniewski and Pavol Findura

Abstract Capital and energy effectiveness in organic production is similar to the one achieved in a traditional system, although it generally has a lower consumption of production and energy means. This consumption depends, however, on the applied technology, size, direction and manner of management. Since, implementation of new technologies and techniques in plant and animal production causes that farms obtain better and better indices of capital and energy effectiveness of their production. In the paper, the production size and consumption of energy carriers and raw materials for production purposes in organic farms was estimated. Effects of the obtained global and commodity production and expenditures incurred thereon presented in energy units enabled determination of capital and energy effectiveness of organic production and its energy consumption. A comparative analysis of the calculated indices was carried out, assuming a division criterion in the form of the surface area of agricultural land.







Keywords Organic farms Global production Commodity production Expenditures Energy effectiveness Energy consumption










1 Introduction In intensive farm production systems the basic purpose is to maximize effects through implementation of industrial production methods that require high material and energy expenditures [1–4]. Organic production, on the other hand, is based on the rational use of those expenditures, in a saving manner and productively using human work resources and production means. Capital and energy effectiveness in

U. Malaga-Toboła (&)
M. Kuboń
D. Kwaśniewski University of Agriculture in Krakow, Krakow 30-149, Poland e-mail: [email protected]; [email protected] P. Findura Slovak University of Agriculture in Nitra, Nitra 949 76, Slovakia © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_89

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organic production is close to the one achieved in the traditional system, although, it generally has a lower consumption of production and energy means [5–11]. Although, this consumption depends on the applied technology and size, farming trend and method [12, 13]. High prices of energy carriers and their increasing consumption for production purposes, which according to the forecasts, will increase in 2020 by 30–40% somehow but enforce further rationalization of the size, trend and production manners both with regard to energy saving and farming profitability [14, 15]. Material and energy inputs incurred in the particular farm on agricultural production decide on the costs of this production, on the agricultural income and the level of remuneration for the farmer’s and farmer’s family work [16–18].

2 Aim, Research Area and Methods Organic farming using the technologies based on natural, technologically non-processed production means obtained lesser production but at the same time incurring less capital expenditures. As many specialists emphasise, the size of this consumption is affected by both the size and type of the performed activity. Thus, the purpose of the paper was to determine effectiveness of capital and energy expenditures incurred on organic production in farms with varied surface area. The research was carried out in the form of a guided survey with farm owners. The collected information concerned their agricultural activity and allowed calculation of production energy consumption and indices which allow assessment of the efficiency of the incurred capital and energy expenditures. The scope of the research covered 50 certified farms located in the southern Poland. All objects had a certificate that confirms the organic nature of the performed activity. In order to carry out a comparative analysis, the objects were divided into four area groups i.e. up to 5 ha; from 5.01–10.00 ha; from 10.01– 20.00 ha and above 20 ha. The number of farms qualified to a particular group was respectively: 12, 17, 12 and 9. Capital and energy effectiveness of organic production activity was determined as a relation of the obtained global and commodity production to expenditures incurred thereon, expressed in energy units. Energy consumption, on the other hand, is reverse to effectiveness. The results were obtained during a 3-year research carried out in the said farms. Capital and energy expenditures were calculated according to Wójcicki method (2014) as a sum of farm, non-farm products, i.e. fertilizers and other agrochemicals, fuel, oil, smear and electric energy, materials incurred on the repair of machines and buildings, technical services, replacement investments and own and hired work [19, 20]. For estimation of the obtained production and incurred expenditures in energy units conversion factors of these contractual units were used [21]. In case of replacement investments, materials and services and non-agricultural production,

Effectiveness of Capital and Energy Expenditures …

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conversion of the monetary value into energy values in the relation of 150 PLN GJ−1 was applied, resulting in simplification from the value of grain and milk.

3 Research Results and Discussion The average area of agricultural land in the investigated farm was 12.61 ha. In the use structure of land, slightly over a half (51.3%) consisted of permanent grassland, arable land constituted 41.7% of agricultural land and orchards and perennial plantations −4.0% (Table 1). In case of area groups, farm up to 10 ha had a decisively more arable land and in case of bigger objects, grasslands prevailed. The investigated farms at the average maintained 11.55 LSU which calculated into a unit of the field surface area gave 0.92 LSU ha−1. The number of livestock was at the level of 4.21 LSU in the smallest farms to 24.07 in the biggest farms. However, referring to the surface area of agricultural land, the biggest farms had the lowest livestock which was only 0.51 LSU ha−1. Farms with the acreage up to 10 ha had the biggest number of animals. At the average 67.88 GJ of energy carriers were consumed in the investigated objects. The highest consumption concerned diesel oil and electric energy which in the energy inputs structure constituted respectively 55.1 and 42.5% Consumption of those two energy carriers proved a raising trend along with the increase of the agricultural land surface area and was at the level of 12.620 to 50.841 GJ in case of electric energy and from 12.782 to 63.124 GJ in case of diesel oil (Table 2). Hard coal for production purposes was consumed only by farms with the surface area up to 10 ha and diesel oil—from 10 to 20 ha. From among agricultural raw materials the highest consumption was in case of fodders (84.5%) including bulky feed 53.1% and concentrates—32.0% (Table 3).

Table 1 Organization of agricultural production Specification

Number of farms

Area (ha) Agricultural land

Livestock Arable land

Permanent grassland

Orchards and perennial plantations

(LSU)

(LSU ha−1)

Area group Up to 5 ha

12

3.33

2.02

0.53

0.78

4.21

0.92

5.01–10.00 ha

17

6.90

4.21

1.99

0.70

8.57

1.11

10.01–20.00 ha

12

15.05

6.77

7.98

0.30

18.97

0.74

Above 20.00 ha

9

31.80

9.94

21.82

0.04

24.07

0.51

50

12.61

5.27

6.47

0.51

11.55

0.92

Average

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Table 2 Consumption of energy carrier (GJ) Specification

Electric energy

Diesel oil

Leaded patrol

Fuel oil

Hard coal

Area group Up to 5 ha 5.01–10.00 ha 10.01–20.00 ha Above 20,00 ha Average

12.620 21.092 39.591 50.841 28.853

12.782 26.646 57.901 63.124 37.386

2.298 1.301 0.332 1.461 1.336

– – 1.274 – 0.306

0.002 0.002 – – 0.001

Their energy value was in total 128.279 GJ. In case of sowing material, seedlings and the remaining raw material, including young livestock and milk, the biggest farms were decisively different. They consumed several times more than farms with a smaller surface area. Consumption of concentrates was comparable in the said groups, while bulky feed significantly increased in objects with the surface area up to 10 ha. Moreover, it was noted that decisive amount of agricultural raw materials came from own farm (Fig. 1) which is in accordance with the generally assumed organic farming principles. At the average, own inputs, which are, the co-called, internal turnover constituted 83%. In the structure of non-agricultural raw materials, the highest number (86.6%) constituted fertilizers admitted to use in the investigated organic farms, the energy value of which was 9.469 GJ (Table 4). Their highest input was reported in farms with the acreage from 10 to 20 ha. It was decisively higher in comparison to the remaining area groups. The highest number of agrochemical substances expressed in GJ was applied by farms with the acreage from 5 ha and from 10 to 20 ha. While, the highest number of concentrates, vitamins and fodder additives were consumed by the biggest farms. Additional materials, such as foil, rope, packaging and cleaning agents constituted a small percentage of use. From the remaining non-agricultural expenditures, labour constituted the highest value. After calculation into energy units it was at the average 84.350 GJ. Replacement investments and materials and parts incurred on renovation of

Table 3 Consumption of agricultural raw materials (GJ) Specification

Sowing material

Seed potato

Concentrate

Volumetric fodders

Others

Area group Up to 5 ha 5.01–10.00 ha 10.01–20.00 ha Above 20.00 ha Average

4.342 5.336 5.751 23.373 8.444

0.498 1.765 1.469 3.886 1.771

30.843 58.301 51.334 48.414 48.259

15.093 72.797 124.058 121.515 80.020

0.325 8.565 11.083 36.044 12.138

Effectiveness of Capital and Energy Expenditures …

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% bought own

sowable material 13

seedlings

87

933

bulky feed

6

concentrate s 21

others

2

45

94

79

98

55

Fig. 1 Structure of agricultural expenditures

Table 4 Consumption of non-agricultural raw materials (GJ) Specification

Fertilizers

Crop protection substances

Concentrate, vitamins, fodder additives

Supplementary materials

Cleaning agents

Area group Up to 5 ha

5.217

1.275

0.000

0.002

0.001

5.01–10.00 ha

0.280

–

0.339

0.003

0.002 0.001

10.01–20.00 ha

29.673

0.955

1.242

0.005

Above 20.00 ha

7.967

0.095

2.662

0.019

0.004

Average

9.469

0.535

0.921

0.006

0.002

machines and buildings were comparable and constituted from 33.247 to 40.844 GJ. Inputs on technical services were 20.460 GJ and for water 6.171 GJ (Table 5). In case of water consumption, repair of machines, services and investments, a raising trend was reported along with the increase of the surface area of agricultural land. While, objects with the acreage from 5 to 10 ha incurred the most on repair of buildings. The highest work inputs incurred in objects with the surface area from 10 to 20 ha which considerably exceeded those in the remaining area groups are worth noting. To conclude, energy inputs in organic farms constituted at the average 15% and were within 7% in farms with the acreage from 10 to 20 ha to 15% in objects with the biggest acreage (Fig. 2). A similar structure was reported for agricultural inputs where their smallest participation (14%) occurred in objects with the area from 10 to 20 ha and the highest one (30%) in farms with the surface area of more than 20 ha. At the average they were 33%. According to the principles of organic farming non-agricultural substances, including fertilizers and agrochemical substances constituted only 3%. While, a half of inputs are the so-called remaining,

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Table 5 Remaining non -agricultural expenditures (GJ) Specification

Water

Repair of machines

Renovation of buildings

Technical services

Replacement investments

Work expenditures

Area group Up to 5 ha

4.927

16.545

7.333

9.750

21.188

64.474

5.01–10.00 ha

5.180

23.456

74.471

10.709

37.551

79.248

10.01–20.00 ha

4.527

25.933

6.027

33.764

51.060

906.889

Above 20.00 ha

11.157

77.978

36.353

35.256

58.790

191.520

6.171

33.247

35.677

20.460

40.844

84.350

Average

including water, renovation of machines and buildings, services, replacement investments and work inputs. Their highest participation was reported in farms with the acreage from 10 to 20 ha (76%). In the remaining area groups their participation was at the level of 53 to 59%. At the average, the global production expressed in the energy units was 920.798 GJ, out of which considerably more, i.e. 756.662 GJ was animal production and 164.137 GJ—plant production (Table 6). The total global production increased along with the surface area of farms and was at the level from 210.480 GJ in the smallest farms to 2489.604 GJ in the objects with the surface area above 20 ha. The highest plant production was reported in farms with the surface area from 10 to 20 ha and animal production in objects with the biggest area. It should be noticed that it was considerably bigger than in the remaining groups. Commodity production constituted at the average 20.5% of the global production. Its highest participation was reported in farms with a smaller area i.e. up to 10 ha. In the commodity production, the animal production constituted the highest participation in all area groups.

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

up to 5 ha

inputs other

59

5,01 10,00 ha 54

inputs non-agricultural

3

0

2

1

2

inputs agricultural

24

34

14

30

33

inputs energy

13

11

7

15

15

Fig. 2 Structure of inputs in area groups

10,01 20,00 ha 76

above 20 ha 53

average 49

Effectiveness of Capital and Energy Expenditures …

935

Table 6 Global and commodity production (GJ) Specification Area group Up to 5 ha 5.01–10.00 ha 10.01–20.00 ha Above 20.00 ha Average

Global production Plant Animal

Total

Commodity production Plant Animal Total

84.863 130.006 274.199 187.555 164.137

210.480 525.961 1013.866 2489.604 920.798

29.595 17.303 13.625 0.783 16.397

125.617 395.955 739.667 2302.049 756.662

55.674 183.149 114.958 383.556 172.263

85.269 200.452 128.583 384.338 188.659

Energy effectiveness indicates which inputs must be incurred in gigajoules to obtain one unit of production expressed in gigajoules. Production activity in the investigated organic farms may be generally considered effective, because out of one unit of the incurred energy input (GJ) at the average over 2 units of global production in GJ were obtained (Fig. 3). Energy effectiveness clearly rises along with the surface area of agricultural land which is indicated by the fact that in the smallest farms effectiveness index was 1.005 and in the biggest ones it was as much as 3.231. However, farms with the acreage from 10 to 20 ha which achieved a negative index of effectiveness are breaking out from the scheme. It resulted from high inputs incurred for production, including mainly the cost of labour. Moreover, for all farms favourable energy effectiveness with the average index at the level of 0.489 was obtained. Similarly as in case of effectiveness, energy effectiveness was better in bigger farms. Objects with the acreage from 10 to 20 ha, where this index is 1.334 were an exception, which means that in order to obtain a unit of global production with the energy value amounting to 1 GJ higher inputs than 1 GJ had to be incurred.

3.5 3.0

[ ]

2.5 2.0 1.5 1.0 0.5 0.0

1.005

5,01 10,00 ha 1.232

10,01 20,00 ha 0.749

above 20 ha 3.231

average

energy effectiveness

up to 5 ha

energy consumption

0.995

0.812

1.334

0.309

0.489

2.045

Fig. 3 Effectiveness and energy consumption of global production in area groups

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12,0 10,0

[]

8,0 6,0 4,0 2,0 0,0

up to 5 ha energy effectiveness

0,407

5,01 10,00 ha 0,469

energy consumption

2,457

2,130

10,01 20,00 ha 0,095

above 20 ha 0,499

average

10,521

2,005

2,386

0,419

Fig. 4 Effectiveness and energy consumption of commodity production in area groups

While, energy effectiveness of the commodity production indicates that at the average, from 1 GJ of inputs only 0.419 of commodity production was obtained (Fig. 4). This effectiveness in all groups, except for farms with the surface area from 10 to 20 ha was comparable and amounted from 0.407 to 0.499. While, in this one group it was exceptionally unfavourable and was at the level of only 0.095. The same group also showed more disadvantageous energy consumption which was as much as 10.521. On the other hand, in the remaining groups, in order to produce 1 GJ of commodity production, inputs in the amount ranging from 2.005 to 2.457 GJ should be incurred.

4 Conclusion The average energy effectiveness of global production in the investigated organic farms was at the level of 2.045. It means that from each gigajoule of the incurred expenditure, over 2 gigajoules of production were obtained. An increasing trend of the effectiveness index along with the agricultural land area was reported. Farms with the acreage above 20 ha obtained a threefold higher effect in comparison to the objects with the area up to 5 ha. Farms with the area from 10 to 20 ha, which obtained mainly a negative outcome, were an exception. Effectiveness of commodity production was however negative both at the average for all farms (0.419) and in all area. Thus, from 1 GJ of the incurred expenditure a little less than 0.5 of the commodity production unit was obtained. Energy consumption of the global production was at the average 0.489. Similarly, as in case of effectiveness, the energy consumption index decreased along with the increase of the farm area. Here, objects with the area from 10 to 20 ha were an exception, There, negative energy consumption at the level of 1.334 was reported.

Effectiveness of Capital and Energy Expenditures …

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While, energy consumption of commodity production is unfavourable with the average index of 2.386. Indices obtained in the area groups are similar to the average, except of farms with the acreage from 10–20 ha, where generation of 1 GJ of commodity production carries with it as much as 10.521 GJ of the expenditure.

References 1. J. Sawa, B. Huyghebaert, P. Burny, Nakłady energetyczno-materiałowe w aspekcie zrównoważonej produkcji rolniczej. Inż. Rolnicza 13, 417–422 (2006) 2. J. Sawa, Nakłady materiałowo-energetyczne jako czynnik zrównoważenia procesu produkcji rolniczej. Inż. Rolnicza 5, 243–248 (2008) 3. P. Grudnik, Efektywność nakładów energetycznych produkcji ziemniaków w wybranych gospodarstwach rolnych. Probl. Inż. Rolniczej 4, 111–119 (2010) 4. M. Kuboń, A. Krasnodębski, Logistic cost in competitive strategies of enterprises. Agric. Econ. 56, 397–402 (2010) 5. T. Dalgaard, On-farm fossil energy use. Ecol. Farm. 32, 9 (2003). IFOAM 6. T. Lötjönen, Machine work and energy consumption in organic farming. Ecol. Farm. 32, 7–8 (2003). IFOAM 7. T. Piskier, Analiza efektywności energetycznej proekologicznych sposobów ograniczania zachwaszczenia pszenicy jarej. J. Res. Appl. Agric. Eng. 53(4), 37–39 (2008) 8. C. Petersen, L.E. Drinkwater, P. Wagoner, The Rodale Institute Farming Systems Trial: The First 15 Years. The Rodale Institute (1999) 9. J.P. Reganold, J.D. Glover, P.K. Andrews, J.R. Hinman, Sustainability of three apple production systems. Nature 410, 926–930 (2001) 10. H. Hill, Comparing energy use in conventional and organic cropping systems. ATTRA-Sustain. Agric. Inf. Serv. 1–8 (2009). 11. C. Foster, K. Green, M. Bleda, P. Dewick, B. Evans, A. Flynn, J. Mylan, Environmental impacts of food production and consumption: a report to the department for environment, food and rural affairs. Manchester Business School. Defra, London (2006) 12. J. Sawa, S. Parafiniuk, S. Kocira, Nakłady energetyczne w różnych systemach gospodarowania. MOTROL. Motoryzacja i Energetyka Rolnictwa. 6, 238–245 (2004) 13. A. Szeptycki, Z. Wójcicki Z, Postęp technologiczny i nakłady energetyczne do 2020 r. IBMER, Warszawa, 14–20 (2003) 14. Z. Wójcicki, Wyposażenie i nakłady materiałowo energetyczne w rozwojowych gospodarstwach rolniczych. IBMER Warszawa (2000). ISBN 83-86264-62-4 15. D. Kwaśniewski, U. Malaga-Toboła, M. Kuboń, Assessment of technical means of production resources on organic farms. Agric. Eng. 7(132), 73–80 (2011) 16. Z. Wójcicki, Poszanowanie energii i środowiska w rolnictwie i na obszarach wiejskich. Infrastruktura i ekologia terenów wiejskich 2(1), 33–48 (2006) 17. M. Kuboń, D. Kwaśniewski, U. Malaga-Toboła, The level and structure of means of transport and loader resources on organic farms. Agric. Eng. 7(132), 57–64 (2011) 18. U. Malaga-Toboła, D. Kwaśniewski, M. Kuboń, Farming conditions versus the size and structure of herd on organic farms. Agric. Eng. 7(132), 93–99 (2011) 19. Z. Wójcicki, B. Rudeńska, Efektywność nakładów materiałowo-energetycznych w gospodarstwie rolnym. Probl. Inż. Rolniczej 4(86), 57–70 (2014) 20. M. Kuboń, D. Kurzawski, Analiza przepływów surowcowo-towarowych w aspekcie kierunku produkcji na przykładzie wybranych gospodarstw Polski południowej. Inż. Rolnicza 2(137), 159–168 (2012). T.2 21. Z. Wójcicki, Poszanowanie energii i środowiska w rolnictwie i na obszarach wiejskich. Monografia. IBMER, Warszawa (2007). ISBN 978-389806-17-18

Financial Condition of the Development of the Market of Renewable Energy Sources Oleksandra Mandych , Arkadii Mykytas , Mariia Melnyk , Olga Girzheva and Sergiy Kalinichenko

Abstract In the context of the current global economic crisis, the increasing attention of the world community is given to increased structural transformation of fuel and energy complexes of countries. The main content of these processes is to increase the economic efficiency of energy use and reduce the dependence on their imports, which is extremely relevant for Ukraine. Thus, it is evident that there is a need for in-depth scientific consideration of the above-mentioned processes in order to localize existing problems, as well as to develop recommendations for their solution. The article generalizes the tendencies of development of the field of alternative energy in Ukraine and the world, conducted an analysis of the financial state of renewable energy sources, developed recommendations for the improvement and development of this industry. In the course of the study, there were positive changes in the field of alternative energy were discovered, but to date there O. Mandych Department of Economics and Marketing, Kharkiv Petro Vasylenko National Technical University of Agriculture, St. Alchevskikh, 44, 61002 Kharkiv, Ukraine e-mail: [email protected] A. Mykytas Department of Life Safety and Law, Kharkiv Petro Vasylenko National Technical University of Agriculture, St. Alchevskikh, 44, 61002 Kharkiv, Ukraine e-mail: [email protected] M. Melnyk (&) Department of Finance, Sumy National Agrarian University, St. Sokolyna, 21, 40013 Sumy, Ukraine e-mail: [email protected] O. Girzheva Department of Business, Trade and Stock Exchanges Activities, Kharkiv Petro Vasylenko National Technical University of Agriculture, St. Alchevskikh, 44, 61002 Kharkiv, Ukraine e-mail: [email protected] S. Kalinichenko Departments of Organization of Production, Business and Management, Kharkiv Petro Vasylenko National Technical University of Agriculture, St. Alchevskikh, 44, 61002 Kharkiv, Ukraine e-mail: [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_90

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are still a range of problems that require a state settlement: regulating the alternative energy market needs to be revised by creating new incentive mechanisms for companies active in the alternative energy market and developing effective guidelines; elimination of bureaucratic procedures for obtaining state benefits; activation of bank financing programs for investment in renewable energy projects. Large-scale development of energy from renewable sources will allow to create a new ecologically safe branch of energy, which will help to increase the level of diversification of energy resources and strengthen the energy and ecological safety of Ukraine.







Keywords Financial condition Alternative energy industry Financing Financial analysis Economic efficiency Renewable energy sources










1 Introduction In the context of the current global economic crisis, the increasing attention of the world community is given to increased structural transformation of fuel and energy complexes of countries. The main content of these processes is to increase the economic efficiency of energy use and reduce the dependence on their imports, which is extremely relevant for Ukraine. Thus, it is evident that there is a need for in-depth scientific consideration of the above-mentioned processes in order to localize existing problems, as well as to develop recommendations for their solution. At the moment, Ukraine is trying to keep pace with developed European countries, maximizing its own natural potential, which by the way is favorable for the development of four main areas of alternative energy (wind power, solar energy, small hydropower plants, biofuel production from organic raw materials of their own production) [8, 22]. Ukraine’s energy policy must ensure the security of supply, reduction or diversification of international dependence, increase the efficiency of production and use of electricity and heat, and take into account the possibilities of future commitments on climate protection [6]. Ukraine has considerable technical potential for the use of renewable energy sources. Thanks to its significant agricultural sector there are very good preconditions for using bioenergy. There is quite a good technical potential for solar and geothermal energy, but in the medium term, their use does not seem economically feasible. The development of this technical capacity will be determined by economic preconditions, as well as the framework conditions of the energy policy. Renewable energy sources play a secondary role only in the energy policy of Ukraine [6]. An important feature of Ukraine is the very close connection between the state and private capital. On the one hand, this connection facilitates the implementation of large-scale projects organized on the basis of the private economy, since they can

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be implemented on a “top-down” basis. This also applies to renewable energy sources. However, on the other hand, this approach reduces the trust of foreign investors in the structures of political subordination and inhibits the activity of medium-sized enterprises. German experience shows that the renewable energy sector exist because of private companies—and above all of medium-sized enterprises. These firms in the framework of a social market economy have a specific profile of requirements for capital equipment, risk preparedness and ability to perform administrative tasks, which should be taken into account in determining the direction of the framework conditions of regulation. Widely used financing projects of the development of RES. Project finance is of great importance especially for comparably small projects —ca. 83% of projects that are smaller than 50 MW use it, but only 36% of projects in the cluster 50–100 MW, and just 28% of even larger projects. Of course the typical project size differs by technology—correspondingly. Recalling that renewables in Germany qualify for a feed-in tariff that takes away all the merchant risk, it is the generally smaller, less risky projects that rely on project finance— putting the contamination risk reason into question, which will be further assessed by the regression analysis [16]. During the last years of the democratization process in Ukraine, certain forces of civil society have been formed, which, along with an active position on ecology and climate protection, also require wider use of renewable energy sources. Together with strict autocratic approaches to energy policy in Ukraine, this has caused the emergence of new instruments for promoting, in particular, for alternative energy sources, such as the Green Tariff Act. This law, like the German Law on Renewable Energy, will temporarily stimulate the production of energy from renewable sources. The development of the renewable energy sector in Ukraine will be driven by a number of general political and economic factors that affect the investment climate, favorable financial conditions and economic prosperity in general.

2 Methodology and Aim of the Study The goal of the research is to study financial condition of the development of the market of renewable energy sources. The study was based on the generally accepted methods for data quantification, presentation, observation, processing, grouping of observation materials and statistical summary. Assessing the financial condition of the development of the market of renewable energy sources, we used the following statistical methods which relate to quantitative methods of economic analysis: (1) statistical observation—recording information on certain principles and for certain purposes;

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(2) series of dynamics: absolute growth, growth rates; (3) summary and grouping of economic indicators according to certain characteristics; (4) comparison of indicators: with competitors, standards, dynamics; The method of comparison with the previous period was also used. It is the comparison of economic indicators of the current period with those of the previous period. Also, the comparison with the best indicators was made—the best practice gives an effect when the comparison is conducted with indicators of similar enterprises. The most used method was the method of horizontal analysis (temporary)—the comparison of each position of reporting with the corresponding position of the previous period, consisted in the construction of several analytical tables.

3 Renewable Energy Development in the World Due to global mixing of greenhouse gases, an efficient climate policy must be done on a global scale. Renewable energy does not lead to greenhouse gas emissions and thus is a crucial part of a strategy to reduce emissions [7]. The development of the renewable energy industry is the important support for the sustainable development of social economy. It is of great significant for economic security and national security and its strategic significance is immeasurable. The process of cultivating, developing and upgrading the renewable energy industry is a comprehensive system project that includes finance, resources, technology and management. As the core of modern economic development, finance plays an important role in the cultivation, development and up gradation of renewable energy industries. The renewable energy industry needs long-term, huge and uninterrupted funding, especially in the early stages of development when it has significant characteristics of high input, high risk and high returns. The optimization and upgrade of the renewable energy industry cannot be separated from financial support, and the establishment of a modern electricity market to promote the large-scale application of renewable energy requires financial support [4, 5, 21]. The most dynamic in recent years are the production and implementation of photovoltaic solar power plants and stations. More than 60% of all facilities put into operation around the world by the end of 2015 have been added over the past three years. In the whole world, the total installed power of photovoltaic systems (stations) has reached 222.3 GW. At the end of 2015, the leaders with installed power of solar photovoltaic systems (stations) were countries such as China (40 GW), Germany (39.6 GW), Japan (33.3 GW), USA (25.5 GW) and Italy (18.9 GW). In 2015, China became the undisputed leader in renewable energy development - this year it installed 14.8 GW of photovoltaic systems (stations). The business value of PV (photovoltaic applications) should be compared to the GDP of each country [19]. While the positive impacts stimulated by the development of renewable

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energy are apparent in terms of direct and indirect stimulation of RE-related sectors, other sectors, especially those related to the conventional energy supply chain, may suffer negative impacts. The development of renewable energy on such a large scale has wide-ranging implications. Investment toward the construction of fossil-fired power plants and other sectors which are stimulated by demand for products of the previously mentioned high-carbon sectors decreases. Meanwhile, benefits accrue in upstream sectors of RE investment, e.g., electronic machinery, and in the research and development sectors [2]. In 2016, global renewable electricity generation grew by an estimated 6% and represented around 24% of global power output. Hydropower remained the largest source of renewable power, accounting for around 70%, followed by wind (16%), bioenergy (9%) and solar PV (5%). In 2015, net additions to grid-connected renewable electricity capacity reached a record high at 153 GW, 15% higher than in 2014. For the first time, renewables accounted for more than half of new additions to power capacity and overtook coal in terms of world cumulative installed capacity [18]. The use of wind energy is expanding around the world, which results in lowering the cost of turbines, raising the level of state support and increasing investor recognition of the positive characteristics of wind power generation. In 2014, the total share of wind power generation accounted for more than 3% of world electricity supply [3, 20].

4 Renewable Energy Development Potential in Ukraine 4.1

Energy Potential of RES

Energy efficiency and the use of renewable energy sources has become a pressing need of time, as it promotes solving energy supply problems, as well as many environmental, economic and social problems. Of the various types of RES, the most widespread and affordable for Ukraine are wind and solar energy, biomass and energy of small rivers, geothermal energy and the environment. According to the State Agency for Energy Efficiency and Energy Saving of Ukraine (State Energy Efficiency), the total annual technically achievable energy potential of the RES of Ukraine in terms of conventional fuel is approximately 98 million tons of standard fuel. (Table 1), which is almost 50% of the total energy consumption in Ukraine at present and is forecast to reach 30% of energy consumption in 2030. This potential is quite significant, technically and economically attractive in conditions of significant increase of prices for traditional energy resources in Ukraine. The project of the updated Energy Strategy for the period up to 2030, promulgated by the Cabinet of Ministers of Ukraine in June 2012, planned (in the baseline scenario of development) to riched the share of renewable energy up to 10% of the installed capacity—in 2030 and up to 5% in 2020 (at 20% of the consumption of renewable electricity planned by the EU) [17].

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Table 1 Technically achiveable renewable energy production potential for renewable energy sources and alternative fuels №

Areas of development of RES

1 Solar power engineering, including Electric Thermal 2 Small hydropower 3 The energy of the environment (heat pumps) 4 Geothermal heat energy 5 Bioenergy, including Electric Thermal 6 Wind power Total amount of replacement of traditional fuel and energy resources Sources [17]

Annual technically achievable energy potential, miln. tons of conventional fuel 6.0 2.0 4.0 3.0 18.0 12.0 31.0 10.3 20.7 28.0 98.0

By joining the Treaty establishing the Energy Community, Ukraine has undertaken to implement certain elements of the acquis communautaire on energy, environment, competition and renewable energy in the legislative field of Ukraine. Accordingly, there is the need for a detailed analysis and refinement as target indicators of RES in the documents of the strategic level, as well as the current legislation.

4.2

Energy Potential of the Sun

Taking into account the climatic peculiarities of the territory of Ukraine and the presence of powerful enterprises (including producers of semiconductor materials, as well as microelectronic and electrical devices, which makes it possible to obtain additional profit for the production of electricity using photovoltaic technologies), the transformation of solar energy into electricity production using photovoltaic devices is one of the most promising directions of the development of renewable energy in Ukraine (Table 2). Photoelectric equipment can be effectively operated throughout the year, but most effectively—for seven months a year (from April to October) in the southern regions and five months a year—in the northern (from May to September). As of January 1, 2016, in Ukraine, under the “green” tariff for electricity production, there are 112 solar power plants with installed capacity of almost 838.83 MW. The above-mentioned objects in 2015 produced over 475.1 million kWh of electricity. Depending on the size and complexity of the system, the prices for autonomous PV vary considerably. Due to technical developments and mass production, prices for small standard systems have declined in recent years [1].

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Table 2 Solar Energy potential in Ukrainian territory №

Regions

The potential of the solar energy Technically achievable potential Theoretically—possible potential billion kW * h/ (х 105) tons of o.е./ (x 109) tons of o.е./year year year

1 Crimea 3.95 2 Odessa 3.92 3 Kherson 3.29 … … … 16 Kirovograd 2.38 17 Sumy 2.24 18 Lviv 2.17 … … … 25 Chernivtsi 0.84 Total 63.01 Sources http://saee.gov.ua/uk/pressroom/1133

2.2 2.09 1.84 … 1.26 1.21 1.12 … 0.46 33.77

1.89 1.79 1.69 … 1.08 1.04 1.1 … 0.41 29.63

As of January 1, 2016, the total capacity of solar installations of private households operating at a “green” tariff is 2.6 MW. The indicated plants produced 410 268 kWh of electricity in 2015, which is 11 times as much as in 2014, thanks in particular to the use of the green tariff for private households producing electricity from alternative sources of energy.

4.3

Wind Energy Potential

According to the International Agency for Renewable Energy (IRENA), the total wind potential, which is the second largest renewable energy resource in Ukraine, is 16–24 GW. Wind power industry of Ukraine can potentially provide annual energy equivalent of 10.5 million tons of oil equivalent, which will save about 13 billion cubic meters of natural gas annually (Table 3). According European and domestic experts, the potential of wind power in Ukraine makes good use of wind power plants with total capacity of 16 GW, excluding offshore wind farm. The most promising regions—the south and southeast, where the average annual wind speed at 80 m height exceeds 7.5 m/s. The Wind Power Potential map shows the presence in Ukraine of significant areas with high wind power potential. For the construction of wind farms of such capacity, over 200 billion hryvnias of investments are needed. According to the results of the conducted studies, the presence in each region of Ukraine of localizations, which ensure the implementation of effective investment projects of wind power.

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Table 3 The highest potential of wind energy in the regions (at an altitude of 100 m) №

1 2 3 4 5 6 7 8 9 10 11 12 Sources

Regions

The specific potential of wind energy Technically achievable, kW. year/m2 Natural, kW. h/m2 per year per year

Crimea 6781 Kherson 6079 Zaporozhye 5771 Ivano-Frankivsk 5538 Odessa 5481 Donetsk 5300 Lugansk 5137 Nikolaev 5047 Dnipropetrovsk 4540 Chernivtsi 4222 Zakarpattya 4175 Lviv 3799 http://saee.gov.ua/uk/pressroom/1133

1061 956 935 902 915 903 891 885 850 708 702 646

From the zoning of the territory, it follows that realization of the implementation projects: – solar power plants are most effective in the Autonomous Republic of Crimea, Odessa, Dnipropetrovsk, Kherson, Kharkiv, Zaporozhye, Chernihiv, Donetsk, Luhansk, Zhytomyr, Kyiv, Mykolayiv and Poltava regions; – ground wind power plants are most effective in the Autonomous Republic of Crimea, Kherson, Zaporozhye, Ivano-Frankivsk, Odessa, Donetsk, Luhansk, Dnipropetrovsk, Chernivtsi, Transcarpathian and Lviv regions. In Ukraine, the support of renewable energy, in particular wind power, is enshrined at the legislative level. The wholesale electricity market is obliged to buy from entities that have a “green” tariff and to pay the full cost of electricity, regardless of the size of installed capacity or volumes of its release.

5 Economic Indicators. Sources of Financing The main factor affecting the economic performance of the production of thermal and electric energy using solar and wind energy is the cost of the main equipment of power systems. Renewable energy is, in fact, a multi-billion dollar industry and the most dynamic sector of the global energy market. Globally installed renewable energy capacity is expected to more than double over the next ten years from approx. 130 GW in 2003 to 300 GW in 2013 [15].

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In determining the projected specific investment, the cost of the main equipment as domestic producers of products for solar energy, such as “Kvazar” OJSC in Kyiv (photovoltaic), “SINTEK” in Zaporozhye (producer of thermal collectors) and European associations: European PV Platform (photovoltaic), European Solar Thermal Technology and the leading countries in the world (USA, Japan, China, etc.). The average investment cost of the abovementioned producers corresponds to the data from the International Renewable Energy Agency (REN 21) report. In the field of photovoltaic power, the specific values of photovoltaic systems in the world and in Ukraine (depending on the selected basic equipment) make an average of 1.2–1.5 thousand USA dollars/kW of installed capacity. The level of specific investments and the total investment need for photovoltaic systems construction are presented in the following tables.

5.1

Solar Power

The following table presents the initial parameters for calculating the technical and economic indicators of solar electricity in Ukraine, and in the Table 5—the need of investments until 2020 (Table 4). Should be note, that at the beginning of 2015, 819 MW of PV power stations were constructed. According to the research, it can be said that the additional power of the photoelectric power plant by 2020 should increase by 50 MV/year. The cost of building up to 2020 also has to increase by 75 million dollars a year, which is estimated at 450 million dollars by 2020.

5.2

Wind Power

In 2016, onshore wind energy continued to be heavily expanded, with some 4443 MW newly installed, marking an increase over the previous year. After the Table 4 Indicators of technical and economic calculations of solar power industry in Ukraine Indicator

Value, $/kW

Share, %

Specific cost of equipment 1125 75 Additional expenses (foundations, installation, other) 300 20 Expenses for the development of electric networks 75 From 5b and connection of PV stations (photovoltaic station) to the network Total specific investments in PV stations 1500a 100 Sources Own resources Note athe specific cost of investments is taken from the report of the International Renewable Energy Agency b the indicator is determined after the feasibility study of the PV stations power scheme has been developed;

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Table 5 Total demand for investments in the construction of PV stations Indicators Additional power of PV station, MW/year Construction cost, mln. $/year Total cost, $ million Sources Own resources

2016

2017

2018

2019

2020

Deviation (±) 2020/ 2016

250

200

250

300

300

50

375 375

300 675

375 1050

450 1500

450 1950

75 1575

dismantling of old installations (277 MW), net expansion in 2016 amounted to 4166 MW. This is the second highest expansion figure since 2014 (4651 MW). At the end of the year, a total of 45,412 MW of installed onshore wind capacity was linked up to the grid. However, the high level of expansion did not have a direct effect on the amount of electricity generated from wind turbines as there was comparatively little wind in 2016. This meant that the amount of electricity produced by onshore wind installations declined by nearly 7% over the previous year, falling to 66,3 billion kilowatt hours (2015: 70.9 billion kilowatt hours) [9]. The following table presents the initial parameters for calculating the technical and economic indicators of wind energy in Ukraine, and in the Table 7—the need of investments until 2020 (Table 6). From this table we can say that the specific cost of a wind turbine is 1000 euros, additional costs are 250 euros, costs for the development of electricity networks and the connection of wind power to the network is 150 euros. In total, the installation of a wind turbine will be 1500 euros. The most capital-intensive is the purchase of wind turbines. The additional capacity of the wind turbines of the planned period 2018–2022 will be reduced by 170 MW/year. In connection with the expansion of production and demand of wind turbines, the cost of construction in the coming years will decrease by 255 million euro. The total cost of the purchase and installation of a wind turbine will increase by 1395 million euro.

Table 6 Indicators of technical and economic calculations (€/kW) Indicators Specific cost of wind turbines Additional expenses (foundations, installation) Expenditures on the development of power grids and connection of wind turbines to the grid Other expenses Total specific investments in wind energy station (WES) Sources Own resources

Value, €

Share, %

1000 250 150

65–70 16–20 7–11

100 1500

5–9 100

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Table 7 Total demand of investments in the construction of wind energy station Indicators Additional power of wind turbines, MW/year Construction cost, million euro/year Total cost, million euro Sources Own resources

2018

2019

2020

2021

2022

Deviation (±) 2022/2018

350

300

250

200

180

−170

525 1275

450 1725

375 2100

300 2400

270 2670

−255 1395

6 Priority Measures to Ensure the Effectiveness of RES The commitment by 195 countries to limit global warming to well below 2 °C sent a clear signal: we have to radically rethink how we produce and consume energy if we are to meet this target. The pledge of 48 climate vulnerable countries at COP22 to use only renewable energy by 2050 further strengthens this resolve [10–14]. Ensuring implementation of the plan for the development of RES in terms of the development of solar generation. – development of power generating capacities. Construction of photovoltaic stations (FES); – development of regulatory and legal support for the development of solar energy; – scientific and technical support for the development of solar energy. Ensuring the implementation of the plan for the development of WPP in terms of the development of wind power; – development of power generating facilities—construction/reconstruction of wind power plants in the regions of Ukraine; – scientific and technical support for the development of wind energy;

7 Conclusion The study found that Ukraine has favorable financial and economic conditions for the development of renewable energy sources. Under the influence of the current world trends in the energy sector and in order to reduce energy dependence on expensive organic sources and increase the share of alternative energy in the energy balance of the country, the Ukrainian authorities in recent years have undertaken a number of measures to stimulate the alternative energy sector: the creation of a number of scientific institutions engaged in research in renewable energy sources; the presence of a “green tariff”, according to which the wholesale electricity market of Ukraine is obliged to buy electricity from alternative energy sources”. But despite some positive developments in the field of alternative energy, there are still

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a range of problems that require a state settlement: the regulatory framework for regulation of the alternative energy market needs to be revised by creating new incentive mechanisms for companies active in the alternative energy market and developing effective guidelines; elimination of bureaucratic procedures for obtaining state benefits, which is possible provided that the existing system for providing them is simplified; activating banking programs to finance investment in renewable energy projects. Large-scale development of energy from renewable sources will enable the creation of a new environmentally friendly energy sector that will increase the level of diversification of energy resources and strengthen the energy and ecological safety of Ukraine.

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14. REN21 Annual Report (2017), http://www.ren21.net/wp-content/uploads/2018/02/REN21_ AnnualReport_2017_web.pdf 15. V. Sonntag-O’Brien, E. Usher Mobilising finance for renewable energies (2014), http:// siteresources.worldbank.org/EXTRENENERGYTK/Resources/5138246-1237906527727/ 5950705-1239134575003/mobfin0mfretb003.pdf 16. B. Steffen, The importance of project finance for renewable energy projects. Energy Econ. 69, 280–294 (2018) 17. O.M. Suhodolya, A.Y. Smenkovsky, A.I. Shevtsov, M.G. Zemlyanii, State and prospects of renewable energy development in Ukraine, in National Institute of Strategic Research. The series “Economics”, Issue 12 (2014), pp. 21–35 18. Tracking Clean Energy Progress, in International Energy Agency (2017), https://www.iea. org/publications/freepublications/publication/TrackingCleanEnergyProgress2017.pdf 19. Trends 2016 in photovoltaic applications, in International Energy Agency (2016), http://ieapvps.org/fileadmin/dam/public/report/national/Trends_2016_-_mr.pdf 20. O. Kucher, L. Prokopchuk, The development of the market of the renewable energy in Ukraine. in Renewable Energy Sources: Engineering, Technology, Innovation. (Springer, 2018), pp. 100–121. ISSN 2352-2542 (electronic), ISSN 2352-2534 21. O. Kucher, T. Hutsol, K. Zavalniuk, Marketing strategies and prognoses of development of the renewable energy market in Ukraine, in Scientific Achievements in Agricultural Engineering, Agronomy and Veterinary Medicine, (Krakow, Poland, 2017), pp. 100–121 22. M. Melnyk, S. Zabolotnyy, The financial efficiency of biogas stations in Poland, in Renewable Energy Sources: Engineering, Technology, Innovation. (Springer, Cham, Switzerland 2018), pp. 83–93

The Influence of Pre-processing of Input Data on the Quality of Energy Yield Forecasts from a Photovoltaic Plant Krzysztof Nęcka, Anna Karbowniczak, Hubert Latała, Marek Wróbel and Natalia Mioduszewska

Abstract The aim of this study was to analyse the influence of different methods of pre-processing of input data such as moving average, subtraction of the mean and smoothing with the 4253H filter on the quality of forecasts of energy yield from a photovoltaic plant developed on the basis of MLP artificial neural networks. Forecasts were conducted at hourly time intervals for three types of cells; mon- and polycrystalline cells, as well as CIGS thin-film cells. The aim of the study was achieved based on the authors’ own research conducted at a PV plant located in Krakow with a total power output of 12.67 kWp. The assessments of the models developed were made based on the total ratio of energy for balancing in the total energy production (DESR) and on an analysis of the mean absolute percentage error (MAPE). Keywords Modelling


Forecasting
Pre-processing
Photovoltaic cells

1 Introduction The use of photovoltaic solar installations in energy grids has attracted a great deal of attention in recent years due to its capacity to directly produce electricity. Along with the systematically falling prices of photovoltaic modules and the ongoing depletion of fossil fuel resources, it is expected that the participation of energy from photovoltaic sources in modern energy grids will continue to increase. The operation of renewable energy resources (RER), however, has a dynamic nature and in K. Nęcka
A. Karbowniczak
H. Latała (&)
M. Wróbel Faculty of Production and Power Engineering, University of Agriculture in Krakow, Kraków, Poland e-mail: [email protected] K. Nęcka e-mail: [email protected] N. Mioduszewska Faculty of Agronomy and Bioengineering, Poznań University of Life Sciences, Poznań, Poland © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_91

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large measure is dependent on weather conditions and the construction of the PV plant. The integration of RER with existing energy grids on a large scale is thus a significant challenge [1]. Due to the unpredictable nature of weather conditions, the output power of a photovoltaic system is always characterized by significant uncertainty in terms of continuity, variability, and randomness [2]. These uncertainties may potentially reduce the efficiency of the usage of energy yield in real time, reducing the economic efficiency of the system, and also creating a serious challenge for the management and operation of the energy grid [3]. The large-scale implementation of photovoltaic plants in a public grid has shown serious problems, such as interference in the stability of the system, in the reliability of energy supply, in the balancing of electrical power, in reactive power compensation, and in ensuring the required frequency of supply voltage [4, 5]. One of the most promising solutions aiming to ameliorate the negative influence of these uncertainties on electrical grids is the use of advanced methods of forecasting power and energy supply in photovoltaic systems [6]. Forecasting of energy yield from photovoltaic systems is often done over a multistage process. Most often this involves the pre-processing of measurement data, the construction of a model, and the simulation of the operation of the photovoltaic installation. Accurate forecasts of electrical energy generation improve the integration of renewable energy resources with other elements of the grid, thanks to which it is possible to limit the amount of energy necessary for balancing from conventional generators and stored energy [7]. Reliable forecasts thus play a key role in the further development of such systems. In order to meet the requirements of the decision-making process, forecast models are heavily based on spatial and time analysis, on meteorological variables, on the selection of input parameters, and on teaching algorithms [8]. Forecasting of power and energy yield is thus a powerful tool which can aid operators and designers of power systems in the efficient exploitation of systems which work together with photovoltaic installations [9]. Prediction of hourly energy production is, however, a very difficult task due to the large number of rapidly changing variable factors which influence it. The literature describes many models and techniques for short-term forecasting [10–13], yet so far a single universal procedure guaranteeing the development of a model with an acceptable level of error has not been developed. It is thus essential to continually seek effective methods of forecasting hourly energy production from renewable energy sources [14].

2 Aim and Scope of the Study and Description of Methodology The aim of this study was to analyse the influence of selected methods of pre-processing of input data on the quality of hourly energy yield forecasts from photovoltaic installations developed with the use of artificial neural networks.

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This aim was achieved based on the authors’ own research, conducted on a photovoltaic plant constructed with monocrystalline panels with a power of 4.2 kWp, and polycrystalline panels with a power of 4.27 kWp, as well as thin-film CIGS panels with a power of 4.4 kWp. The photovoltaic plant, with a southern exposure and an angle of 32°, is located in the city of Kraków. The study involved the constant measurement and recording of installation parameters such as power and electrical energy, intensity of solar radiation, external temperature, and operating temperature of the photovoltaic cells. The measurement data was recorded every 120 s, and next aggregated into hourly time intervals. From the information gathered, only those periods were selected during which there were meteorological conditions which allowed for the operation of the plant. Next, the database generated was divided into three sets: a teaching set including 50% of the observations, a test set (25%), and a validation set (25%). When dividing the data, it was ensured that an entire day’s data belonged to a single set and that during the study these days were not switched between sets. Next, the construction of a model of energy yield from the PV panels was begun, using for this purpose an artificial neural network available in the Statistica 13 program. The development of a neuron model required first and foremost the selection of input variables, the pre-processing, and finally the determination of the optimal network architecture. Pre-processing of the time series involved its smoothing. Smoothing always involves some form of local averaging of data so that non-systematic components of individual observations cancel each other out. In this study, among others, methods such as moving average and median as well as subtraction of the mean were used. The basic advantage of smoothing using the median, in comparison with a moving average, is that the results are less burdened by outlying results (within the smoothing window). Therefore, if the data includes outlying observations (for example, resulting from measurement errors), smoothing using the median usually gives smoother or at least more reliable curves than a moving average with the same window width. In this study, the influence of other transformations on the quality of energy yield forecasts from a PV plant was studied, such as Danielle, Tukey, Hamming, Parzen and Bartlett techniques, and also the use of a 4253H filter and tempering. Pre-processed time series of the intensity of solar radiation and temperature were used to search for a structure of the neural network which would allow for the generation of reliable forecasts. By optimisation of network structure we understand not only the determination of the number of neurons in the input layer, but also the determination of the type of neural network, the number of layers and the number of neurons in hidden layers. This is because the structure of the neural network is a factor which influences the properties of the network and the qualities of approximation of dependencies contained in the presented training data [15]. For the construction of forecast models, an automatic neural network teacher was used for which the number of neurons in the input layer was determined based on a previously conducted analysis of significance of the influence of factors, and the range of variation in the number of hidden neurons and taught SSN was determined.

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Fig. 1 Architecture of the artificial neural network (ANN)

Based on a review of the literature and the results of the authors’ own research, it was decided to use a one-directional MLP network (Fig. 1). The predictive quality of the models constructed was assessed based on the values of forecast errors indicated by the formulas: 1 Xn jErz Etp j
100 t¼1 Erz n Pn jErz  Etp j DESRt ¼ t¼1 c
10 Erz

MAPE ¼

ð1Þ ð2Þ

where: MAPE ΔESRt Erz Ecrz Ept

– – – – –

mean absolute percentage error of forecast, annual percentage error of forecast, real value of electricity generated from the PV plant, real annual value of the generated eclectic energy from PV plant, forecast value of the electricity generated from the PV plant.

3 Results and Discussion The characteristics of the influence of selected methods of smoothing on the demand patterns of analysed variables is presented based on the intensity of solar radiation (Fig. 2), which is the factor which most strongly influences the operation of photovoltaic cells. From the characteristics of the influence of selected methods of pre-processing of input variables presented in the tables, it can be seen that in most cases these have only a slight influence on the time series. The strongest influence on the average intensity of solar radiation was observed for tempering. The transformed

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Fig. 2 The influence of selected methods of pre-processing of a series on its demand pattern

time series was characterized by the lowest average value, which suggests the greatest smoothing. The variability co-factor which was indicated for this, however, had the highest value, exceeding even the level for the non-processed series. From the demand patterns illustrated in Fig. 2, it can be seen that pre-processing of the time series of the input variable influences a local reduction of the amplitude of change in the intensity of solar radiation. Due to its dynamics, the response of inverters to force from the photovoltaic cells may have a positive influence on the quality of forecasting models for electricity generation. After transformation of selected input variable such as intensity of solar radiation, external temperature, and temperature of the panels, the construction of models of artificial neural networks was begun using the abovementioned methods. In the illustrations below, assessment indices for the quality of the models developed are presented, depending on the method used for pre-processing of input variables for hourly time intervals. For monocrystalline panels, the mean absolute percentage error for the test set was comparable for all smoothing methods and amounted to less than 14%, while for the teaching set the lowest error was 10% for the subtraction of the mean method of smoothing. The difference between the methods used for smoothing variables and raw data amounted to on average 0.4% for the test set and 1% for the teaching set. Insignificant differences were also seen in the total actual value of energy balance DESR. Both for methods of data smoothing and for data without pre-processing, an annual forecast error was obtained of approximately 8% for the test set and 6% for the teaching set (Fig. 3). In the case of polycrystalline panels, a reduction of the mean absolute percentage error, which was approximately 14%, was also not achieved for the test set. For the teaching set, the opposite effect was achieved after applying standardization and Bartlett’s window methods of smoothing, in which the error increased by 0.1%. The annual percentage error of forecast DESR also showed a difference of 0.1% both for the teaching and test sets (Fig. 4).

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Fig. 3 Quality of characteristics of prognostic models for monocrystalline modules

Fig. 4 Quality of characteristics of the prognostic models for polycrystalline modules

Fig. 5 Quality of characteristics of the prognostic models for thin-film modules

For CIGS thin-film panels, in comparison with other types of panels, the highest mean absolute percentage error was obtained for the test set, at a level of 16%, both for data without pre-processing and after the application of smoothing methods such as Bartlett’s window. The error for the teaching set, in contrast, was 14%. After the application of standardization and the subtraction of the mean, the error was reduced by 2% both for the teaching and test sets. An analysis of the results obtained for the annual forecast error DESR after the application of standardisation and subtraction of the mean showed that the error was reduced by 2% for the teaching set, while for the test set the reduction in error was a mere 0.1% (Fig. 5).

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4 Conclusions The calculations conducted indicated that pre-processing of input data for artificial neural network models caused an average reduction in the mean absolute percentage error (MAPE) of 0.1 to 2%. The exception were models constructed using the Bartlett’s window, which on average experienced an increase in forecasting error of 0.5% for test sets of thin-film panels. In practical terms, the most significant parameter for assessing the models is the total actual value of energy balance DESR. For most of the models constructed on the basis of transformed variables, a reduction in the value of the DESR index was observed when compared to models constructed on the basis of non-transformed variables. The greatest reduction, of more than 2%, of the values of the index analysed for thin-film CIGS panels was obtained for input variables smoothed with standardisation and subtraction of the mean. Due to the lowest total energy balance value in practical applications however, models should be preferred which are constructed based an hourly time series smoothed by subtraction of the mean. Acknowledgements This research was financed by the Ministry of Science and Higher Education of the Republic of Poland.

References 1. G. Graditi, S. Ferlito, G. Adinolfi, G.M. Tina, C. Ventura, Energy yield estimation of thin-film photovoltaic plants by using physical approach and artificial neural networks. Sol. Energy 130, 232–243 (2016) 2. J. Liu, W. Fang, X. Zhang, C. Yang, An improved photovoltaic power forecasting model with the assistance of aerosol index data. IEEE Trans. Sustain. Energy 6(2), 434–442 (2015) 3. H.S. Jang, K.Y. Bae, H.S. Park, D.K. Sung, Solar power prediction based on satellite images and support vector machine. IEEE Trans. Sustain. Energy 7(3), 1255–1263 (2016) 4. C. Wan, Y. Zhao, Z. Song, Z. Xu, J. Lin, Z. Hu, Photovoltaic and solar power forecasting for smart grid energy management. CSEE J. Power Energy Syst. 1, 38–46 (2015) 5. S. Koohi-Kamali, N. Rahim, H. Mokhlis, V. Tyagi, Photovoltaic electricity generator dynamic modeling methods for smart grid applications: a review. Renew. Sustain. Energy Rev. 57, 131–172 (2016) 6. H. Wang, H. Yi, J. Peng, G. Wang, Y. Liu, H. Jiang, W. Liu, Deterministic and probabilistic forecasting of photovoltaic power based on deep convolutional neural network. Energy Convers. Manag. 153, 409–422 (2017) 7. S. Ferlito, G. Adinolfi, G. Graditi, Comparative analysis of data-driven methods online and offline trained to the forecasting of grid-connected photovoltaic plant production. Appl. Energy 205, 116–129 (2017) 8. S. Sobria, S. Koohi-Kamalia, N.A. Rahima, Solar photovoltaic generation forecasting methods: a review. Energy Convers. Manag. 156, 459–497 (2018) 9. F. Barbieri, S. Rajakaruna, A. Ghosh, Very short-term photovoltaic power forecasting with cloud modeling: a review. Renew. Sustain. Energy Rev. 75, 242–263 (2017) 10. J. Łyp, Prognozy krótkoterminowe obciążeń małych odbiorców energii elektrycznej. Polityka Energetyczna 10(2), 277–287 (2007)

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11. J. Małopolski, M. Trojanowska, Modele rozmyte zapotrzebowania na moc dla potrzeb krótkoterminowego prognozowania zużycia energii elektrycznej na wsi. Część I. Algorytmy wyznaczania modeli rozmytych. Inż. Rol. 5(114), 177–183 (2009) 12. K. Nęcka, Use of data mining techniques for predicting electric energy demand. TEKA Kom. Mot. i Energ. Roln. XIC, 230–236 (2011) 13. M. Trojanowska, J. Małopolski, Wykorzystanie modeli Takagi-Sugeno do krótkoterminowego prognozowania zapotrzebowania na energię elektryczną odbiorców wiejskich. Inż. Rol. 1(110), 325–330 (2009) 14. K. Nęcka, The use of machine learning technique for short-term forecasting of demand for electricity. J. Res. Appl. Agric. Eng. 59(2), 71–74 (2014) 15. P. Rośczak, Implementacja i wykorzystanie wielowarstwowej sieci perceptronowej w modelowaniu makroekonomicznym. Praca magisterska. Uniwersytet Łódzki, Wydział Ekonomiczno-Socjologiczny, Łódź (2005)

An Adaptive Monitoring System of Heat Storage Using Phase Change Materials Paweł Obstawski, Tomasz Bakoń

and Anna Kozikowska

Abstract Overheat—it is a negative phenomenon which occurs in solar heating systems due to lack of power consumption. As a result, working fluid, in this case propylene glycol, undergoes phase changes by expanding, which shortens its service life and may unseal the installation and cause an air lock. In practice, there are different methods of preventing the installation to overheat such as shading collector surface, installing additional domestic hot water tanks (DHWT). This article presents an alternative method of protection of solar heating system against the effects of overheat by replacing additional domestic hot water tank with tank filled with phase change material (PCM). The proposed solution gives an extra benefit of higher heat capacity of tank filled with phase change material compared to water tank at the same volume and, moreover, there is no need to initiate anti-legionella cycle. Keywords Phase change material monitoring system


Long-term heat and cold storage
Adaptive

1 Introduction The main operational problem with solar heating systems that use liquid flat-plate collectors is an overheat of the installation. An overheat, which is an increase of temperature of a working fluid above boiling point, is a very negative phenomenon that occurs due to lack of power consumption. This is often a consequence of oversizing of collectors segment as compared to the size of thermal storage which is P. Obstawski
T. Bakoń (&)
A. Kozikowska Warsaw University of Life Sciences, Nowoursynowska 166, 02-787 Warsaw, Poland e-mail: [email protected] P. Obstawski e-mail: [email protected] A. Kozikowska e-mail: [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_92

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domestic hot water tank (DHWT). The main problem in this case relates to the project concept which requires solar heating system to cover demand for domestic hot water (DHW) to a large extent. It is obvious that solar thermal installation never operates as a monovalent system which is able to fully cover DHW demand in Polish climate conditions. Solar thermal installation is a part of a hybrid supply system based on heat source that uses conventional energy carrier [1]. The problem of oversizing of solar segment, which in practice means that more than 50% of DHW demand is covered by solar heating system, is caused by the fact of reducing consumption of conventional energy carrier which generates costs in contrast to solar energy. The overheat is a negative phenomenon that causes faster aging of working fluid and may lead unseal the installation and cause an air lock. Obviously, there are methods that protect solar heating system against overheat by installing additional buffer tank that could store surplus heat in short-term period, provide reverse operation of system during night time, shade the surfaces of collectors absorbers or by modifying the absorber surface of flat-plate solar collector. All of the above solutions have advantages as well as disadvantages. It seems, however, that the best solution would be the possibility for long-term storage of surplus heat produced by solar installation. Phase change materials (PCM) give such possibilities.

2 Phase Change Materials Despite the fact that phase change materials have been known since the late 19th century, due to many emerging operational problems such as: PCM storage method, temperature measurement inside PCM tank as well as charge and discharge control system of PCM tank, this technology is still not commonly used. There are large-scale studies focusing on improving meteorological, control and PCM storage technology aspects. The main subject of these studies is to optimise the parameters of the materials used to produce PCM tanks, the sizes and geometry of the exchangers in order to intensify heat transfer between PCM and working fluid which is a heat carrier. The aspects of control the energy conversion process from PCM tank (discharging the tank) and energy conversion to the tank (charging the tank) are also important operational problem. There is a difficulty with controlling the input and output power of PCM tank in order that PCM remains in a phase change. The aspect of using PCM tank as a protection of solar heating system against the effects of overheat as well as the problem with charge and discharge control system of PCM tank shall be presented using the example of simulation tests.

3 Models of Selected Installation Components The simulation tests were performed using the example of system that combines solar thermal installation with 5 liquid flat-plate collectors, 500 dm3 domestic hot water tank and 100 dm3 PCM tank.

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Model of solar heating system was developed using differential equation that describes the process of heat transfer inside liquid flat-plate collector, widely known as Hottel-Whillier-Bliss equation (1) [2]. It is based on the collector energy balance with respect to average temperature of working fluid flowing through the collector. This equation is the general correlation between instantaneous values of input power of collector, power transferred by working fluid and heat losses of collector: ðmcÞeK

dTout ðtÞ _ p  ðTout ðtÞ  Tin ðtÞÞ  ULK ¼ I ðtÞ  AC  FR  mc dt  ðTin ðtÞ  Tamb ðtÞÞ

ð1Þ

where: (mc)eK Tout Tin FR Ac IT ULK Tamb _ m cp

—collector total heat capacity [J/K], —working fluid output temperature [K], —working fluid input temperature [K], —heat removal factor, —collector aperture surface area [m2], —solar irradiation [W/m2], —collector heat losses coefficient [W/m2K], —ambient temperature [K], —working fluid mass flow rate [kg/s], —working fluid specific heat [J/kgK]

Since the temperature of working fluid and ambient temperature are interdependent, Eq. (1) can be simplified and transform into transfer function (2) using Laplace transform in order to analyse dynamic characteristics of solar component.

Tout ðsÞ ¼


_ p ULK Þ ðmc mc _ p 

I ðsÞ þ
Tin ðsÞ ðmcÞeK ðmcÞeK s þ 1 sþ1 _ p _ p mc mc Ac
FR mc _ p

ð2Þ

Domestic hot water tank is the main heat load of solar heating system. Since a working fluid is propylene glycol, heat between solar installation and water in the tank is transferred via a coil-wound heat exchanger placed inside the tank. The temperature increases of water in the tank depend on the amount of heat given by exchanger and heat losses of tank walls. Knowing the amount of heat transferred from exchanger to the tank and heat losses from tank to the environment, the temperature increases can be estimated by using Eq. (3): ðmcÞezas

  _ p Tin ðtÞ  TzasðtÞ dTzas 2ULW mc ¼  ULZ ðTzas ðtÞ  Tamb ðtÞÞ _ p þ ULW dt 2mc

ð3Þ

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where: —tank total heat capacity [J/K], —tank water temperature [K], —exchanger heat losses coefficient [W/m2K], —tank heat losses coefficient [W/m2K], —ambient temperature [K], —working fluid mass flow rate [kg/s], —working fluid specific heat [J/kgK]

(mc)ezas Tzas ULW ULZ Tamb _ m cp

The temperature increase in a domestic hot water tank depends not only on heat capacity of the tank but also on dynamic characteristics of heat exchanger that is placed inside the tank. Dynamic characteristics of the exchanger can be described using differential Eq. (4): ðmcÞeW

  dTout ðtÞ Tin ðtÞ þ Tout ðtÞ _ p ðTin ðtÞ  Tout ðtÞÞ  ULW ¼ mc  Tzas ðtÞ dt 2

ð4Þ

where: (mc)eW Tzas Tout Tin ULW ULZ _ m cp

—exchanger total heat capacity [J/K], —tank water temperature [K], —working fluid output temperature [K], —working fluid input temperature [K], —exchanger heat losses coefficient [W/m2K], —tank heat losses coefficient [W/m2K], —working fluid mass flow rate [kg/s], —working fluid specific heat [J/kgK]

Since DHW tank is provided with thermal insulation, heat losses of the tank are marginal and the temperature of a working fluid depends on the ambient temperature. Therefore, Eqs. (3) and (4) can be simplified and transform from time domain to complex domain using Laplace transform in order to determine dynamic characteristics of the tank (5, 6) [3]. G1 ðsÞ ¼

G 2 ðsÞ ¼

_ p 2ULW mc 2mc _ p ðULW þ ULZ Þ þ ULW ULZ _ p þ ULW ÞðmcÞeZ ð2mc

2mc _ p ðULW þ ULZ Þ þ ULW ULZ s þ 1 ULZ ð2m_ cp þ ULW Þ 2m_ cp ðULW þ ULZ Þ þ ULW ULZ

ð2m_ cp þ ULW ÞðmcÞeZ 2m_ cp ðULW þ ULZ Þ þ ULW ULZ s þ 1

ð5Þ

ð6Þ

The temperature increase in PCM tank as well as in DHW tank depends on output power of solar heating system and output power of tank. Therefore, similarly to DHW tank, model of PCM tank is described by Eqs. (5) and (6). However, there

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is an exception to value of specific heat of phase change material that has a significant impact on value of tank heat capacity. The value of specific heat of phase change material varies depending on temperature of phase change material (Fig. 1). PCM is characterised by limited number of charge and discharge cycles as an electrical accumulator, which affects its durability. Hence, PCM storage tank should operate only in transition phase in a limited temperature range of Tsol and Tliq. The variation of PCM specific heat can be described by Eqs. (7) [4].

cph;c

PCM

¼

8 cph;c > > < hR Tliq > > :

Tsol

cph;c

PCM ;sol

PCM

ðT ÞdT þ Lf

Tliq Tsol cph;c PCM ;liq

i

T\Tsol

9 > > =

Tsol \T\Tliq > > ; T [ Tliq

ð7Þ

where: T Tsol Tliq cph,c,PCM

—PCM temperature [K], —temperature limit of solid phase [K], —temperature limit of liquid phase [K], —PCM storage tank specific heat [J/kgK]

In order to perform simulation tests, it was necessary to describe the curve representing specific heat variation as a function of PCM temperature in transition phase using a function to be integrated so that the current value of PCM storage tank heat capacity can be calculated. Knowing the value of heat capacity, the amount of energy stored in a tank can be estimated. The results of the tests show that it is not possible to describe the curve representing specific heat variation as a function of temperature in transition phase using one mathematical formula. The best solution was to divide the curve into six parts which were described using polynomial functions [5].

Fig. 1 PCM specific heat variation as a function of temperature—basic model

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Knowing the values of temperature limits of solid and liquid phases, which can be found in the catalogue, and the value of latent heat, it is possible to describe the changes in PCM specific heat as a function of temperature.

4 An Adaptive Charge and Discharge Control System of PCM Storage Tank The operational problem with charge and discharge control system of PCM buffer, that was presented in this article, was solved by developing an adaptive monitoring system to control the amount of energy stored in PCM tank, and more precisely to keep the position of operating point in transition phase in a limited temperature range of Tsol and Tliq. As a result, number of PCM phase changes can be limited to the minimum, which maximises service life of tank. Charge and discharge control system of PCM storage tank requires measurement of: volume flow rate as well as flow and return temperatures of working fluid on the primary side (solar thermal installation) and secondary side (output) of PCM tank so that input and output power of PCM tank can be quantified. There are three stages in the algorithm. The first stage is the identification of static and dynamic characteristics of PCM tank. The aim of this stage is to determine effective heat capacity of PCM tank and to define charge and discharge time. Therefore, during identification process, lack of power consumption from PCM tank is required and it is necessary for PCM to remain solid—temperature of PCM must be below Tsol. Knowing the value of temperature limit of solid phase Tsol, temperature limit of liquid phase Tliq and output power of solar installation, tank heat capacity representing fully charged tank can be calculated. The second stage is the stage of operation where tank can be charged or discharged at the same time. The algorithm calculates input and output power of tank, and based on this information and PCM temperature measurements the amount of energy stored in tank can be calculated. If temperature of solid or liquid phase is reached and calculated discharge and charge rates are different from 0% and 100% respectively, the algorithm corrects the amount of energy in PCM tank. The algorithm concept shall be presented using the example of the system that combines solar thermal installation with 5 collectors at aperture surface area of 2 m2 and tank at volume of 100 dm3 filled with PCM at Tsol = 45 °C and cpsol = 18,000 J/kgK, Tliq = 55 °C and cpsol = 20,000 J/kgK, and cplaten = 80,000 J/kgK. The simulation tests were performed in Matlab Simulink environment. The system operation control algorithm as well as an adaptive monitoring system were implemented in State Flow library (Fig. 2). The simulation tests were performed at high and constant solar irradiation value of 1000 W/m2. Figure 3 shows temperature characteristics of solar installation and PCM tank along with charge rate of PCM tank. The simulation was performed at constant flow rate of working fluid of 0.125 kg/s in solar installation, initial temperature of working fluid was 20 °C, the

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Fig. 2 Installation framework implemented in Matlab Simulink

same in solar installation and in PCM tank. Preliminary charging process of PCM tank started in the early stage of system operation (between 0  1430 s). Due to the energy produced in solar installation, temperature of PCM increased and the material changed its state from solid to liquid. The actual charging process started when temperature of PCM reached the value of 45 °C (charge rate of 0%) and lasted until temperature of PCM reached the value of 55 °C—charge rate of 100% (between 1430  3460 s). During that time, solar heating system produced 40.3 MJ of energy that was stored in the tank. Next there was the simulation of

Fig. 3 Temperature characteristics of solar installation and PCM tank along with charge rate of PCM tank at constant flow rate of working fluid of 0.125 kg/s in solar installation

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energy consumption from the tank with the result of 4 kJ/s (3460  4520 s). The process of discharging the tank ended when the charge rate reached 0%, assuming solar installation was not producing any energy that could be stored in PCM tank. The experiment of charging and discharging the PCM tank was repeated twice and the results were similar. The algorithm shall be implemented in microcontroller and tested in operation control system of installation where long-term storage of heat and cold will be possible. This technology shall be tested in three pilot installations located in Austria, Cyprus and Spain. The utilisation of PCM tank as an innovative solution for long-term storage of surplus heat and protection of solar installation against the effects of overheat shall be presented using the simulation results of the system that combines solar thermal installation with 500 dm3 domestic hot water tank and 100 dm3 PCM storage tank (Fig. 4). The simulation was performed at extreme operating conditions of solar installation which can be expected in the summer time when solar irradiation is high. During holiday season there may be temporary lack of DHW consumption, which generally results in high temperatures in DHW tank. The simulation was performed assuming that there was DHW consumption in the morning, thus initial temperature in DHW tank was 30 °C. It was also assumed that PCM tank was discharged so initial temperature in tank was 45 °C. Due to no heat consumption from DHW tank and high doses of solar irradiation of 1000 W/m2, water temperature in tank increased its value from 30 °C to limit value of 80 °C in 2760 s. In practice, controller of solar installation would switch off the heat pump under such conditions (water temperature in DHW tank), which would result in lack of power consumption from solar collectors protecting DHW system against temperature increase above 100 °C. Lack of power consumption

Fig. 4 Temperature characteristics in the system of solar thermal installation loaded by domestic hot water tank (DHWT) and PCM storage tank

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from solar installation would cause temperature increase of working fluid and, as a consequence of overheating, would change its state from liquid to gas. Temperature in solar thermal installation was significantly reduced by installing additional tank filled with phase change material and it helped to avoid overheating of the system. In this case, solar thermal installation produced 552 MJ of energy and PCM tank was powered by 120 MJ of surplus heat.

5 Summary and Conclusions The analysis presented in this article shows that using tank filled with phase change material effectively protects solar thermal installation against the effects of overheat that significantly shortens service life of working fluid as well as has a negative impact on performance parameters of the system and, in extreme cases, may unseal the installation and cause an air lock. PCM storage tank is a good alternative for additional buffer tanks or oversized DHW tanks which are used as a standard solution. PCM buffer has much higher heat capacity compared to conventional DHW tank at the same volume (in this case it is more than 100%), which reduces space requirement necessary to install additional tanks in the boiler room. Moreover, PCM buffer enables the selection of phase change material parameters so that the temperature in transition phase corresponds to required temperature of DHW (as in this case). Another benefit of using PCM buffer is that there is no need to initiate anti-legionella cycle in DHW tank and repeat it once a day, which requires increasing temperature above 60 °C in DHWT. Acknowledgements Presented research results were funded from the TESSe2b project, that is financially supported by the Horizon 2020 Research Innovation Action (RIA) of the European Commission, call EeB-Energy-efficient Buildings (Grant Agreement 680555).

References 1. A. Chochowski, D. Czekalski, P. Obstawski, Monitorowanie funkcjonowania hybrydowego systemu odnawialnych źródeł energii. Przegląd elektrotechiczny 8, 92–95 (2009) 2. J. Duffie, W. Beckman, Solar Energy Thermal Processes (J. Willey and Sons, New York, 1974) 3. P. Obstawski, Identyfikacja parametryczna w diagnostyce słonecznych instalacji grzewczych (Wydawnictwo SGGW, Warszawa, 2013) 4. S. Aren, Modelling, design and analysis of innovative thermal energy storage systems using PCM for industrial processes, heat and power generation. Università degli Studi di Cagliari (2015) 5. T. Bakoń, P. Obstawski, A. Kozikowska, Modelling of heat storage using phase change material tank, in Renewable Energy Sources: Engineering, Technology, Innovation. Springer Proceedings in Energy (Springer, Cham 2018)

Test and Implementation of Control Algorithm in Hybrid Energy System with Phase Change Material Storage Tank in State Flow Matlab Toolbox Paweł Obstawski, Tomasz Bakoń

and Anna Kozikowska

Abstract Control algorithm is the most important element of hybrid energy system while it is in operation. It determines energy effects of each segment of system, which has influence on efficiency of whole system and operating costs. This paper presents the results of research studies which enabled control algorithm of hybrid energy system combining heat pump, solar installation and phase change material (PCM) storage tank to be tested and optimised. Matlab Simulink software was used to perform simulations. A great advantage of this software is the possibility to compile and implement control algorithm in programmable logic controller (PLC). The algorithm that was implemented in PLC is in form of function block diagram, which makes the entire PLC programme very clear. Keywords PLC


Hybrid energy system
PCM storage tank

1 Introduction Green energy sources, for example, solar radiation, wind etc. have lower density of energy compared to conventional sources. Due to this fact, renewable sources of energy are connected in hybrid energy system in order to provide continuous power supply for the system [1, 2]. One of the most popular connection is solar thermal installation and heat pump. Geothermal energy is more stable than solar energy, so heat pump plays a dominant role in hybrid energy system, but it needs electric energy to power compressor. Operating costs depend on prices of electric energy. There are availP. Obstawski
T. Bakoń (&)
A. Kozikowska Warsaw University of Life Sciences, Nowoursynowska 166, 02-787 Warsaw, Poland e-mail: [email protected] P. Obstawski e-mail: [email protected] A. Kozikowska e-mail: [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_93

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able special electric energy tariffs for heat pump users in many European Union countries. These tariffs regulate prices of electric energy throughout the day. Prices depend on supply and demand of electric energy in network. This means that operation of heat pump is economical in periods, when there are lower prices for electric energy. It requires heat demand of building to adapt to periods of lower prices for electric energy. This requirement is impossible to achieve in operating conditions. The solution of this problem is to use heat storage system based on the phase change materials (PCM).

2 Heat Pump, Solar Collectors and PCM Storage Tank in Hybrid Energy System Due to the fact that phase change materials change value of specific heat as a function of temperature, it is possible to store heat or cold in a long period of time. The analysis of long-term heat storage shall be presented in this paper. The main problem with phase change materials is loss of accumulation abilities during phase changes from solid to liquid or from liquid to solid. Thus, it is required to keep temperature between solid and liquid areas as PCM storage tank is in operation. This means that temperature between solid and liquid phase should match the operating temperature of PCM storage tank. Due to this, the most important element of hybrid energy system operation is control algorithm.

3 Analysis of Control Algorithm of Hybrid Energy System The best way to design and develop control algorithm of hybrid energy system is to perform simulation tests of how selected segments of the system work together. Matlab Simulink is one of a tool to perform simulations, test and optimise control algorithm. Additional advantage of this software is the possibility to compile control algorithm to SCL language and implement it in programmable logic controller (PLC). It is very important that models of selected segments of hybrid energy system, that were used in simulations, include their static and dynamic characteristics. These models are described in papers [3, 4]. Each model of hybrid energy system components such as: solar collectors (SC), domestic hot water tank (DHWT), heat pump (HP), hot PCM storage tank was implemented in Matlab Simulink State Flow Toolbox. Despite the fact that the models are very simple, their implementation and connection was very difficult, and consequently the structure of the whole system is very complicated (Fig. 1). The most important values and parameters were set on the hydraulic scheme of the system in order to simplify analysis of simulated hybrid energy system

Fig. 1 Structure of DHW tank model and three-way valve in Matlab Simulink

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Fig. 2 Final solution of hybrid energy system simulation

operation. This solution enables applications similar to SCADA environment to be developed (Fig. 2) [5]. This application enables hybrid energy system operation to be visualised and values of crucial parameters of selected system segments to be changed, for example flow rate during simulations. Control algorithm was implemented in State Flow Matlab Toolbox. This tool gives the possibility to implement and test control algorithm using standard functions available in PLC such as: timers, counters, logical and math functions, etc. Control algorithm was implemented in a very similar way to typical PLC using LAD programming language. It is important to

Fig. 3 Part of control algorithm of solar installation and heat pump

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Fig. 4 Example of control algorithm simulation of system combining solar installation, DHW tank and PCM tank

define parameters, and if all parameters which are located on the LAD network are reached, state of digital output changes, for example from logical 0 to logical 1 (Fig. 3). Different parts of control algorithm can be done as “OR” or “AND” logical. Functions of this tool shall be presented and analysed using the example of system combining solar installation, DHW tank and PCM tank. Figure 4 shows simulation results of this system while it is in operation. Initial parameters of control algorithm simulations were: constant solar radiation value of 1000 W/m2 and temperature value of 20 °C in DHW and PCM storage tank. Phase change material that was used in simulations is characterised by solid phase temperature of 45 °C, liquid phase temperature of 55 °C and latent heat of 50 °C. The volume of PCM storage tank was 100 dm3. Solar installation was built with five solar collectors. Aperture surface area of each collector was 2 m2. The volume of DHW tank was 200 dm3. Glycol that was used as a working fluid in solar installation is charcterised by the specific heat value of 3580 J/kgK. Simulations were performed at constant flow rate of 0.138 kg/s in solar installation. The main role of solar installation is to transfer energy to DHW tank so it can be stored. If temperature difference between working fluid and DHW tank is higher than 10 K, controller starts solar pump and DHW tank charges within 1200 s (Fig. 4). Set point temperature in DHW tank was 45 °C. When set point in DHW tank was reached, controller changed position of two-way valves and energy absorbed by solar collectors was transferred to PCM storage tank (time 12003900 s) (Fig. 4). While PCM storage tank was charging, flow rate of working fluid in solar installation was changed from 0.138 kg/s to 0.148 kg/s and after 400 s to 0.138 kg/s. As a result, difference between input and output

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temperature in solar installation changed. Due to DHW consumption during charging process of PCM storage tank and transition phase of PCM, temperature of water in DHW tank decreased below 40 °C, and as a result controller changed position of two-way valves. Energy absorbed by solar installation was transferred to DHW tank. When temperature of water reached set point of 45 °C in DHW tank, controller changed position of two-way valves and solar installation started to operate again together with PCM storage tank. After that, when PCM reached liquid phase temperature, due to high value of solar radiation of 1000 W/m2 and possibility of charging DHW tank (water temperature of 45 °C), solar installation started to operate together with DHW tank. Simultaneously, value of solar radiation decreased to 450 W/m2. In consequence, temperature difference between working fluid and DHW tank was lower than stop set value of solar pump. Due to lack of working fluid flow in solar system, temperature increased above control set value. This means that controller must periodically start and stop solar pump. The following simulation of control algorithm tested how the system operates when solar radiation is low and temperature in DHW tank is high. As a result of DHW consumption, temperature of water decreased to 62 °C. Next, solar pump ran continuously until temperature of DHW increased to 68 °C and after that solar pump was periodically in operation. Description of Fig. 4: T1 T2 T3 T4 T5 T6

– – – – – –

inlet temperature of DHW tank (outlet temperature of solar collectors) [°C], temperature in DHW tank [°C], outlet temperature of DHW tank (inlet temperature of solar collectors) [°C], inlet temperature of PCM tank [°C], PCM tank temperature [°C], outlet temperature of PCM tank [°C]

After testing control algorithm, it is possible to implement it in PLC programme. At this stage control algorithm should be completed, and then it is possible to generate the structure of control algorithm using language dedicated for one of possible to select from programmable logic controllers (Fig. 5). After generating the structure of control algorithm, it should be implemented in State Flow Matlab Toolbox where programming PLC as external source file and generating code is possible. Next, compiled controller transforms into simpler block with empty places for input and output signals ready to use. It is necessary to define memory areas of

Fig. 5 Generation of control algorithm code for one of PLC

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Fig. 6 Compilation of controller in PLC software

PLC for input and output values in these empty places and upload whole block to PLC (Fig. 6). After these procedures controller is ready to work.

4 Summary and Conclusions The solution presented in this paper is very simple and useful. It gives the possibility to design and test control algorithm of hybrid energy systems and implement it in programmable logic controller. It should be noted that design time of control algorithm is very short and there is no need to rewrite tested control algorithm in PLC software. It is very important that compiled control algorithm is implemented in PLC as homogeneous block. This solution simplifies the structure of PLC programme. Otherwise, implementation of control algorithm tested in Matlab Simulink would require many lines in LAD language in PLC programme, which could adversely affect its clarity. Acknowledgements Presented research results were funded from the TESSe2b project, that is financially supported by the Horizon 2020 Research Innovation Action (RIA) of the European Commission, call EeB-Energy-efficient Buildings (Grant Agreement 680555).

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References 1. A. Chochowski, P. Obstawski, D. Czekalski, Właściwości dynamiczne płaskich kolektorów słonecznych. Przegląd Elektrotechiczny 6, 92–95 (2010) 2. D. Czekalski, A. Chochowski, P. Obstawski, Parametrization of daily solar irradiance variation. Renew. Sustain. Energy Rev. 16, 2461–2467 (2012) 3. P. Obstawski, T. Bakoń, J. Gajkowski, Analysis of models applied for modelling of adaptive control for thermal energy storage system. Part 2 – Models of heat pump, borehole heat exchanger and phase change material tank. Ann. Warsaw Univ. Life Sci. – SGGW Agric. 71, 73–87 (2018). https://doi.org/10.22630/aafe.2018.71.8 4. P. Obstawski, T. Bakoń, Analysis of models applied for modelling of adaptive control for thermal energy storage system. Part 1 – Models of solar collector. Ann. Warsaw Univ. Life Sci. – SGGW, Agric. 71, 61–72 (2018). https://doi.org/10.22630/aafe.2018.71.7 5. P. Obstawski, D. Czekalski, Zastosowanie programu SCADA do wizualizacji i monitoringu pracy hybrydowego systemu zasilania. Zeszyty Naukowe Politechniki Rzeszowskiej 59/2/II (2012)

Optimization of the Parameters for the Process of Grain Cooling Igor Palamarchuk , Sergey Kiurchev , Valentyna Verkholantseva , Nadiia Palianychka and Olena Hryhorenko

Abstract Among the classical technologies, which apply elevated temperatures for preserving of grain and cereal products, there are two the most effective ones, currently used all over the world. The indicators are storage of cooled fresh raw materials in adjustable or modified gas environment and a long-term storage in a frozen state. The study dealt the first technology which employed active ventilation by the flow of refrigerant. Qualitative parameters for optimization of the investigated process included the mass fraction of gluten, moisture in raw materials, volume of air supplied, and the product processing temperature. On the base of a rootable, central-composite planning of a multifactorial experiment, a mathematical model for the data distribution was obtained. The obtained mathematical models, which are presented in the form of a multiple regression of the second order, allowed to describe the process of grain products storage adequately. As a result, we determined the optimal technological parameters for the equipment operation while studying the humidity of the processed materials, volumetric flow of air as well. Keywords Grain


Optimization
Cooling
Storage
Process
Parameters

1 Introduction Cooling of food products with subsequent storage at appropriate low temperatures is one of the best methods for preventing or slowing down product damage, ensuring the most complete storage of their original natural properties. The goal is achieved as a result of suspension of microorganisms and pathogenic microflora I. Palamarchuk National University of Life and Environmental Sciences of Ukraine Kyiv, Heroes of Defense 15, Kyiv 03041, Ukraine S. Kiurchev
V. Verkholantseva (&)
N. Palianychka
O. Hryhorenko Tavria State Agrotechnological University, B. Khmelnitsky ave., 18, Melitopol 72312, Ukraine e-mail: [email protected] © Springer Nature Switzerland AG 2020 M. Wróbel et al. (eds.), Renewable Energy Sources: Engineering, Technology, Innovation, Springer Proceedings in Energy, https://doi.org/10.1007/978-3-030-13888-2_94

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viability, as well as reduction of the rate of chemical and biochemical processes which occur in the product under the influence of its own enzymes, oxygen, air, heat and light [1–5]. To supply market, processing and food industries two methods of products canning are used: • processing and storage when the temperature is above the level of freezing of the fabric fluid. The process is used for the food products cooling and maintaining the state; • processing and storage when the temperature is significantly lower than the freezing point of the fabric fluid. This is the method of freezing and storing food in frozen form. The production of frozen food is associated with higher power expenditures for the process, much higher costs for cooling which maintains frozen products, rising costs due to lower qualitative characteristics and negative effects of irreversible processes, although at the time of freezing the most complete storage of the main quality indicators provides a long-term storage of food products [2, 3, 6–8]. According to the recent research, if we consider physical, mechanical and morphological properties of grain and grain and cereal products, it is expedient to keep the products in a cooled state. To intensify this process, we used active ventilation of the product by the flow of the refrigerant, which was preliminary heated by the raw material to increase the driving force in the heat exchange as well as creation of a fluidized bed of bulk mass [7]. This substantiates the relevance of the effective modes choice for technological processing. Statistical analysis of the qualitative parameters for the raw material was performed. It was based on the results of preliminary experimental data which we obtained after investigation of grain storage processes with the application of designed method and equipment (Table 1). The qualitative parameter for optimization of the investigated process is determined by the mass fraction of gluten К, %: ð1Þ where W is moisture content in raw materials, %; P is volumetric air supply, m3 per hour; T is the temperature of raw material processing, °C. The power characteristic of the investigated process will have the following functional interpretation: ð2Þ Investigation of the influence of the mentioned above factors on the technological and power parameters of the studied process during the implementation of one-factor experiments is quite difficult and labor-intensive. Therefore, it is advisable to carry

Optimization of the Parameters for the Process of Grain Cooling Table 1 Intervals for grouping original samples of qualitative parameters of investigated processes

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Experimental data Periodicity

For the technological indicator 19 < x  20 2 20 < x  21 6 21 < x  22 4 22 < x  23 6 23 < x  24 5 25 < x  26 3 26 < x  27 4 For power characteristics 8