PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION

2025 Edited by Igor Krasnikov PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION Collective monograph Copyright © Author(s) 2025 This is an open access paper under the Creative Commons Attribution 4.0 International License (CC BY 4.0) UDC 621.311 E54 Published in 2025 by TECHNOLOGY CENTER PC ® Shatylova dacha str., 4, Kharkiv, Ukraine, 61165 E54 Authors: Edited by Igor Krasnikov Igor Krasnikov, Anatolii Babichenko, Juliya Babichenko, Oleksandr Dzevochko, Yana Kravchenko, Ihor Lysachenko, Valerii Samsonkin, Valerii Druz, Oksana Yurchenko, Vitalii Budashko, Oksana Glazeva, Albert Sandler, Sergii Khniunin, Valentyn Bogach, Yurii Zhuravlov, Petro Lezhniuk, Viacheslav Komar, Vladyslav Lysyi, Yuliia Malohulko, Volodymyr Netrebskyi, Olena Sikorska, Oleksandr Povazhnyi, Volodymyr Kukhar, Oleksiy Koyfman, Khrystyna Malii, Volodymyr Pashynskyi Processes and control systems: synthesis, modeling, optimization: collective monograph. – Kharkiv: TECHNOLOGY CENTER PC, 2025. – 192 p. This monograph is a complex scientific and applied work covering the most important directions in the field of sustainable energy, materials science and environmental safety. The studies and recommendations presented in it have practical significance and can be used for further development of scientific and technological solutions in this field. The results presented in the monograph can be useful in the development of new solutions for the energy industry, in the design of renewable energy systems, in the sphere of waste utilisation and in the issues of reducing the environmental impact of industrial facilities. The obtained data and recommendations are intended for a wide range of specialists, including engineers, developers, scientists, designers, as well as undergraduate and postgraduate students of technical areas of training. Figures 88, Tables 41, References 147 items. This book contains information obtained from authentic and highly regarded sources. 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Trademark Notice: product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. DOI: 10.15587/978-617-8360-19-1 ISBN 978-617-8360-19-1 (on-line) Cite as: Krasnikov, I. (Ed.) (2025). Processes and control systems: synthesis, modeling, optimization. Kharkiv: ТЕСHNOLOGY СЕNTЕR PC, 192. doi: http://doi.org/10.15587/978-617-8360-19-1 9 786178 360023 9 786178 360191 iii authors chapter 1 Igor Krasnikov PhD, Associate Professor Department of Technology System Automation and Ecology Monitoring National Technical University "Kharkiv Polytechnic Institute" ORCID: https://orcid.org/0000-0002-7663-1816 Anatolii Babichenko PhD, Associate Professor Department of Technology System Automation and Ecology Monitoring National Technical University "Kharkiv Polytechnic Institute" ORCID: https://orcid.org/0000-0002-8649-9417 Juliya Babichenko PhD, Associate Professor Department of Heat Engineering, Heat Engines and Energy Management Ukrainian State University of Railway Transport ORCID: https://orcid.org/0000-0002-5345-7595 Oleksandr Dzevochko PhD, Associate Professor Department of Technology System Automation and Ecology Monitoring National Technical University "Kharkiv Polytechnic Institute" ORCID: https://orcid.org/0000-0002-1297-1045 Yana Kravchenko РhD Department of Technology System Automation and Ecology Monitoring National Technical University "Kharkiv Polytechnic Institute" ORCID: https://orcid.org/0000-0002-6311-8060 Ihor Lysachenko PhD, Associate Professor Department of Technology System Automation and Ecology Monitoring National Technical University "Kharkiv Polytechnic Institute" ORCID: https://orcid.org/0000-0002-7388-1385 chapter 2 Valerii Samsonkin Doctor of Technical Sciences, Professor Department of Transport Technology and Process Control Traffic National Transport University ORCID: https://orcid.org/0000-0002-1521-2263 Valerii Druz Doctor of Biological Sciences, Professor Department of Radioelectronic and Biomedical Computerised Means and Technologies National Aerospace University "Kharkiv Aviation Institute" ORCID: https://orcid.org/0009-0004-5808-2456 Oksana Yurchenko PhD, Associate Professor Department of Management of Commercial Activity of Railways National Transport University ORCID: https://orcid.org/0000-0001-6834-692X Vitalii Budashko Doctor of Technical Sciences, Professor, Director Educational and Scientific Institute of Automation and Electrical Engineeringe National University "Odessa Maritime Academy" ORCID: https://orcid.org/0000-0003-4873-5236 Oksana Glazeva PhD, Associate Professor Department of Electrical Engineering and Electronics National University "Odessa Maritime Academy" ORCID: https://orcid.org/0000-0002-4992-7697 chapter 3 Albert Sandler PhD, Associate Professor Department of the Theory of Automatic Control and Computer Technology National University "Odessa Maritime Academy" ORCID: https://orcid.org/0000-0003-0655-4379 iv PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION Valentyn Bogach PhD, Associate Professor Department of Engineering Mechanics and Ship Repair National University "Odessa Maritime Academy" ORCID: https://orcid.org/0000-0002-0822-0003 Yurii Zhuravlov PhD, Associate Professor Department of Engineering Mechanics and Ship Repair National University "Odessa Maritime Academy" ORCID: https://orcid.org/0000-0001-7342-1031 Petro Lezhniuk Doctor of Technical Sciences, Professor Department of Electric Power Stations and Systems Vinnytsia National Technical University ORCID: https://orcid.org/0000-0003-0338-2131 Viacheslav Komar Doctor of Technical Sciences, Professor, Head of Department Department of Electric Power Stations and Systems Vinnytsia National Technical University ORCID: https://orcid.org/0000-0003-4969-8553 Vladyslav Lysyi PhD Student Department No. 3 Wind Power Institute of Renewable Energy of the National Academy of Sciences of Ukraine ORCID: https://orcid.org/0009-0007-0211-9100 chapter 4 Yuliia Malohulko PhD, Associate Professor Department of Electric Power Stations and Systems Vinnytsia National Technical University ORCID: https://orcid.org/0000-0002-6637-7391 Volodymyr Netrebskyi PhD, Associate Professor Department of Electric Power Stations and Systems Vinnytsia National Technical University ORCID: https://orcid.org/0000-0003-2855-1253 Olena Sikorska PhD, Associate Professor Department of Electric Power Stations and Systems Vinnytsia National Technical University ORCID: https://orcid.org/0000-0003-3123-1971 Oleksandr Povazhnyi Doctor of Economic Sciences, Professor, Rector Technical University “Metinvest Polytechnic” LLC ORCID: https://orcid.org/0000-0002-9835-6464 Volodymyr Kukhar Doctor of Technical Sciences, Professor, Vice-Rector for Research Department of Metallurgy and Production Organization Technical University “Metinvest Polytechnic” LLC ORCID: https://orcid.org/0000-0002-4863-7233 Oleksiy Koyfman PhD, Associate Professor, Head of Department Department of Automation, Electrical and Robotic Systems Technical University “Metinvest Polytechnic” LLC ORCID: https://orcid.org/0000-0003-2075-7417 Khrystyna Malii PhD, Associate Professor, Head of Department Department of Metallurgy and Production Organization Technical University “Metinvest Polytechnic” LLC ORCID: https://orcid.org/0000-0002-9046-4268 Volodymyr Pashynskyi Doctor of Technical Sciences, Associate Professor, Head of Department Department of Materials Science and Applied Mechanics Technical University “Metinvest Polytechnic” LLC ORCID: https://orcid.org/0000-0003-0118-4748 chapter 5 Sergii Khniunin PhD, Associate Professor Department of Information Technology International Humanitarian University ORCID: https://orcid.org/0000-0001-5941-5372 v The monograph "Processes and control systems: synthesis, modeling, optimization" is devoted to topical issues in the field of energy, materials science and sustainable development, including the study of magnetic field effect on silicon microstructure, development of innovative designs of solar concentrators, use of solid domestic waste in the energy balance of Ukraine, as well as the prospects and technologies of co-combustion of coal and biomass at thermal power plants. In "Technological aspects of computer control of the secondary condensation complex of ammonia production under uncertainty", within the framework of research on the influence of magnetic field on the microstructure of silicon grown by the Czochralsky method (Cz-Si), doped with elements Al, Mg, Cu, Fe, Zr, Hf, the influence of these impurities on the interaction energy of silicon atoms in the crystal lattice is considered for the first time. It is found that doping with elements reducing the interaction energy leads to an increase in defects during magnetic treatment for 240 hours, while 720 hours of treatment reduces their number. In "Management of transport systems and processes based on a unified theory of self-organizing systems" of the monograph is devoted to the development of improved designs of solar concentrators used in the field of green energy. The research is aimed at reducing production costs and increasing efficiency by reducing the number of metal elements and introducing automated assembly processes. The developed new design with fewer elements contributes to cheaper production and faster assembly process. The prototypes can find wide application in agriculture, organic waste recycling and energy supply of residential buildings within the concept of "green" buildings. In "Improvement of the method of linear-quadratic control of azimuthal drivers of the combined propulsion complexl" special attention is paid to the issues of involvement of solid domestic waste in the energy balance of Ukraine by creating alternative solid fuel (RDF - refuse derived fuel). The kinetics of convective drying of RDF of different compositions depending on temperature and speed of the heat carrier is investigated. Drying coefficients, rates of thermal decomposition of organic and mineral substances, as well as calorific value of RDF are determined. The results obtained are the basis for the development of energy-efficient RDF production technologies to reduce dependence on fossil fuels. The "Intelligentization of control systems for local electric power systems" considers the current state and prospects of the energy complex of Ukraine. Based on the analysis of available energy resources, the methodology of selection and justification of priority fuels for regional energy supply is proposed. Environmental aspects of utilisation of traditional resources such as coal, oil, gas and nuclear fuel are considered, as well as the possibilities of transition to alternative energy sources. The "Improving condition monitoring and maintenance framework for refractory linings in induction melting furnaces through continuous improvement methods" is devoted to the development abstract PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION vi of technologies for co-combustion of coal and biomass, which is a promising direction for reducing emissions of harmful substances, diversifying fuel sources and improving combustion conditions at thermal power plants. The technologies of biomass combustion and gasification are considered, experimental studies of co-combustion of gas coal and biomass are carried out, thermal calculations of boiler plants using ANSYS FLUENT are performed. Recommendations for implementation of these technologies at Ukrainian TPPs were developed. Thus, the results presented in the monograph are an important contribution to the solution of urgent problems in the field of sustainable energy, material science and environmental safety. The monograph will be useful for engineers, researchers, designers and specialists working in the field of energy, waste processing and development of "green" technologies. Keywords Silicon, magnetic field, doping, crystal lattice defects, solar concentrators, alternative energy, production automation, municipal solid waste, refuse-derived fuel, thermal decomposition, energy efficiency, co-firing, biomass, greenhouse gas emissions, energy balance, convective drying, environmental safety, crystalline structure, phase transformations, computer modeling. Circle of readers and scope of application This monograph is a complex scientific and applied work covering the most important directions in the field of sustainable energy, materials science and environmental safety. The studies and recommendations presented in it have practical significance and can be used for further development of scientific and technological solutions in this field. The results presented in the monograph can be useful in the development of new solutions for the energy industry, in the design of renewable energy systems, in the sphere of waste utilisation and in the issues of reducing the environmental impact of industrial facilities. The obtained data and recommendations are intended for a wide range of specialists, including engineers, developers, scientists, designers, as well as undergraduate and postgraduate students of technical areas of training. vii contents List of Tables .....................................................................................................................ix List of Figures ....................................................................................................................xi Introduction.......................................................................................................................1 Chapter 1. Technological aspects of computer control of the secondary condensation complex of ammonia production under uncertainty ............................................................3 1.1 Earlier research findings and relevant literature review .........................................5 1.1.1 Crystallochemical peculiarities of semiconductor silicon .............................5 1.1.2 Phase transformations in semiconductor silicon .......................................6 1.1.3 Martensitic transformation mechanisms in silicon ..................................11 1.1.4 General problems on magnetic field effect on "nonmagnetic" substances .........................................................................................12 1.1.5 The nature of Nernst-Ettingshausen effect ............................................17 1.1.6 Magnetoplastic effect in diamagnetic crystals ........................................18 1.2 Materials and methods of the study ..................................................................23 1.2.1 Study materials...................................................................................23 1.3 Microstructures of the samples before and after the magnetic field treatment .....25 1.4 The sample microhardness values before and after treating with the magnetic field ............................................................................................37 1.5 The physical parameters of the samples before and after treating with the magnetic field ............................................................................................46 Conclusions .............................................................................................................49 References..............................................................................................................51 Chapter 2. Management of transport systems and processes based on a unified theory of self-organizing systems ...............................................................................................54 2.1 Literature review and problem statement ..........................................................56 2.1.1 Existed prototypes of solar concentrators .............................................57 2.1.2 Applications of solar concentrators .......................................................61 2.2 The aim and objectives of the study ...................................................................62 2.3 Materials and methods ....................................................................................63 2.3.1 Object and hypothesis of the study .......................................................63 2.3.1.1 First model ..........................................................................63 2.3.1.2 Number of mirrors ................................................................65 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION viii 2.3.2 Materials ...........................................................................................65 2.3.3 Methods ............................................................................................66 2.3.4 Software ............................................................................................68 2.4 New structure of solar concentrator with flat triangular mirrors .........................68 2.4.1 Reducing the number of structural elements ..........................................68 2.4.2 Calculation of structural elements .........................................................70 2.5 Discussion ......................................................................................................71 Conclusions .............................................................................................................72 References..............................................................................................................73 Chapter 3. Improvement of the method of linear-quadratic control of azimuthal drivers of the combined propulsion complex ................................................................................76 3.1 Analytical review and analysis ...........................................................................77 3.1.1 Municipal solid waste and fuel from it ....................................................77 3.1.2 Technologies of obtaining RDF/SRF ........................................................79 3.2 Study of regularity of RDF convective drying ......................................................83 3.2.1 Preparation of municipal solid waste for drying .......................................83 3.2.2 Research of drying modes of RDF .........................................................85 3.2.3 Research of heat and mass exchange processes during drying RDF ..........89 3.3 RDF thermal analysis .......................................................................................91 3.3.1 Research technique for thermal decomposition of RDF ............................92 3.3.2 Results of the derivatographic studies of RDF ........................................94 Conclusions ...........................................................................................................102 References............................................................................................................102 Chapter 4. Intelligentization of control systems for local electric power systems ..........106 4.1 State and prospects for the development of the energy sector of Ukraine ..........107 4.1.1 Hydropower ......................................................................................109 4.1.2 Wind power ......................................................................................110 4.1.2.1 Disadvantages of modern wind power plants .........................112 4.1.3 Solar energy .....................................................................................112 4.1.3.1 Disadvantages of solar energy .............................................115 4.1.4 Bioenergy .........................................................................................116 4.1.4.1 Advantages and disadvantages of bioenergy ..........................120 4.1.5 Thermal power ..................................................................................121 4.1.6 Nuclear energy .................................................................................125 4.2 Methodology for substantiating the choice of the type of energy resource for the region ................................................................................................127 4.2.1 Comprehensive assessment of efficiency indicators of energy resources 128 contents ix 4.2.1.1 Analysis of existing comprehensive assessments ...................131 4.2.1.2 Environmental pollution indicators and their standardization ....132 4.2.1.3 Combined normalization of resource efficiency and environmental pollution indicators .........................................133 4.2.2 Results of polluting capacity assessment .............................................134 4.2.3 Using a complex indicator for resource selection ..................................134 Conclusions ...........................................................................................................138 References............................................................................................................139 Chapter 5. Improving condition monitoring and maintenance framework for refractory linings in induction melting furnaces through continuous improvement methods ...........144 5.1 Coal and solid biofuel co-firing technologies ......................................................148 5.1.1 Existing biomass and coal co-firing technologies ....................................148 5.1.2 Current biomass research ..................................................................150 5.2 Experimental study of joint pulverized combustion of bituminous coal and biomass ..................................................................................................152 5.3 Verification of the obtained results by performing engineering calculations using the normative method ....................................................................................158 5.4 Calculation of co-firing of coal with biomass for selected schematic solutions of the biomass feed system to the boiler furnace .................................................163 5.4.1 Initial conditions for modeling co-firing .................................................163 5.4.2 Main results of modeling in the mode without pellet input .....................166 5.4.3 Main results of modeling in the mode with the feeding of pellets ............169 5.5 Recommendations for the use of co-firing of coal and biomass at Ukrainian TPPs ..............................................................................................172 References............................................................................................................173 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION xvi 5.12 Comparison of heat flux densities in the walls of zones according to the results of numerical modeling with the data of zone-by-zone calculations using the normative method 168 5.13 Distribution of coke burnout intensity by fuel height according to the results of numerical modeling and according to the data of the zone calculation by the normative method 169 5.14 Temperature fields in the mode with the feeding of 10% pine pellets in sections along the burners, 3–10 (a), 1–12 (b) and along the z axis (c) 170 5.15 Effect of pellet feeding on mass average temperatures at the zones outlet 5.16 Coke burnout intensities of coal (a) and pellets (b), as well as the devolatilization intensities of coal (c) and outputs (d) in the cross section of burners 3–10. White field – exceeding the upper limit of the scale 170 5.17 The effect of pellet particle size on the efficiency of coal and pellet coke burnout 171 1 Introduction Modern global challenges in the field of energy, ecology and resource conservation require a systematic approach and search for innovative solutions aimed at improving energy efficiency, introduction of renewable energy sources and rational use of natural resources. The rapid depletion of traditional fuels such as coal, oil and gas leads to the need to develop new technologies that ensure stable energy supply with minimal environmental impact. In addition, increasing volumes of industrial and domestic waste, as well as increasingly stringent environmental requirements for enterprises, create additional challenges for the energy sector and industry as a whole. In this regard, studies aimed at developing new materials, technologies and approaches to the organisation of energy systems that could ensure high efficiency and environmental safety are becoming relevant. This monograph is devoted to a comprehensive study of some of the most important areas in the field of materials science, alternative energy and sustainable development, which are of strategic importance for modern industry and energy. The following key issues are discussed in detail in the monograph: – the influence of a magnetic field on the microstructure of silicon grown by the Czochralsky method (Cz-Si) doped with the elements Al, Mg, Cu, Fe, Zr, and Hf. For the first time in scientific practice the study of structural changes of silicon under the influence of magnetic field and the influence of various impurities on its crystal lattice is carried out. The research shows that these elements differently affect the interaction energy of silicon atoms in the lattice and behave differently under the influence of a magnetic field. The results may be useful for the production of semiconductor materials with improved characteristics, which is critical for microelectronics and solar energy; – development of innovative designs of solar concentrators. The work explores the issues of improving the technological efficiency and reducing the production cost of solar concentrators, which plays a key role in the development of alternative energy. The existing designs have been analysed and new solutions have been proposed, aimed at reducing the weight of structural elements, reducing assembly costs and increasing the ease of operation. The developed prototypes of solar concentrators can be widely applied in agriculture, in power supply systems of residential buildings and in organic waste recycling processes; – utilisation of municipal solid waste (MSW) in the energy balance of Ukraine. One of the most important directions of sustainable development is the processing and utilisation of waste for its further use as an alternative energy source. In this paper the physical and chemical properties of RDF (refuse-derived fuel) - an alternative solid fuel produced from combustible components of MSW are investigated. The kinetics of drying, thermal decomposition and calorific value of RDF of different compositions were analysed. The obtained data can contribute to the development of energy-efficient technologies of RDF production and its effective application at thermal power plants; 2 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION – analysis of the state and prospects of development of the energy complex of Ukraine. An important part of the monograph is the analysis of the structure of the energy balance of the country, identification of key problems and proposals to improve the current situation. The issues of using traditional energy resources, such as coal, oil, gas and nuclear fuel, as well as the prospects of transition to renewable energy sources are considered. A methodology for selecting optimal energy strategies for different regions, taking into account environmental and economic factors, is propose; – co-firing of coal and biomass as a way to reduce harmful emissions. The work is aimed at the development of coal and biomass co-combustion technologies, which allows to reduce CO2, SO2 and NOx emissions, diversify fuel sources and increase the sustainability of energy systems. The basic principles of co-combustion are investigated, heat engineering calculations are performed, and experiments on co-combustion of gas coal and biomass are carried out. Recommendations for the introduction of technologies at TPPs have been developed, which can contribute to the improvement of energy efficiency and environmental safety. Modern methods and approaches, including X-ray diffraction analysis, thermogravimetric analysis, computer modelling in ANSYS FLUENT software packages, as well as experimental methods of measuring and controlling the characteristics of materials were used in the research within the framework of this work. The results presented in the monograph can be useful in the development of new solutions for the energy industry, in the design of renewable energy systems, in the sphere of waste utilisation and in the issues of reducing the environmental impact of industrial facilities. The obtained data and recommendations are intended for a wide range of specialists, including engineers, developers, scientists, designers, as well as undergraduate and postgraduate students of technical areas of training. Thus, this monograph is a complex scientific and applied work covering the most important directions in the field of sustainable energy, materials science and environmental safety. The studies and recommendations presented in it have practical significance and can be used for further development of scientific and technological solutions in this field. 3 CHAPTER 1 CHAPTER 1 abstract The current publication reports on the magnetic field influence on the microstructure of Cz-Si doped with Al, Mg, Cu, Fe, Zr, Hf. The point is that these dopants have different effects on the interaction energy of silicon atoms in its crystal lattice and differently behave under magnetic field treatment. In this context, the problem of silicon processing is first time addressed. It is established that the dopants (Al, Mg, Cu, Fe), which decrease the energy of atom interaction within the crystal lattice of silicon, lead to the increase in the defects of the silicon structural units after 240 hours of magnetic field treatment while 720 hours produce the decrease in the quantity of such defects. Cz-Si doped with Zr, Hf (these dopants increase the interaction energy of the silicon crystal lattice) experiences the decrease in the quantity of defects in the structural units starting from 240 of exposing to the magnetic field. By means of X-ray diffraction technique, the occurrence of new peaks on the scattering angles of 90–92 degrees has been detected, that is due to SiFCC lattice distortion and the formation of Si orthorhomic alongside with it. This indicates phase transformations in the samples of semiconductor silicon during magnetic treatment at room temperature. KEYWORDS Semiconductor silicon, complex doping, interaction energy, phase transformations, dislocation density, twins, magnetic field treatment, microhardness, specific electrical resistivity, charge mino rity-carrier lifetime. Commonly, power engineering for energy production has always been posed as the principle industry of any developed country. To provide energy independence is one of the strategic tasks to address in modern Ukraine's economy development. The promising way how this task can be solved is in maximizing the strategic balance by enhancing the energy share from the own energy DOI: 10.15587/978-617-8360-19-1.CH1 Igor Krasnikov, Anatolii Babichenko, Juliya Babichenko, Oleksandr Dzevochko, Yana Kravchenko, Ihor Lysachenko © The Author(s) of individual chapters, 2025. This is an Open Access chapter distributed under the terms of the CC BY license Technological aspects of computer control of the secondary condensation complex of ammonia production under uncertainty 4 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 1 resources. The urgency of this problem in Ukraine determines the need for the development of the alternative energy forms based on renewable sources alongside with the energy saving. Back in 1990, the world's developed countries initiated transition stage to the new energy sources. The environmentally-friendly attitude is among the features of this stage, i.e. it strives to reduce environmental pollution and to minimize carbon dioxide and sulfur dioxide emissions. Expected that during the next two or three decades, the mankind is to introduce ecologically-friendly renewable energy sources into everyday life, primarily wind power and solar power. Ignoring these tendencies threats with ecological disasters of the future and is able make the entire life on earth endangered. Moreover, pursuing the target of achieving European Integration, Ukraine sets the strategic goal of rapid implementation for the energy produced from the renewable energy sources. Thus, solar power is the most promising direction of such kind in Ukraine, where there is a high potential due to the country's geographical position in the terrestrial latitudes with good solar radiation intensity. The latter implies that the photovoltaic equipment can be used throughout the year. Further, the high-performance operating time in the northern areas makes up 5 months (May to September), while in the southern areas it is 7 months (April to October). However, the solar power economic features require careful further study. According to experts, the operating cost of the electrical power generated by the solar modules will reduce by 5 times during the next 10 or 15 years. Taking into account the above stated necessity of solar engineering development, silicon, as a constituent of solar cells, draws the close attention of the scientists. In particular, thermal stability of silicon crystal properties is one of the basic parameters of semiconductor quality and at the same time it is the very factor that determines the resistance of microelectronic devices to degradation at elevated temperatures and expands the area of their operation. Furthermore, thermal stability of silicon crystals is essential for manufacturing microelectronic devices, since crystals are exposed to high temperatures in many technological processes that often irretrievably deteriorate properties of primary crystals. The topical character of the study is determined by the need to reveal the degradation regularities in silicon physical properties and the means of their further control, as well as by the necessity to develop semiconductor devices based on silicon with stable parameters. The manufacturing processes and operation of semiconductor devices are known to be followed by thermal and radiation effects that cause the changes in the physical properties of both in semiconductors and the devices based on them. However, there are rigorous specifications to the manufactured semiconductor devices concerning stability of their parameters under various radiation and thermal operating conditions. The potentially productive ways of control over silicon physical parameter degradation are in its thermal treatment, doping and processing within a magnetic field. Today there is a growing demand for monocrystalline silicon for photo-emissive converters from both foreign and domestic companies. The circle of scientific interests of the global research community continues to be focused on solar cell manufacturing techniques from cheap silicon that can be represented by polycrystalline silicon of low-purity ("dirty"), thin films of amorphous silicon of polycrystalline type and other semiconductors. 5 chapter 1. Technological aspects of computer control of the secondary condensation complex of ammonia production under uncertainty CHAPTER 1 Considering the full-scale opportunities for the silicon and the dedicated equipment, the need for the sufficiently high level of readiness should be provided, which enables the rapid and efficient growth of modern solar power in Ukraine. The first section of the current publication contains the literature review on the regularities in semiconductor silicon structure formation and properties, as well as the modern views and opinions on phase transformations and martensitic transformation mechanisms that occur in semiconductor silicon. The contemporary publications targeting the problem of the magnetic field effect on the semiconductor silicon structure and properties have been reviewed. This analysis enables outlining the character of the further studies and the stages of the topical scientific and technical task to be solved for the current research: for the present publication we set the task to develop the complex resource-saving technology and energy saving solution for production of semiconductor silicon with enhanced physical and mechanical properties by influencing its liquid and solid forms physically and chemically with the objective to expand the areas of its application. The second section provides the data on the material and the research techniques. The object of the research is monocrystalline semiconductor silicon samples (Cz-Si) grown by Czochralski method, both in undoped version and doped with single elements of B, Sn, Ge, Hf, Zr, and with the complexes of B-Sn and B-Mo, ranging from 2⋅10–4 to 8.7⋅10–2 at % in the initial state, after they have been exposed to the complete heating-cooling cycle, the thermal treatment regimes and the weak direct current magnetic field effect. In the third section the structure peculiarities formed under the magnetic field effect for both the undoped Cz-Si samples and the Cz-Si doped with Al, Mg, Cu, Fe, Zr, and Hf have been analysed, with the focus on the difference in the dopant effects on the silicon atom interaction energy within silicon crystal lattice. During the magnetic treatment at room temperature, the phase transformations have been detected in semiconductor silicon samples via X-ray diffraction technique. In the fourth section we report on the magnetic treatment effect on the microhardness values of doped Cz-Si structural units. The fifth section reveals physical parameters and mechanical properties of the doped and undoped silicon samples before and after magnetic field treatment with the induction of 66 mT. 1.1 Earlier research findings and relevant literature review 1.1.1 Crystallochemical peculiarities of semiconductor silicon Silicon is an element of IVB subgroup of the periodic system, the atomic number of 14, an electron configuration of 1S22S2P6ЗS2Р2. Silicon atoms possess four valence electrons and form a diamond-type or a zinc blende type of the crystal lattice with covalent bonds and coordination number of 4 at room temperature, when silicon behaves as a typical semiconductor. 6 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 1 Silicon has high specific melting point and its density increases when transformed from a solid state to a liquid one [1]. Under atmospheric pressure silicon is a covalent substance with strong semiconductor properties. Interatomic bonds are defined by means of tetrahedral symmetry and have sp3 hybrid composition. All 4 silicon atom bonds are equivalent and equally saturated. In [1–3], it is shown that silicon undergoes the semiconductor-metal transition during melting, while at high pressure (~12 hPa) [2] there has been detected the transition from purely covalent structure (K = 4) of a diamond to bcc tetragonal covalent metal structure within silicon (as the white tin type) and then (~16 hPa) the transition to the typical body-centered cubic metallic structure (K = 8). The publications [1–4] suggest that the transition to metallic state (when melting the elements belonging to IVВ group (germanium and silicon) as well as compounds of АIIIВV and АIIВIV types etc.) is related to the disruption in homopolar bond space system and to the separation of many free electrons; the latter form a new configuration with electron density of higher symmetry [3]. Silicon melting causes the sharp increase in its conductivity which value becomes equal to the liquid metal conductivity value. It should be noted, that conductivity alteration is connected to the rearrangement from the "diamond structure" of a solid state to denser packing peculiar to the "metallic state" that occurs when melting these substances of short range ordering; this process is confirmed by the density increase factor that to some extent reflects the structural changes. According to the X-ray investigation data, it has been proved that the structure change occurs in many semiconductors with diamond structure (including silicon) when in a liquid state. During melting silicon coordination number increases from 4 to 6. 1.1.2 Phase transformations in semiconductor silicon It is peculiar of silicon to have high specific fusion heat as well as density increase during transition from a solid state to a liquid state [5, 6]. Fusion entropy of silicon is considerably higher than that of pure metals that is why its value is greatly affected by the process related to the electron delocalization at the solid-liquid transition. The electron component is connected to the chemical bond type change (mainly from covalent bonds to metallic ones) during melting that is followed by the marked increase of free electron concentration [6]. For the substances that become highly metallized at melting, solid-liquid transition is followed by disruption in the sp3-hybrid homopolar bond space system, by detachment of four valence electrons and their transition to the free state and by major changes of the short range ordering and atom vibrational spectrum [7–9]. A distinguishing feature of the first-order phase transitions in silicon (by that we mean melting and crystallization) is the change of the free electron number and the important role of the electron component is in this transition. Apparently, at the temperature and the pressure change, allotropic transformation can be followed by the free electron number alteration. 7 chapter 1. Technological aspects of computer control of the secondary condensation complex of ammonia production under uncertainty CHAPTER 1 The data on phase transitions in the solid polymorphic type of silicon are given in the publications [6–8]. Polymorphic closely-packed metallized modifications of silicon are formed at high pressure [7]. At the pressure of 12 hPa and the temperature of 20°С, the phase transition SiI→SiII has been detected by means of resistometric investigation and X-ray analysis [8]. A notable dependence has been revealed for the SiI→SiII phase transition on the shift components of load, pressure and the holding-pressure time of the sample. Due to this, the transition continues at 2–3 hPa. SiII phase is reported as one having metallic conductivity. The inverse transition SiII→SiI has not been detected. After subjecting SiII samples to certain pressure, there have been revealed 2 modifications of Si (SiIII and SiIV) by X-ray analysis under atmospheric conditions. Heating SiIII within 200–600°С causes its lattice rearrangement and, consequently, there occurs SiIV modification with the hexagonal wurtzite-type structure. Under additional pressures, SiIV behaves as a metastable phase. Two assumptions have been suggested concerning SiIII: it either can be a stable phase under 12 hPa at 20°С with a body-centered cubic lattice, or it is a transition phase from SiII of tetragonal structure when pressure is removed. Under the pressure of 12 hPa, SiII phase transforms into superconductive state if T = 6.7 K [11]. In [9–11], the temperature dependence of some semiconductor silicon properties has been described, particularly, thermal expansion coefficient, hardness, lattice parameter, electrical properties at atmospheric pressure in the range from T = 20°С to T < Tmelting. During phase transitions, semiconductor silicon undergoes discontinuous change of thermal, volumetric, mechanical and electrical properties due to the transition from one crystalline state into another. Establishing the property-temperature and property-pressure dependences allows revealing phase transition. Normally, phase transition develops with a high rate, however, this behaviour is true only for certain regions. Being conditioned by the size and the number of a new phase regions that are formed per unit time, the volume rate of transformation is low in many cases, though the region formation rate is very high. The volume rate of the transformation is taken into account in [9] for the studies on temperature dependence in silicon properties when heated at the rate of ≤5°С/min. These studies on semiconductor silicon properties reveal the monotonic dependence. The abnormal character of the temperature dependence of the sample linear dimensions shows that there are different silicon phases at certain temperatures due to formation of which the registered changes occur. In [10], the following phase transitions in silicon at heating are described. The general conclusion based on the ultrapure silicon research data is that these phase transitions can be observed in the local crystal volumes during heating with the rate of less than 5°С/min: (I) within 250–350°С SiFCC→SiORTHORHOMBIC; (II) within 680–700°С SiORTHORHOMBIC→SiBCC; (III) within 1150–1200°С SiBCC→SiHCP; (IV) within 1420°С SiHCP→Р. 8 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 1 Low-temperature transformations (I and II) have low DН values and can be referred as phase transitions that cause lattice atom shears at small distances. In this case we observe shear transformations that are based on the ordered lattice rearrangement. The lattices of both modifications are combined or adjacent while the shear transition starts heterogeneously. The nuclei appear in the areas with the dedicated dislocation nodes (the order growth rate is 103 m/sec). Polymorphic transformation rate is especially high in defect-free crystals. Phase transition III is accompanied by high thermal effect, so hyperthermal transformation in silicon is a first-order phase transition and it occurs due to the total rearrangement of the lattice. The specific feature of a first-order phase transition is the presence of interfaces that is why the transitions of this type lead to the fundamental crystal structure rearrangement. The calorimetric analysis of the ultrapure semiconductor silicon [11] reveals that the phase transition is blurred and this phenomenon can be explained by as below: – formation of polymorphic modifications with closely adjacent lattices; – irregular distribution of impurity atoms within the crystals, namely О2, Н2, С; – irregular distribution of defects. Considering the above stated, it can be suggested that when heating semiconductor silicon, its crystal lattice is proved to become denser before Tmelting, conditioned by the degree of bond directions and followed by the transition to the metallic state. The transition of covalent crystals to the metallic state can be obtained regardless of the lattice disruption type and the techniques to influence the crystals. The transition mechanism of the covalent crystals to the metallic state at various ways of the lattice excitement is the same: there occurs electron subcrystalline structure alteration, particularly, the sp3-hybrid bond disruption is followed by the band gap narrowing and the corresponding increase in the number of charge carriers [11, 12]. The transition from the covalent bonding to the metallic one is carried out due to electron motion from the "coupled" state in the valance band to the "antibonding" conduction band, that leads to the decrease in the shear resistance of diamond lattice [12]. The experiment shows that at heating semiconductors, the transition from the semiconductor to the metal begins at the temperature considerably lower than Tsmelting. It is interesting to note, that this temperature is not the same for the crystals obtained by different techniques [13]. The transition occurs due to the sequential lattice rearrangement from less dense to denser by the shear or shear-diffusion mechanism and is followed by the change in the correlation between the covalent component and the metal component of the chemical bond. In other words, in silicon there occurs direct and reverse martensitic transformation on its exposure to the different factors. The most important feature of the diffusionless transformations is the concerted migration of large atomic groups during the new phase crystal growth. According to Kurdyumov, "Martensitic transformation is a regular lattice rearrangement in which the adjacent atoms do not interchange their places but only shear relative to each other at a distance which does not exceed the interatomic one" [14]. 9 chapter 1. Technological aspects of computer control of the secondary condensation complex of ammonia production under uncertainty CHAPTER 1 All the martensitic transformations without any exception have certain features conditioned by the following: 1) the cooperative character of atom migration during the crystal growth; 2) transformations in anisotropic elastic medium. The crystals of the martensitic phase appear and reach their finite sizes at small-time intervals. The increase in the amounts of new phases takes place mainly due to the formation of new crystals, however, in some alloys there can be observed discontinuous growth of previously formed plates. The martensite crystals usually have a shape of a double convex lens and are twinned formations with a twining plane that coincides with the lens symmetry plane. Similar to twinning, such martensite crystal shape is explained by the elastic strain effect that occurs in the surrounding matrix during the growth of the new phase crystals.Theoretically, the analogy between twinning and diffusionless transformations is so due, that many authors regard twinning as a special case of diffusionless transformation during which the substance structure remains unchanged [15, 16]. Twinning can occur both with the change of the shape and without it (for instance, quartz). By analogy, diffusionless phase transformations can be subdivided into two groups: 1) diffusionless phase transformations that change the shape; 2) diffusionless phase transformations that do not lead to the change of the shape. The transformation accompanied by the shape change is the one, during which there occurs primary macroscopic deformation; the transformation without such a change in the shape is the one, at which there is only "secondary" deformation. Thus, martensitic transformations are the diffusionless transformations accompanied by shape change. The diffusionless transformations with no shape change are more common for the crystals with complex structure, chiefly, for molecular crystals. These transformations, in case of preserving the atom migration cooperative character, can be deprived of many peculiar to martensitic transformations features related to the shape change. In combination with the elastic medium effect on the growing crystal, the macroscopic shear, that follows martensitic transformations, causes the "elastic" martensite crystal formation. This phenomenon is analogous to elastic twinning. The martensite crystal growth takes place due to regular atom migration to new dislocations, so that the adjacent atoms of the initial lattice remain adjacent in the new lattice as well. On the separation interface of the two phases, there is one lattice which continuously transforms into the other, i.e. there is a coherent bonding between the lattices of the initial phase and the new one. With the crystal size increase, the elastic strains on the interface surface of the two phases also increase; eventually, these strains lead to plastic deformation and, consequently, to coherence violation between the two lattices and the crystal growth character alteration. When covalent crystals are heated to the critical values at certain temperature due to the increase in the antiphase oscillation amplitude, there occurs covalent bond breakdown and the localized pairs of electrons in them become collective, that, in its turn, predetermines transition to the metallic state. 16 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 1 while the strong magnetic fields can activate some other magnetic field mechanisms of action in dielectric material that have not been previously discussed.  Fig. 1.3 The dependence between the relative value of property changes in solid bodies (DI/I): a – the magnetic energy per unit volume (χmH2/2); b – time t1 for some substances. The approximation described in this publication is marked with a continuous line Source: [27] From the above mentioned it can be obviously deduced that the magnetic effect value (DI/I) is assumed to be related to the time (t1) as it reflects time when waiting for the phenomenon to occur in a magnetic field and characterizes the kinetics of the change accumulation (that are induced by a magnetic field) in the crystal. Fig. 1.3, b shows DI/I(t1) dependence that is also subdivided into a and b groups. Group a mostly includes semiconductors and metals while group b consists of dielectric materials. This fact emphases that there is a considerable difference in the mechanisms of the magnetic field effect on the physical properties of semiconductors and dielectric materials. Fig. 1.3, b shows the approximation of dependences DI/I(t1) (marked with continuous lines) of a and b types per straight lines: y = A+B⋅x, y = DI/I, x = t1 with the following parameters: – for a line: A = 5.3 ± 3.7; B = 0.4 ± 0.2; – for b line: A = 6.4 ± 3.5; B = 15.9 ± 1.6. Group b embraces those substances, wherein the magnetic effect is in a linear relation with the time (t1). Group a contains the substances with magnetic effect being independent of the time (t1) that is expressed by a small value of B coefficient. The magnetic effect value (DI/I) with short time (t1) is almost the same (identical A coefficients) and close to 5% for both a and b types of dependences. The growing number in the publications to address the problem of a magnetic field effect on the properties of solids within the last few years allows revealing the number of general regularities for the solids: 1. Magnetic field induces the nonreversible transition to a new state after which the secondary processes occur causing sometimes the virtual crystal recovery and are perceived as "relaxation" 17 chapter 1. Technological aspects of computer control of the secondary condensation complex of ammonia production under uncertainty CHAPTER 1 after being excited by a magnetic field. In fact, they are the consequences of the primary processes and are insensitive to further magnetic field effects and their values. 2. On average, for a wide range of substances (dielectric materials, metals and semiconductors), the time invariable to describe the time period of the transition into a new state decreases in its value with the magnetic field (H) increase according to the law of t1 = t0/Н4. 3. The relative change in the physical properties of solids under DI/I magnetic field effect in weak fields (~0.1–1 T) is the same for a wide range of substances and makes ~5%. The influence of strong magnetic fields (3–30 T) is able to classify solids into two large groups in terms of their behaviour. Thus, the first group includes metals and semiconductors and there is DI/I dependence revealed on the magnetic field energy in such substance, while the second group mainly consists of dielectric materials in which DI/I shows strong dependence on the energy of a magnetic field per unit volume of a substance. 1.1.5 The nature of Nernst-Ettingshausen effect Nernst-Ettingshausen effect or transverse effect is a thermomagnetic effect observed when a semiconductor with a temperature gradient is exposed to a magnetic field. This effect was discovered by Nernst and Ettingshausen in 1886, and in 1948 it was theoretically grounded by Sondheimer [28]. The nature of this effect is in the occurrence of the electric field (E) in a semiconductor and its direction is perpendicular to the temperature gradient vector (∇) and the magnetic induction vector (B), i.e. it is in the direction of the vector ([∇T, B]). If the temperature gradient and the magnetic induction are directed along X axis, then the electric field is parallel to Y axis. Therefore, there occurs the electric potential difference (u) between the points of a and b. Both Nernst-Ettingshausen effect and Hall effect occur due to the flow divergence of charged particles caused by Lorentz force. However, there is the difference between them: Hall effect is responsible for the directed flow of particles resulted from the drift in the electric field, while in the case of Nernst-Ettingshausen effect, the same phenomenon is caused by diffusion. The considerable difference between them is that unlike Hall constant, the sign of q⊥ is independent of the charge carrier sign. Actually, during the drift in the electric field, the charge permutation causes the drift direction alteration, that changes the sign of Hall field. In this case, the diffusion flow is directed from the heated end of the sample towards the cold one irrespectively to the particle charge sign. Therefore, the direction of the Lorentz force for positive and negative particles is mutually antithetic, but the direction of the electric charge flows in both cases is identical. Longitudinal Nernst-Ettingshausen Effect. The longitudinal Nernst-Ettingshausen effect is in the change of thermal electromotive force in metals and semiconductors under the magnetic field influence. 18 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 1 When the magnetic field is absent, the thermal electromotive force in electron semiconductor is defined by the difference between fast electron velocity components (drifting from the hot side) and slow electrons (drifting from the cold side) along the temperature gradient. At the presence of the magnetic field, there is the change observed in the longitudinal components (along the temperature gradient) and transverse components (transverse to the temperature gradient) of the electron velocity, this change is dependent on the rotation angle of electron velocity in the magnetic field; the angle is defined by the time of free run of the electrons τ in metals or semiconductors. If the time of the free run for slow electrons or electron holes (in a semiconductor) is greater than that for the fast electrons, then u1Х(Н)/u1Х(0) > u2Х(Н)/u2Х(0), where u1Х(Н), u2Х(Н) – longitudinal components of velocities for slow electrons and fast electrons under magnetic field; u1Х(0), u2Х(0) – longitudinal components of velocities for slow and fast electrons when the magnetic field is absent. The value of thermal electromotive force in a magnetic field (that is proportional to the difference of u2Х(Н) – u1Х(Н)) is higher than that when the magnetic field is absent at the difference of u2Х(0) – u1Х(0); vice versa, if the time of free run for slow electrons is lower than that for the fast electrons, then the magnetic field presence decreases the thermal electromotive force. In electron semiconductors, the thermal electromotive force increases within the magnetic field provided that there is the decrease in the time of free run τ under the increase in the electron energy (scattering at the acoustic phonons). Within the same substances of electron semiconductors, the thermal electromotive force decreases under the magnetic field, if the time of free run τ increases with the increase in the electron energy (during the ionized impurity scattering) [29]. 1.1.6 Magnetoplastic effect in diamagnetic crystals In [30], was described the found and investigated decay of the particles from CdCl2 impurity phase in monocrystalline matrix of NaCl (alkali-halide crystal) caused by magnetic field induction effect. Further, the structural changes started to appear in a few hours after the magnetic field induction treatment (the latency time) and lasted for several weeks. It has been revealed that the duration of the latency time and further structural changes are closely related to the "background" of the primary crystals. However, no physical model to explain these effects has been discussed in [30] and it is only stated that the magnetic field induction can affect the paramagnetic impurities which stabilise the quasi-equilibrium structure in primary crystals but cannot be controlled. 19 chapter 1. Technological aspects of computer control of the secondary condensation complex of ammonia production under uncertainty CHAPTER 1 The direct magnetic field with the induction (0.5 T) causes the dislocation motion in NaCl and LiF crystals if no mechanical loads, thus changing the plastic properties of the sample. The established regularities of the magnetoplastic effect can be summarised as follows: – the direction of the dislocation motion does not change during the magnetic field sign reversal (paired effect); – the velocity of the dislocation motion is proportional to the square of the field induction and inversely proportional to the square root of paramagnetic center concentration within a crystal; – dislocation pathlength tends to a constant value (saturation) depending upon the induction value of the magnetic field and the holding time for the crystals to spend within the magnetic field. The paired nature of the magnetoplastic effect and its quadratic dependence on the induction value of a magnetic field imply the magnetostriction character of the phenomenon. To verify this assumption, the dedicated calibration measurement has been carried out to define the creep of NaCl samples at room temperature. At the load of ~30 kPa, the average dislocation pathlength during 5 minutes is similar to that of the magnetic field with 0.4 T induction holding (when without the load) during the same time. The revealed correlation should correspond to the magnetostriction constant of m ~ σ/G⋅B2 ~ 4⋅10–5 T–2, where G is a shear modulus. However, the obtained value turns out to be several orders greater than the value of m ≤ 1.5⋅10–9 T–2 obtained for these crystals independently. The observed magnetoplastic effect can alternatively be explained as followings: the dislocation motion in the magnetic field occurs under the far-reaching internal stress field effects, while the magnetic field effect is narrowed to disconnecting of the dislocations from the local barriers (stoppers) through the spin-dependent electronic transitions in the magnetic field within the dislocation-impurity system. The magnetoplastic effect, that has been evidenced by the chemical technique of double etching, necessitates the search for the similar effects in a wider range of experimental conditions, for instance: in a mode of active macrodeformation and creep, during microhardness measurement and electric dipole moment generated by the charged dislocations. These vast experiments have been carried out on the crystals of ZnS, Al, Bi, Si and InSb and C60 fullerite monocrystals and allow the following: – to determine activation energy, reinforcement factor, yield point, creep rate and other magnetoplastic effect parameters as well as their dependence upon the effect produced by magnetic fields on the samples; – to find out that the magnetic field affects these point defects of low-sensitivity which have less effective radii of interaction with the dislocations as compared to the point defects that are insensitive to the magnetic field effect; – to reveal the magnetoplastic effect in a wide range of relative deformations ranging from ~10–7 to ~1 and to study this effect at different stages of macroplastic deformation; – to establish the role of internal stresses within dislocation shears in magnetic fields when no external stresses. 20 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 1 The magnetic treatment of the dislocation-free crystals and the further detection of the motion in as-introduced dislocations in them reveal that within the subsystem of point defects there is the following phenomenon: the magnetically stimulated residual changes reduce the free pathlength of the dislocation under the magnetic field and increase them under conditions of mechanical load and the magnetic field absence. This difference as it has been noted earlier is conditioned in the crystals by the presence of the stoppers insensitive to the magnetic field along with magnetosensitive obstacles. The first physical models of the magnetoplastic effect were based on the idea of the spin nature of the interaction between the dislocations and the paramagnetic point defects. Further, with the reference to this idea it was theoretically grounded, that the coeffect of the direct magnetic field and the pulsed magnetic field can cause resonance weakening of the crystals if the impulse frequency (ν) satisfies the condition of paramagnetic resonance, expressed by as given: hν = gµBB0 (h – Planck constant, g – factor of spectroscopic splitting, µB – Bohr magneton, B0 – direct magnetic field induction). Fig. 1.4 presents the dependence between the average edge dislocation pathlength and the magnetic field induction for various exposure modes. This dependence illustrates that at simultaneous exposure of NaCl:Ca (0.001%) crystals to the magnetic fields, acting perpendicular each other, namely the direct current magnetic field and the ultrahigh-frequency magnetic field, there can be observed the maximum increase in the dislocation pathlength (L) at several discrete values of (В0). Further, the "resonance" values of the induction correspond to В0 = hν/gµ, and the applied frequency of ultrahigh-frequency field is ν = 9.5 GHz. Under these conditions, the resonance transitions occur between the splits from spin sublevels of electrons within the direct magnetic field and the effective factors of spectroscopic splitting g1 ≈ 2, g2 ≈ 4 and g3 ≈ 6, respectively. For crystals with Eu impurities the dependence is even more complex (Fig. 1.5). Being obtained with the standard electron paramagnetic resonance spectrometer, the electromagnetic wave absorbance spectrum for NaCl crystals heavily doped with Eu shows the extrema. By analysing the experimental data on the obtained magnetoplastic effects in diamagnetic crystals, there have been suggested the scheme of the probable mechanism how magnetic field effects on the evolution of metastable defect complexes. It is shown in Fig. 1.5. The local minimum characterizes the profile of the elastic interaction between the constituents of the complex found in the metastable state. The solid line and the dotted lines that unite the complex constituents designate the covalent bonding in the equilibrium state and in the excited state: kT – thermally stimulated process, j – exchange integral, DЕ – exchange energy differences in Sand Т-states of the complex, νi – frequency of transitions between absorption states that practically coincide with those in the weakening spectra, this indicates the fact that impurity ions are within the magnetosensitive complexes of defects. According to the scheme (Fig. 1.5), the thermal fluctuations with the frequency (ν1) excite the complex by covalent bonding stretching (or by changing configuration coordinates (r), such as bond angles) from the primary singlet S-state to the excited S-state. When the magnetic field does 21 chapter 1. Technological aspects of computer control of the secondary condensation complex of ammonia production under uncertainty CHAPTER 1 not act, the complex, being exposed to the elastic forces from the crystal lattice, reverts to the original S-state due to prohibition for the complete spin that means that the complex is in dynamic equilibrium between Sand S-states.  Fig. 1.4 Dependence between the average edge dislocation pathlength (L) in NaCl:Ca crystals upon the direct magnetic field induction (В0): exposure time of 15 min Source: [30] When there is a magnetic field, the prohibition is partially lifted, and the complex with ν2 = µBBDg/h frequency that has changed its multiplicity (Dg-mechanism of mixing states is the most probable under such conditions) evolves into a new electron T-state. Further, under influence 22 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 1 of the elastic forces from the crystal lattice there occurs reverse motion of nuclei. At that, the equilibrium RT-state between them appears to be higher than that in the singlet RS-state, since the negative J value of exchange integrals causes the mutual repulsion of the complex constituents. Thus, with ν3 frequency there occurs a relatively continuous triplet of T-state, in which the total energy of the complex constituent bonds is DЕ = 0.1–1 eV, less than that in the S-state. The "dispersed" by this way complexes are less stable as compared to the initial ones, and the random motion of nuclei can cause either their decay with ν4 frequency that is followed by the system escape from the local energy minimum and its further relaxation, or the restoration to the initial S-state with ν5 frequency. Normally, the decay of the point defect complexes leads to the formation of weaker stoppers for the dislocations; that agrees with the experimental data on the weakening effect for the ionic crystals after they have been subjected to the magnetic fields.  Fig. 1.5 Schematic illustration of the process sequence in the complexes of point defects within the magnetic field: on the energy scale of Е complex Source: [30] 23 chapter 1. Technological aspects of computer control of the secondary condensation complex of ammonia production under uncertainty CHAPTER 1 In other words it can be expressed as here: in the subsystem of the paramagnetic structural defects of the ionic crystals, spin-dependent magnetosensitive reactions are thought to considerably affect their plastic properties, while the kinetics of these reactions, according to the numerous tests, can be regulated by the weak constant fields and (what is even more efficient) by the pulsed magnetic fields. 1.2 Materials and methods of the study 1.2.1 Study materials In the current paper, there have been studied the samples of monocrystalline semiconductor silicon grown by Czochralski method (Cz-Si), both undoped version and doped with B, Sn, Ge, Hf, Zr, and the complexes of B-Sn and B-Mo ranging from 2⋅10–4 to 8.7⋅10–2 at % in initial state, after their exposure to the full heating-cooling cycle, various thermal treatment conditions and the weak direct magnetic field effect (refer to Table 1.1).  Table 1.1 Properties of the studied silicon crystals No. Sample characteristics (technique of preparing) Oxygen content, atm/cm3 Carbon content, atm/cm3 Electric resistance at room temperature, ohm Temperature ranges of variation lg(σ), lg(h), lg(µ) = f(1/T) from straight-line correlation 1 2 3 4 Tstart Tend Tend Tend Tstart Tend Tstart Tend 1 Float zone melting 4 1014 3 1015 1200 250 400 520 770 960 1005 1040 1150 2 Czochralski method, dislocation growth 1017 1016 25–50 260 380 770 860 960 1130 1170 1215 3 Czochralski method, dislocation-free growth 1017 1016 80–100 260 460 725 770 920 970 1090 1185 4 Cast polycrystalline 2⋅1017 1.5 1018 0.3–3 220 320 432 555 730 918 1065 1180 5 "Raw" silicon trichlorosilane – – 1–20 210 350 650 750 920 960 1040 1190 6 "Raw" silicon monosilane – – 1–20 150 452 635 772 924 954 – – Source: [31] 1.2.2 Methods of the study The chemical composition of the samples under analysis was determined by the spectroscopy performed at ARL-2400 testing facility. 24 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 1 The microstructure of the alloys was studied on the "Neophot-21" optical microscope. For revealing the general structure of semiconductor doped silicon, the samples were exposed to etching in HF:H2O:Cr2O3 solution at the ratio of 3:3:1 with subsequent wash in the flowing water. The temperature dependence of the thermal expansion coefficient of a semiconductor silicon was studied using the AD-80 dilatometer in the argon flow medium at the heating and cooling rate of 5°С/min. The thermal expansion coefficient rate accuracy was 0.1%. The change in the solubility of doping elements (dopants) and their distribution between the structural constituents was studied by means of X-ray diffraction technique while the microhardness change was studied by means of the local X-ray spectrum analysis with MS – 46 microprobes and Camebax. XRD patterns of the alloys were recorded with DRON-3M diffractometer in kα copper radiation. Aluminium of А999 grade and chemically pure silicon were used as reference standards. In order to determine the lattice parameters, the profiles of the diffraction extremum graphs (422) Si and (511) Si were recorded by means of the gravity center coordinate determination. The microhardness of the modified silicon structural units was measured at PMT-3 testing facility under the load of 20 g. Each sample underwent from 36 to 76 measurements. In order to reveal the hidden regularities of silicon-based solid solution formation, the interval data imitating the distribution function [32] were used. For that purpose, the variation range of the characteristic was divided into n equal intervals and the number of cases in each interval was counted. The applied technique allowed taking into account and demonstrating silicon microhardness changes during doping. XRD patterns of the alloys were recorded on DRON-3M diffractometer in kα copper radiation. Chemically pure silicon was used as a reference substance. The specific electric resistivity of doped Cz-Si was measured with 4-probe technique (the error was within of 2.5%). The minority-carrier lifetime of charges was measured on the original testing facility for radiating heat kinetics measurement, the device built in V. Ye. Lashkaryov Institute of Semiconductor Physics of the National Academy of Sciences of Ukraine (Kyiv). The instrument accuracy was ± 0.1%. The thermal treatment of the doped Cz-Si was performed in the laboratory in the chamber muffle kiln furnace of SNOL 2.5, 2.5/1.5. The desired temperature was maintained as accurate as ± 0.5°С by means of VRT-3 device. The temperature measurements were taken via chromealuminium thermocouples on R-4833 general-purpose instrument switched on according to the lattice network (the instrument accuracy of 0.05). The magnetic treatment of the samples was carried out in the direct current magnetic field with induction of 0.066 T. The time periods of exposing for the samples were 10 and 30 days. The measurements of the current minority-carrier lifetime after magnetic treatment were measured by the decay of the photoinduced current that occurred in the samples exposed to the GaAs light-emitting diode by means of SEMILABWT1000B device with the accuracy of ± 0.1%. 25 chapter 1. Technological aspects of computer control of the secondary condensation complex of ammonia production under uncertainty CHAPTER 1 1.3 Microstructures of the samples before and after the magnetic field treatment Fig. 1.6 shows the microstructures of Cz-Si samples in the initial state and after 240 and 720 hours of exposure in the direct magnetic field with the induction of 66 mT. The initial silicon microstructure is quite homogeneous with a low dislocation density (Fig. 1.6, a).  Fig. 1.6 Microstructures of Cz-Si samples: a – initial state, ×500; b, c, d – after 240 hours of exposing to direct-current magnetic field, ×400; e, f – after 720 hours of exposing to direct-current magnetic field, ×400 Source: [33–36] 32 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 1 orientations, in their turn, brings the changes in the crystal lattice type that means the phase transformation.  Fig. 1.12 Microstructures of Cz-Si samples doped with Fe: a – initial state, ×500; b, c – after 240 hours of exposing to direct-current magnetic field, ×400; d, e, f – after 720 hours of exposing to direct-current magnetic field, ×400 Source: [33–36] The large number of twins formed within the structure might be assigned to the formation of silicon orthorhombic phase and silicon BCCIII phase with the shear pattern within the certain masses of the sample [1–4, 6]. In undoped silicon, the shear transformation of SiFCC↔SiORTHORHOMBIC 33 chapter 1. Technological aspects of computer control of the secondary condensation complex of ammonia production under uncertainty CHAPTER 1 occurs at the temperatures higher than 350°С [39–43], in cases of the treatment in the magnetic field at the room temperature, this phenomenon is provoked only by the magnetic field influence. After 720 hours of exposing, there are no significant changes found in the sample structure. At this the measurements have shown the increase in the parameters of microhardness and specific electric resistance vs the samples which have been treated during 240 hours. This indicates the further proceeding of the phase transformation and the structure stabilization under the magnetic field effect. Note that all the above-mentioned doping elements increase the critical temperatures for SiFCC↔SiORTHORHOMBIC and SiORTHORHOMBIC↔SiBCCIII (refer to Table 1.2). Moreover, the doping elements increase the thermodynamic stability of the closed packed phases of silicon to the magnetic field action (the magnetic field as well as the higher temperature add to the energy to the system). Furthermore, it might be assumed that the doping elements stabilise the high temperature phase of SiBCCIII, thus eliminating low temperature shear-diffusion phase transformations as well as the formation of twins within the structure.  Table 1.2 Temperatures of phase transformation for doped silicon and the dedicated thermal expansion coefficient values Cz-Si/doping elements Temperature/coefficient of thermal expansion°С/α⋅10–6⋅°С–1 I SiFCC↔SiORTHORHOMBIC II SiORTHORHOMBIC↔SiBCC III III SiBCCIII↔Sihcp Cz-Si 350/4.3 700/4.4 900/5.3 Cz-Si+Al 450/5.0 750/4.5 900/6.0 Cz-Si+Zr 500/4.5 – 850/4.7 Cz-Si+Hf 380/4.5 – 850/4.7 Source: [33–36] Considering the influence of both the magnetic field and the doping elements on the energy of silicon interatomic bonds, it is difficult to make any assumptions since the most similar changes in the structures have been observed in the samples of Cz-Si(Al) and Cz-Si(Hf) after 240 hours and 720 hours of exposing to the magnetic field (refer to Fig. 1.7, 1.10 respectively), despite the fact that aluminium drastically decreases the energy of silicon atom interaction while hafnium increases it greatly. Further, the similar changes have been detected within the structures of Cz-Si(Cu) and Cz-Si(Fe) (Fig. 1.8, 1.9). At this, copper reduces the interaction energy of silicon atoms while iron does not bear influences on it. In the samples of doped silicon, which has undergone magnetic field exposing during 240 hours, the increase in the defects of the inner structure can be explained via the changes in the wave functions of the electrons. Quite local is the change in the wave functions of electrons and the crystal lattice rearrangement is to provoke the breakage in covalent binding of those adjacent atoms, which wave functions will not have changed enough to meet the orientation changes of 34 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 1 covalent binding (the density of the electron states in the space-time). This local breakage of the atom binding is to cause the appearance of complete dislocations or partial ones together with the defects of atom packing. The gradual decrease in both the density of the defects and the microhardness values of the structures in the samples of Si-Al, Si-Cu and Si-Zr after 720 hours spent in the magnetic field can be regarded as relevant to the structure stabilization during the time of quite long holding within the magnetic field as well as related to the decrease in the thermal capacity (enthalpy) of the system by means of annihilation of the certain portion of the structure defects. The same changes are observed in the samples during their annealing in the furnace [2]. Due to the commonly known property of aluminium to strongly decrease the energy of atom interaction in silicon, the easier shear-diffusion phase transformations within silicon occurs while hafnium influence is on the contrarily and drastically increases this energy that means slowing down the phase transformations and stabilizing the silicon structure of SiFCC [31]. In order to identify the phases in the samples, which have been under the magnetic field treatment, the method of X-ray analysis have been applied. Fig. 1.13 shows the diffractogram of Cz-Si sample in the initial state.  Fig. 1.13 Diffractogram of Cz-Si sample (initial state) Source: [44] 100 80 60 40 20 0 20 30 40 50 60 70 80 90 100 I, imp/s Cz-Si (initial state). Co-Ka emission Si (111) Si (220) Si (311) Si (511) Si (400) In the initial state, Cz-Si in the diffractograms shows the reflections of FCC lattice, and line (400) possesses the maximal intensity at the scattering angles of less than 65 degrees (Fig. 1.13). After treating the silicon samples with direct-current magnetic field of 0.4 T inductions, there have appeared the reflections at the scattering angles of 30–40 degrees (Fig. 1.14), which are interpreted as orthorhombic phase of silicon [45]. 35 chapter 1. Technological aspects of computer control of the secondary condensation complex of ammonia production under uncertainty CHAPTER 1  Fig. 1.14 Diffractogram of Cz-Si sample (B = 0.4 T) Source: [44] 100 80 60 40 20 0 20 30 40 50 60 70 80 90 100 I, imp/s Cz-Si (0.4 T). Co-Ka emission Si (111) Si orthorhombic Si (220) Si (311) Si (511) Si (400) The reflection intensityies for silicon with cubic close-packed lattice at angle of 65–70 degrees decrease after the magnetic field influence. It can be explained by phase transformation initiated in silicon, namely SiFCC↔SiORTHORHOMBIC [34] under the action of the direct current magnetic field with 0.4 T of induction. Fig. 1.15 depicts that after treating the samples with the aggressive direct current magnetic field (В = 1.2 T), there is the reduction in intensities of reflections in all the silicon phases and appears a considerable number of reflections from silicon oxide. This verifies the assumption of silicon surface activation with the direct-current magnetic field and enhancing its absorbing properties [46]. Furthermore, with the behaviour of this kind we confirm the assumption that the silicon phase structure stabilises under the action of direct magnetic field [33]. However, more detailed investigation on the line profile (511) evidences that additional phases are formed within the crystal array, and they possess the different type of the lattice. In Fig. 1.16, the curves are presented to show the differential extrema (511) for the samples in the initial state and after treating with the magnetic field: В = 0.4 T (b), 1.2 T (c). They have been obtained at the scattering angles of 90–92 degrees, which is the feature of silicon phase of cubic close-packed lattice [46]. The splits of the diffraction lines detect the presence of the distortions in the crystal lattices of Cz-Si samples. At this the split of the extremum (511) is to be assigned to overlapping of certain interferences of orthorhombic phase of silicon [41, 44, 45]. Further, the line splitting (511) increases with the increase in the induction of external magnetic field. The splits of the differential extrema at the scattering angles of 90–92 degrees at higher values of external magnetic field induction evidence the presence of two phases in the silicon and 36 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 1 are relevant to the formation of SiORTHORHOMBIC phase within this material array. The same is observed on the differential extremum split (511) at the scattering angles of 90–92 degrees after the silicon semiconductor heat treating at the temperature range of 280–450°С, and it is assigned to the crystal lattice distortion of SiFCC and formation of the certain quantity of SiORTHORHOMBIC [47, 48]. Eventually, the heat treatment of the silicon semiconductor gives greater splitting of the interference extremum (511) at increasing the annealing temperature from the range of 280–320°С up to the range of 400–450°С [48]. In the currently reported research, the significant splitting is observed at the increase of the external magnetic field induction from 0.4 T to 1.2 T. This evidences that the magnetic field and the heat treatment initiate the phase transformations of silicon.  Fig. 1.15 Diffractogram of Cz-Si sample (В = 1.2 T) Source: [44] 1000 900 800 700 600 500 400 400 300 200 100 0 20 30 40 50 60 70 80 90 100 I, imp/s Cz-Si (1.2 T). Co-Ka emission Si (111) Si orthorhombic SiO 2 (monoclinic) SiO 2 (monoclinic) Si (220) Si (311) Si (511) Si (400)  Fig. 1.16 Line profile (511) before the magnetic field action and after it: а – initial state; b – 0.4 T; c – 1.2 T Source: [44] 140 120 100 80 60 40 2020 0 90 91 a b c 2θ I, imp/s 18 16 14 12 10 8 6 6 4 2 0 90 91 92 2θ I, imp/s 30 25 20 15 10 5 0 0 90 91 92 I, imp/s Si orthorhombic Si FCC Si FCC Si orthorhombic Si FCC 140 120 100 80 60 40 2020 0 90 91 a b c 2θ I, imp/s 18 16 14 12 10 8 6 6 4 2 0 90 91 92 2θ I, imp/s 30 25 20 15 10 5 0 0 90 91 92 I, imp/s Si orthorhombic Si FCC Si FCC Si orthorhombic Si FCC 140 120 100 80 60 40 2020 0 90 91 a b c 2θ I, imp/s 18 16 14 12 10 8 6 6 4 2 0 90 91 92 2θ I, imp/s 30 25 20 15 10 5 0 0 90 91 92 I, imp/s Si orthorhombic Si FCC Si FCC Si orthorhombic Si FCC 37 chapter 1. Technological aspects of computer control of the secondary condensation complex of ammonia production under uncertainty CHAPTER 1 1.4 The sample microhardness values before and after treating with the magnetic field Magnetic field acting on Si sample has certain influence on the sample microhardness values. For the sake of the reader's swift reference we consider it is reasonable to summarise the revealed data on the microhardness change in similar patterns of representation as below. In Fig. 1.17, the graphs present the microhardness values of the aluminium-doped silicon samples after 240 hours (Fig. 1.17, a) and 720 hours (Fig. 1.17, b) of exposing to direct-current magnetic field with the induction of 66 mT. The analysis performed for the graphs has revealed that the average microhardness of the sample matrices after 240 hours of exposition is 11000 MPa (the values vary within the range of 9000–14000 MPa), the dislocations areas demonstrate 12500 MPa (the variation range makes 11500–12500 MPa), the swirl-defect allow 10000 MPa of the value (within the range of 9000–16000 MPa). The average microhardness per the structural units of the samples after 720 hours spent within the magnetic field becomes lower by 2500 and 950 MPa; for the matrix such change is within the range of 8500–10500 MPa while that of the dislocation areas is within the range of 9500–14000 MPa (swirl-defects have not been detected). These bring the conclusion that the ranges of the structural units' microhardness values undergo the considerable changes of decrease.  Fig. 1.17 Microhardness graphs for Сz-Si(Al) samples: a – after 240 hours of exposing to direct-current magnetic field; b – after 720 hours of exposing to direct-current magnetic field a b 7000 7500 8000 8500 9000 9500 10000 10500 11000 11500 12000 12500 13000 13500 14000 14500 15000 15500 16000 16500 1 2 3 4 5 6 7 8 9 10 Microhardness, MPa Number of measurements Matrix Dislocations Swirl-defects 7500 8000 8500 9000 9500 10000 10500 11000 11500 12000 12500 13000 13500 14000 14500 12345678910 Microhardness, MPa Number of measurements Matrix Dislocations Fig. 1.18 shows the average microhardness values per the structural units for Сz-Si(Al) samples both in the initial state and after 240and 720-hour exposition to direct-current magnetic field. 38 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 1 As it can be deduced from the given bar graph, the sample microhardness values notably increase after 240 hours of exposing within the magnetic field vs the initial state of the samples. The further treating of the samples (720 hours) causes the gradual decrease in the microhardness values that is connected with the decrease in the defects of the silicon samples.  Fig. 1.18 Microhardness per the structural units for Сz-Si(Al) samples (in the initial state, after 240and 720-hour exposition to direct-current magnetic field) 64005500 11220 12670 10020 8780 11760 0 2000 4000 6000 8000 10000 12000 14000 Matrix Dislocations Swirl-defects Microhardness, MPa In Fig. 1.19, we demonstrate the microhardness graphs for Сz-Si(Hf) samples after they spent 240 and 720 hours within the magnetic field for the treatment. The average microhardness values of the structural units, which Сz-Si(Hf) samples possess after 240 hours and 720 hours of the mentioned holding, are as follows: 9000 MPa (variation range is 8500–10500 MPa) and 10400 MPa (with the variations within the range of 89500–12500 MPa) for the matrices, respectively; 12400 MPa (12500–14500 MPa) and 12700 MPa (12500–16500 MPa) for the dislocation areas. Therefore, it follows that the increase in the holding time within the magnetic field results in higher range of the microhardness value variations that is probably connected with the increase in the defects. The microhardness parameter for swirl-defects has been revealed as much as 11000 MPa in the samples after 240-hour exposing while the etched samples of 720-hour exposing have not exhibited swirl-defects. The microhardness average values per the structural units of Сz-Si(Hf) samples before and after the magnetic treatment are given in Fig. 1.20. These bar graphs show that the microhardness values gradually increase (but with slowing intensity) during further exposing to direct-current magnetic field. In Fig. 1.21, we show the microhardness graphs for Сz-Si(Cu) after the action of the direct-current magnetic field. After 240 hours of magnetic field influence, the microhardness values for the matrix vary from 7100 MPa to 9500 MPa while those for the dislocation areas are within the range of 7700–11500 MPa. After 720 hours of holding, the microhardness values show 39 chapter 1. Technological aspects of computer control of the secondary condensation complex of ammonia production under uncertainty CHAPTER 1 the variations from 5600 MPa to 9500 MPa for the matrix and from 6100 to 12700 MPa for the dislocation areas.  Fig. 1.19 Microhardness graphs for Сz-Si(Hf) samples: a – after 240 hours of exposing to direct-current magnetic field; b – after 720 hours of exposing to direct-current magnetic field ab Matrix Dislocations Swirl-defectsMatrix Dislocations 7500 8000 8500 9000 9500 10000 10500 11000 11500 12000 12500 13000 13500 14000 14500 12345678910 Microhardness, MPa Number of measurements 7500 8000 8500 9000 9500 10000 10500 11000 11500 12000 12500 13000 13500 14000 14500 15000 15500 16000 16500 12345678 91 0 Microhardness, MPa Number of measurements  Fig. 1.20 Microhardness values per the structural units of Сz-Si(Hf) samples (in the initial state, after 240 and 720 hours of exposing to direct-current magnetic field) 77507400 9030 12460 11030 10420 12710 0 2000 4000 6000 8000 10000 12000 14000 Matrix Dislocations Swirl-defects Microhardness, MPa 40 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 1  Fig. 1.21 Microhardness graphs for Сz-Si(Cu) samples: a – after 240 hours of exposing to direct-current magnetic field; b, c – after 720 hours of exposing to direct-current magnetic field 6500 7000 7500 8000 8500 9000 9500 10000 10500 11000 11500 12000 12345678910 Microhardness, MPa Number of measurements Matrix Dislocations 5500 6000 6500 7000 7500 8000 8500 9000 9500 10000 10500 11000 11500 12000 12345678910 Microhardness, MPa Number of measurements Matrix Dislocations 5000 5500 6000 6500 7000 7500 8000 8500 9000 9500 10000 10500 11000 11500 12000 12500 13000 1 2 3 4 5 6 7 8 9 10 Microhardness, MPa Number of measurements Matrix Dislocations a b c The average microhardness values per the structural units of Сz-Si(Cu) samples before and after the magnetic field treatment are shown in Fig. 1.22. Comparing with the initial state, the microhardness parameter increases by approximately 1400 MPa in the matrix and by approximately 3500 MPa for dislocations after 240 hours of the treatment. After 720 hours spent within the magnetic field, the microhardness values increase by 100 MPa more for the matrix, but the hardness of the dislocation zone decreases by 700 MPa. In Fig. 1.23, the microhardness graphs of Сz-Si(Mg) samples are presented after their exposing for 240 and 720 hours within the magnetic field. The analysis of the graphs detects that after 240-hour treatment by the magnetic field, the microhardness values of the sample matrices vary from 7700 MPa up to 10300 MPa while those of the dislocation areas are within 41 chapter 1. Technological aspects of computer control of the secondary condensation complex of ammonia production under uncertainty CHAPTER 1 10300–12700 MPa. After 720 hours of the magnetic field action, the microhardness values for the matrices vary 7700–11400 MPa, while for the dislocations they are 10300–12700 MPa.  Fig. 1.22 Microhardness per the structural units of Сz-Si(Cu) samples (in the initial state, after 240and 720-hour exposition to direct-current magnetic field) 66506350 8020 9770 8130 9070 0 2000 4000 6000 8000 10000 12000 Matrix Dislocations Microhardness, MPa  Fig. 1.23 Microhardness graphs for Сz-Si(Mg) samples: a – after 240 hours of exposing to direct-current magnetic field; b – after 720 hours of exposing to direct-current magnetic field 7500 8000 8500 9000 9500 10000 10500 11000 11500 12000 12500 13000 12345678910 Microhardness, MPa Number of measurements Matrix Dislocations 7500 8000 8500 9000 9500 10000 10500 11000 11500 12000 12500 13000 1 2 3 4 5 6 7 8 9 10 Microhardness, MPa Number of measurements Matrix Dislocations a b Fig. 1.24 presents the average values of microhardness per the structural units of Сz-Si(Mg) samples before and after treating with the direct-current magnetic field. This bar graph demonstrates that the microhardness values of the structural units increase during the time of exposing 48 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 1 this dependence considerably weakens and the notable irregularities in it are found if we study the Si samples doped with Zr, Hf (Fig. 1.31, b, c) and Mg (Fig. 1.31, c). Shortening the life time for the current minority-carriers can be explained as the relevance with that oxygen which the silicon surficial layers contain. As the publication reports [34], during the time when silicon is treated within the magnetic field, the oxygen content increases drastically in its surficial layers, the same is true for the ions of the alkaline metal (K+, Na+), hydroxyl groups and other radicals. This is related to the surface activation and enhancing its absorption ability under the influence of weak magnetic field.  Fig. 1.31 Dependence between the time span of the current minority-carriers and the average microhardness of the samples: a – initial state; b – after 240 hours of exposing to direct-current magnetic field; c – after 240 hours of exposing to direct-current magnetic field a b c Si Si Si(Hf) Si(Zr) Si(Zr) 0 100 200 300 400 500 600 600064006800720076008000 Microhardness, MPa Minority carrier lifetime, µm Minority carrier lifetime, µm Si Si(Hf) Si(Hf) Si(Zr) Si(Cu) Si(Mg) Si(Mg) Si(Al) Si(Al) Si(Fe) Si(Fe) 0 10 20 30 40 50 60 70 80 86009000940098001020010600110001140011800 Microhardness, MPa Minority carrier lifetime, µm 0 10 20 30 40 50 60 70 80 90 100 880093009800103001080011300 Microhardness, MPa Si(Cu) 49 chapter 1. Technological aspects of computer control of the secondary condensation complex of ammonia production under uncertainty CHAPTER 1 Apart from the oxygen in the principle state or the triplet state, the radical groups absorbed on the silicon surface also possess the ability of capturing the current carriers [33] and drastically decrease their lives in the free state. Doping silicon with the elements of a greater affinity for oxygen (Zr, Hf, Al) permits the decrease in the influence of oxygen on the charge carrier life time by its binding. This is an assumable explanation for the reason why the samples doped with the mentioned elements have quite high values for the auxiliary charge carrier life time if the microhardness values are also high. The exception to this regularity is Si(Al). Conclusions 1. The microstructure of the initial Cz-Si sample which is formed under the influence by the treatment within the magnetic field has been not studied before the research conducted for the current publication. The research reveals as follows: – during 240 hours of exposing to the magnetic field, there is the significant increase in the number of the internal structure defects and the density of the dislocations as well as the formation of twins; – during 720 hours of treating within the magnetic field, the polycrystalline silicon is formed with a large quantity of grain boundaries. 2. This research is the first time when it has been addressed to the problem of the magnetic field influences on the microstructure of Cz-Si doped with the elements which influence differently the energy of interaction between the silicon atoms within the crystal lattice, namely – Al, Mg, Cu, Fe, Zr, Hf. With this publication, we show what influence produces the treatment within the magnetic field on Cz-Si doped with those elements which are able to decrease the interaction energy of silicon atoms (Al, Mg, Cu, Fe). The data revealed can be summarized as follows: – there is an increase in the quantity of the sample structural defects at exposing during 240 hours but their notable decrease is observed during 720 hours; – Cz-Si doped with Zr and Hf, which increase the energy of interaction between the silicon atoms within the lattice, goes down significantly in the quantity of structural defects starting from at the point of 240 hours spent within the magnetic field. 3. By means of X-ray analysis conducted for the samples, which have been subjected to the magnetic field, it is registered that there are splits in the diffraction lines as well as the appearance of the new peaks at the scattering angles of 90–92 degrees. These phenomena are caused by the distortions of SiFCC crystal lattice and forming SiORTHORHOMBIC along with it. This evidences about the phase transformations in the samples of the semiconductive silicon when the magnetic treatment at the room temperature. 50 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 1 4. The study performed to address the problem of magnetic field influence on the microhardness of the doped Cz-Si has revealed as follows: – the microhardness of Cz-Si doped with Al, Mg, Cu, Fe grows by 1.8–2.0 times at exposing both during 240 hours and 720 hours; – the microhardness of Cz-Si doped with Zr, Hf grows by 1.5–1.8 times after exposing to the magnetic field during 240 hours while such values are higher by 1.2–1.5 times after 720 hours of exposition. 5. In this publication, the problem of the magnetic field treatment is first studied in terms of its influence on the physical properties of the doped Cz-Si, namely, its specific electric resistance (r, Оhm⋅cm), life time (τ, µs). It has been revealed as follows: – 240 hours spent within the magnetic field decrease the specific electric resistance (r, Оhm⋅cm) of Cz-Si by 1.7–2.0 times while 720 hours of exposing decrease this parameter by 1.08; – specific electric resistance (r, Оhm⋅cm) of Cz-Si Al, Cu decreases by 3.4 times at exposing within the magnetic field during the time period from 240 to 720 hours; – for Cz-Si doped with Zr we observe the decrease in specific electric resistance values (r, Оhm⋅cm) by 18 times after 240 hours of the mentioned exposing and by 13.5 times at 720 hours of exposition; – for Cz-Si doped with Hf, the specific electric resistance decreases by 13.5 times after 240 and 720 hours of exposing; – the life time for minority-carriers of the charge (τ, µs) decreases 900 times within Cz-Si under conditions of both 240 and 720 hours of the magnetic field treatment; – for Cz-Si doped with aluminium, the life time for minority-carriers of the charge decreases by 30 times when 240 hours of treatment while the decrease in 38 times is detected after 720 hours of exposing; – for Cz-Si doped with copper, the life time for its minority-carriers of the charge decreases by 8–9 times both under 240 hours and 720 hours within the magnetic field; – for Cz-Si doped with hafnium, the life time for its minority-carriers of the charge (τ, µs) decreases by 6 times at 240 hours and by 5 times at 720 hours of exposing; – doping with zirconium enables sustaining the longest life times for its minority-carriers of the charge (τ, µs) vs those of the initial state: the life time for its minority-carriers of the charge experiences the shortening just by 2.4–3.2 after exposing within the magnetic field during 240 and 720 hours and they correspond to the values of 93.3 µs and 69.57 µs, respectively, compared against 0.63–0.65 of Cz-Si. 6. In this publication, we report on the development of the new complex production technology for silicon semiconductor. The technology includes the stages of silicon doping with the transition metals and rare earth metals, heat treatment at the temperatures of phase transformations and treating within the magnetic field at room temperature. These stages provide the enhanced set of the mechanical and the physical properties for Cz-Si products intended for devices. 51 chapter 1. Technological aspects of computer control of the secondary condensation complex of ammonia production under uncertainty CHAPTER 1 References 1. Glazov, V. M., Timoshina, G. G., Mikhailova, M. S. (1996). Printcipy legirovaniia kremniia dlia povysheniia ego termostabilnosti. Doklady Akademii Nauk, 347 (3), 352–355. 2. Taran, Yu. N., Glazov, V. M., Regel, A. R., Kutsova, V. Z., Koltsov, V. B., Timoshina, G. G. et al. (1991). 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Dnepropetrovsk, Ukraine. 54 CHAPTER 2 CHAPTER 2 abstract Green energy includes solar, wind, geothermal and other types of energy sources generation. The object of this research is solar concentrators. The problem to be solved is connected with the development of the structure frame, especially for solar concentrators with flat triangular or square mirrors that approximate a parabolic shape surface. The essence of the investigation is developing and producing several prototypes of solar concentrators that have low cost of materials but since the devices were assembled by hand, the cost their manufacture is quite high. Therefore, it is important to reduce cost through automation of solar concentrator production process. To obtain the better condition for future automation it is necessary to reduce the number of metal structural elements of solar concentrator. In this case the automation problem is simpler for its realization. The purpose of the research is to develop a new and improved design of the solar concentrator frame prototype, which should be technologically simpler than the previous one and lighter in weight. The study proposes a new frame structure design that contains fewer metal elements, is lighter than the previous one and is more convenient for the automatic assembly process. The development of improved solar concentrator design and structure can help to reduce the cost of assembly and to accelerate the solar concentrator assembly process. In case of massive production, they can be used in practice. The proposed solar concentrators can be used, in particular, for green buildings in rural areas, in reactors to accelerate the chemical process of processing organic waste, in agriculture in combination with agricultural fields. These solar concentrators are quite promising in combination with small thermal energy storage devices, with the help of which it is possible to create small power plants for green buildings that satisfy all the energy needs of residential buildings. KEYWORDS Solar energy, flat facet parabolic solar concentrator, thermal energy storage, support frame. Energy consumption is growing all over the world due to new lifestyle trends in the form of the increasing use of electronic devices. Global energy consumption will grow nearly 50% from 2018 DOI: 10.15587/978-617-8360-19-1.CH2 Valerii Samsonkin, Valerii Druz, Oksana Yurchenko © The Author(s) of individual chapters, 2025. This is an Open Access chapter distributed under the terms of the CC BY license Management of transport systems and processes based on a unified theory of self-organizing systems 55 chapter 2. Management of transport systems and processes based on a unified theory of self-organizing systems CHAPTER 2 through 2050, according to the U.S. Energy Information Administration (EIA) [1]. With the threat of global warming and the rising cost of energy, the trend towards the use of renewable and sustainable energy sources is becoming more and more popular. The use of solar energy, for example, in Mexico or in Azerbaijan, has great potential, since these countries have good conditions for the development of this industry, which is expressed in the duration of sunny days, their number, as well as direct solar radiation on the surface [2]. Solar energy is the most powerful and affordable, as well as the use of solar energy is leading in renewable energy. Solar power plants are designed to convert the energy of solar radiation into heat and electricity. There are the following types: 1) photovoltaic (PV) converters that are used to directly convert electricity through the photovoltaic effect [3, 4]; 2) thermal concentrated solar power (CSP) that are designed to produce thermal energy for its further use or conversion into other types of energy. The mirrors and lenses are used in CSP to generate thermal energy. Photovoltaic converters used semiconductors. The operation of the device is based on the emission of photoelectrons or the internal photoelectric effect. Currently, silicon-based photovoltaic modules (single-crystal and polycrystalline) are the most common type. Solar concentrators are devices that capture incoming solar radiation and convert it into usable heat. This heat is transferred to the working liquid for transfer directly to the consumer, to a heat exchanger, or a heat engine (for example, Stirling or Ericsson engines) to generate electricity. The temperature level of the working liquid determines its energy performance, and the main factor is the mass flow rate of the working liquid. There are installations for the simultaneous production of electricity and hot water at the outlet. Renewable energy has many aspects to develop. Solar, wind, geothermal energy and so on demand the special instruments and apparatus to generate electricity from different energy sources. So, industrial engineering and engineering design are very important to be developed. But not only engineering side of this problem is important. For example, the storage and transportation of renewable energy is very important too [5]. For this reason, the mathematical models are constructed to evaluate or optimize the renewable energy systems [6, 7]. In [7] the authors not only created the mathematical model but and applied the model to analyze energy storage and hydrogen production at renewable energy power plants in Japan in 2050. It is important to integrate renewable energy sources for new housing developments to reduce demand for grid energy and carbon emissions [8]. Different technologies are oriented to include or to combine with green energy [9, 10]. An effective response to climate change is a rapid replacement of fossil carbon energy sources with green energy [10]. So, the target of decarbonization in the energy sector can be achieved. The intensification of the use of different renewable energy sources is essential for the fulfillment of the Paris Agreement or for achieving the goals of sustainable development [11]. 56 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 2 So, green energy, and especially solar energy generation is very actual and important area of science and engineering. To create cheap and effective devices is a challenge for scientists. 2.1 Literature review and problem statement Solar energy is one of the most accessible energy sources. Different countries actively develop the photovoltaic systems. For example, one of the leaders in these investigations is India [12]. Development and application of solar energy have been regarded by the government of India and common people, and they thought that solar photovoltaic energy can provide more energy in future compare to other renewable energies. Not only photovoltaic systems are developed. Parabolic solar concentrators are developed [13]. The authors developed a system comprising external parabolic solar concentrators integrated with cylindrical vertical type sensible-based thermal energy storage (TES) tanks. Solar concentrators can generate thermal energy in the highest operating temperature range (≥300°С) and can be used in solar thermal-energy applications in the industrial sector [14]. Parabolic dish concentrator converts 72% of solar energy into usable heat [15]. With 50% of global energy consumption in the form of heat, the market for thermal energy is vast. The parabolic concentrators are expensive because of using large-area curved mirrors. A way to overcome these difficulties can be connected with plane mirror using. To reduce the cost, let's propose to use plane mirrors that have a cost 2–3 dollars for one square meter. For our task it is necessary only to cut them. Low cost parabolic solar concentrators based on multitude of small triangular flat mirrors that can approximate parabolic surfaces were developed [16]. These solar concentrators can be used for energy supply to residential houses [17]. Small scale residential power plant will contain flat facet parabolic solar concentrators, TES, and powerhouse hall. Let's present in Fig. 2.1 two possible variants of their collocation. The system presented in Fig. 2.1, a, is better when there are free areas or can combine the solar concentrators with agricultural fields [17]. The system presented in Fig. 2.1, b, is better for economic surface using. Parabolic solar concentrators can generate heat energy (approximately 300–400°С) in the focal point and then can be accumulated in TES. Equipment for transformation of heat energy to electrical energy and middle/low temperature heat energy is situates in powerhouse hall. Middle/low temperature heat energy can be used for space and water heating (for example, hot water we can use for chemical reactors to accelerate the chemical process of organic waste processing [6]), for meal preparation, etc. Electrical energy is needed for illumination and electrical devices feeding. Let's propose the design of solar concentrators and TES [6]. Flat facet solar concentrators were proposed in 80th years and the prototype of solar energy plant based on these concentrators was made in Australia, White Cliffs (1998) [18, 19]. After that many versions of flat facet solar concentrators were proposed, developed and patented. 57 chapter 2. Management of transport systems and processes based on a unified theory of self-organizing systems CHAPTER 2  Fig. 2.1 Residential power plant: a – parabolic solar concentrators are collocated in special zone; b – solar concentrators are combined in the roof of TES and powerhouse The main goal of these works is to decrease the cost of materials and labour needed for parabolic solar concentrator manufacture. 2.1.1 Existed prototypes of solar concentrators Last decade we developed several prototypes of flat facet concentrators and improved the methods of adjustment of parabolic surface [19–21]. It is possible to estimate the cost of concentrators near 20 or 30 USA dollars per square meter. This cost permits to supply all needed energy for the houses in countries with hot arid climate, for example, in Azerbaijan and Mexico. In countries with cold climate such as Ukraine and Canada solar energy can provide a significant part (sometimes more than half) of the energy consumed by a residential house. So, let's consider the possibility of using solar concentrators in different countries. In this regard, let's propose a brief analytical review of modern technologies of existing solar concentrators. 64 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 2  Fig. 2.7 First structure project Source: [16]  Fig. 2.8 Support structure frame of the first prototype: a – four mirrors collocated on the structure; b – concentration of solar energy in focal point a b 65 chapter 2. Management of transport systems and processes based on a unified theory of self-organizing systems CHAPTER 2 2.3.1.2 Number of mirrors In common case it is possible to calculate the number of mirror N using the following equation: Nn=⋅ () −66 2, (2.1) where n – the number of layer. In the next paragraph, let's explain this formula in more detail. Several prototypes of one meter of diameter were made. In these prototypes we did not place the mirrors in the center (minus 6 mirrors). This hole is used for collocate the gauge with parabolic edge to adjust all screws to obtain the parabolic surface curve [16, 20]. In Fig. 2.9, the solar concentrator prototype is presented that contains six layers and in accordance with equation (2.1) contains 210 flat mirrors. This structure was patented in USA, Spain and Mexico. In this case we used the same principle: one cell for one flat mirror.  Fig. 2.9 Prototype with the first structure model Source: [20] The main disadvantage is the large number of elements in the structure. Let's use aluminum, which is lightweight, but the number of elements complicates the assembly of the device. The assumptions made in the work are following: it is possible to reduce number of structural metallic elements without loss of structural strength; with reducing of number of elements we can do the structure lighter than previous structure. Simplifications adopted in the work are connected with idea that we can use structural elements of the previous prototype as basic elements of the structure of solar concentrator. 2.3.2 Materials The materials that were used in the study are metallic components for support frame. It was used aluminum bars (Fig. 2.7–2.9). The structure in this case is sufficiently light and firm. 66 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 2 Before constructing the prototypes, it is possible to simulate the elements and structure of solar concentrator using SolidWork. 2.3.3 Methods As method that was used in the study is a geometrical model of solar concentrator. It was selected the diameter of solar concentrator 1.6 meters. With calculations using this model it was demonstrated the possibility to obtain sufficient thermal energy with proposed solar concentrators. 2.3.3.1 Geometric model of solar concentrator This part presents the mathematical description of the model. The sketch of solar concentrator is drawn in the SolidWorks software environment (Fig. 2.10). The main parameters are shown in the Table 2.1. We want to explain the values from the Table 2.1. They were obtained for our prototype of solar concentrator. The concentrator contains N = 210 flat mirrors, which have a triangular shape with size of one side L1 (Fig. 2.10) [6].  Fig. 2.10 Model of solar concentrator with parameters Source: [6]  Table 2.1 Parameters of the parabolic concentrator Parameter name Value Unit Concentrator diameter (Dc) 1.6 m Size of a mirror side (L1) 0.13 m Solar constant (kW per square meter) (Cs) 1.361 kW/m2 67 chapter 2. Management of transport systems and processes based on a unified theory of self-organizing systems CHAPTER 2 The surface area of the parabolic concentrator can be calculated using equation A D c c == ⋅ = π2 2 4 314256 4 201 .. .. m (2.2) The power of the concentrator with this area is possible to present as W NL Ct CS M C =⋅⋅⋅ ⋅⋅ =⋅ ⋅⋅⋅⋅ = 1 22 24 3 4 210 0131361 7 24 07 3 4 2091 53η.. ., W (2.3) where WC – the concentrator power; N – the number of mirrors; L1 – the size of a mirror side; CS – the solar constant (amount of energy that reaches 1 square meter of the earth) (Cs = = 1.361 kW/m2) [34]; tM – the number of hours (average) with the direct sun (not diffuse), for example, in Mexico, 7 hours of sunlight per day; hC – the concentrator efficiency (hC = 0.7). Satellites have directly measured the amount of energy arriving at Earth from the Sun as sunlight. Although this value varies slightly over time, it is usually very close to 1,361 watts of power per square meter (1.4 kW). The concentrator contains N = 210 flat mirrors, which have a triangular shape with size of one side L1 (Fig. 2.8) [6]. So, there is concentrator power (WC) more than 2 kW that is sufficient to built a system with thermal energy storage and use it for chemical reactor heating. 2.3.3.2 Calculation of number of structural elements To calculate the number of structural elements we present schematically part of solar concentrator structure. We can on the base of every external side (side LC in Fig. 2.10) demonstrate the triangular zone that begins from outside line to the central point of solar concentrator structure. One triangle it is schematically presented in Fig. 2.11. The one triangle corresponds to triangle ABC (in this case AB = Lc). We can on the base of every side demonstrate the triangle that begins from outside line to the central point of solar concentrator structure. We want to consider one triangle as it is schematically presented in Fig. 2.11. The one triangle corresponds to triangle ABC (in this case AB = Lc). It is possible to see the triangle ABC (magenta colour), where point C is the central point of structure of solar concentrator and near this point we begin to place four triangular mirrors. Triangle ABC is 1/6 part of the solar concentrator structure (for this reason in equation (2.1) let's multiply by 6). There are seven lines which are parallel to AB line (blue colour). So, every zone has 49 triangular mirrors. In total, there is the solar concentrator with 288 mirrors (49*6–6 = 294–6 = 288 mirrors) if we do not include six mirrors in center of the solar concentrator structure. Every mirror is collocated on cell from three upper aluminum bars that are connected with three vertical bars with other three lower aluminum bars. To make the system from bars 68 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 2 tough three diagonal bars were added. So, every cell includes 12 bars. If the structure contains 288 mirrors so it is necessary to construct it 3456 metal bars.  Fig. 2.11 Triangle ABC of solar concentrator In the first type of structure every triangular mirror has the support cell for every mirror (Fig. 2.7, 2.8). Every vertex of the triangle has a fixing screw. The problem of this prototype is complexity of the solar concentrator structure (Fig. 2.10) and large number of structural metal elements for automatic assembly. Next, let's look at the frame improvements of the prototype of solar concentrator. 2.3.4 Software The methods that were used in the study are simulating of the support structure using SolidWork. After that the hardware as prototypes of solar concentrators were made to validate the proposed solutions. At the first stage we used SolidWork software to simulate the the 3D models of structure of solar concentrator. 2.4 New structure of solar concentrator with flat triangular mirrors 2.4.1 Reducing the number of structural elements The second structure of the support frame was developed after the model described in Section 2.3.1.1. New structure is presented in Fig. 2.12. Instead of triangular cells for every mirror 69 chapter 2. Management of transport systems and processes based on a unified theory of self-organizing systems CHAPTER 2 it was proposed to have parallel bars in every zone of structure to collocate several mirrors. As for the first prototype and for the second prototype the structure has six zones (hexagon shape); so, the structure in the both cases have six external sides. In Fig. 2.12, a is presented the structure from parallel bars. In Fig. 2.12, b one zone with screws (black points) that are used to fix the triangular mirrors. The same scheme is used for all six triangular zones of concentrators [35].  Fig. 2.12 The second structure model: a – structure from parallel bars; b – one zone with screws (black points) In Fig. 2.13, let's present the scheme of screw connection for mirrors with metallic elements that we use. This connecting node contains distance ring; washer (to protect mirror) and screw.  Fig. 2.13 Scheme of screw connection for mirrors For the first model the number of metal structural elements has been calculated in case of seven parallel lines in every zone (Fig. 2.9). It was 3456 aluminium bars. 70 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 2 2.4.2 Calculation of structural elements If to analyze the second model with seven lines we decrease by 56 the number of metal elements (in Fig. 2.12 we demonstrate only six lines in every zone). In Fig. 2.14, let's present the structure with mirrors in one zone. The total number of triangular mirrors N we can calculate as in equation (2.1). But the number of horizontal top bars, vertical bars, diagonal bars and horizontal low bars (Fig. 2.7) will decrease significantly. In Fig. 2.15, let's present the simulation of the solar concentrator structure with flat triangular mirrors with new support frame.  Fig. 2.14 Structure with mirrors  Fig. 2.15 The concentrator with the second structure model 71 chapter 2. Management of transport systems and processes based on a unified theory of self-organizing systems CHAPTER 2 For example, it is possible to analyze the situation with horizontal top bars. Number of bars in the center of prototype is not changed: six radial bars and six perimertric bars. In total, there are 12 bars in the center with length of triangular size a. With every new line the gain will be more significant. The primer line after center in the first prototype (Fig. 2.9) had K1 = (7–1·6 = 36 bars with length of triangular size a. In new version (Fig. 2.12, 2.14) line 1 has K2 = (2·6)l = 12l+2a bars, where l = 2a. If the first line has bar with length (a) the second line has the size of (2a). And every new line will have the size (n·a), where n is the number of lines. It is possible to imagine the prototype with two lines. In this case for the first prototype K1 = (11–2)·6 = 54 bars. For the second prototype K2 = (3·6)l+2a = 18l+2a bars with length (l = 3a). If the frame has three lines for the first prototype K1 = (15–3)·6 = 72 bars. For the second prototype K2 = (4·6)l+2a = 24l+2a bars with length (l = 4a) and so on. This reducing of number of bars is described only for horizontal top bars. But if the vertical, diagonal and horizontal low bars analyzed too, the savings will be greater. In total, if for the first prototype it was said about thousands of structural elements, then in this new case it is only about tens elements. If the structure contains six or seven lines in one zone, there is the solar concentrator from one to two meters of diameter. It is not heavy and can be carried, transported and installed in different places. The advantage of new model is less consumption of metal bars. So, in this case the solar concentrator will be light in comparison with the weight of previous one. 2.5 Discussion It was proposed the geometrical model of solar concentrator and the results of calculations with this model (equations (2.2) and (2.3)) demonstrated that it is possible to build solar concentrator with 1.6 meters of diameter to obtain sufficient energy for heating. Due to its small size and weight the concentrator can be easily transported and installed. This solar concentrator is possible to install on the roofs of the buildings as TV antennas. The main result that was obtained is a development of new support structure for prototype of solar concentrator. New support structure (support frame) of a solar parabolic concentrator was developed to reduce the number of structural elements, and as consequence of this, to reduce the cost and make construction lighter and easier to automatic assembly (Fig. 2.12, 2.14). This prototype, in comparison with the first model developed earlier (Fig. 2.7, 2.8), contains less metal elements in the structure. It is not necessary to construct the cell for every triangular mirror from metal elements as it was made in the first prototype. For mirror supporting is sufficient to have horizontal bars as it is presented in Fig. 2.12, 2.14. Green energy is a future of energetic development. So, any contribution to the technological aspects of this solar energy capture process is very important. 72 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 2 It was developed and described new frame of solar concentrator prototype in what the parabolic surface was approximated by triangular plane mirrors. After analysis of the first model of solar concentrator the possibilities for its improving were found. The first prototypes are presented in Fig. 2.7, 2.8. For the comparison the new structure is presented in Fig. 2.12, 2.14. The new structure has advantages compared to the previous version. For example, fewer structural elements that allows for easier assembly process. Fewer automation steps result in shorter build times. Also, in this case, the prototype structure becomes lighter. It is easier to transport and install this compact solar concentrator prototype with diameter of 1.6 meters. This new structure is more convenient for automation of the assembly process of solar concentrators in future. The parabolic solar concentrators provide a clean, inexpensive source of thermal energy for a wide range of applications, including industrial process heat, space heating and cooling, hot water, water desalination and purification, and remote and distributed power applications. The proposed solar concentrators can be used directly to produce heat energy. To produce electrical energy, it is necessary to use Stirling thermal motor or Ericsson motor in focal point to convert heat energy to electricity. The proposed solar concentrators can be used for different applications, for example, for green buildings in rural areas, or for chemical reactors to accelerate the chemical process of organic waste processing. Other application is to use solar concentrators in combination with agricultural fields. These solar concentrators can be used with small scale TES. Using TES, it is possible to make power plants for green buildings. Small solar power plants can support all the energy demands of residential houses. The limitations of the study that must be taken into account when trying to apply in practice are connected with necessity to develop or to adapt existing sun tracking system, which can increase the efficiency of solar concentrator system. It is important to investigate as well as in further theoretical studies of solar concentrator systems to improve their structure and work. Conclusions 1. In comparison with existed models of solar concentrators it was proposed the concentrator from one meter of diameter to two meters of diameter that is less than it is known from literature (for example, 9 meters). It was demonstrated with geometrical model that diameter of 1.6 meters is sufficient to produce thermal energy. The number of structural elements was more than three thousand elements. 2. The new model of support frame of solar concentrator was proposed. The result is a decreased number of structural metal elements. New design of frame structure is presented which contains less metal elements and it is lighter in comparison with previous one and more convenient for automatic assembly process. Instead of thousands of structural elements as for the first prototype in this case we are talking about several tens. The disadvantage is connected with the size of elements. For the 73 chapter 2. Management of transport systems and processes based on a unified theory of self-organizing systems CHAPTER 2 first concentrator all elements are unified; there are only three types. For the second solar concentrator there are different elements with different sizes but there are much fewer of them. The cost of the both types of concentrators is small because of using the flat triangular mirrors. With this investigation the cost of solar concentrator can decrease even more. It was proposed the scheme of screw connection for mirrors with metallic elements. This connection method is safe and reliable. Financing This research was partly supported by the project UNAM-DGAPA-PAPIIT IT 102320. Acknowledgments We thank Dra. Graciela Velasco Herrera for their comments on the text of this article and the master's and postgraduate students that help us in different aspects of investigation. References 1. Market Overview (2021). Energy Information Administration (EIA). International Energy Agency (IEA). Available at: https://www.solarflux.co/markets/ 2. Kussul, E., Baydyk, T., Mammadova, M., Rodriguez Mendoza, J. L. (2022). Solar concentrator applications in agriculture. Energy facilities: management and design and technological innovations. Kharkiv: PC TECHNOLOGY CENTER, 177–207. https://doi.org/10.15587/978617-7319-63-3.ch5 3. Renewable energy solutions. Suncatcher Energy. Available at: https://suncatcherenergy.com/ Last accessed: 12.01.2024 4. Solar Energy for Homes, Businesses, and Farms. Suncatcher Solar. Available at: https:// suncatchersolar.com/ Last accessed: 12.01.2024 5. Kousksou, T., Bruel, P., Jamil, A., El Rhafiki, T., Zeraouli, Y. (2014). Energy storage: Applications and challenges. Solar Energy Materials and Solar Cells, 120, 59–80. https://doi.org/ 10.1016/j.solmat.2013.08.015 6. Kussul, E., Baydyk, T., Curtidor, A., Herrera, G. V. (2023). Modeling a system with solar concentrators and thermal energy storage. Problems of Information Society, 14 (2), 15–23. https://doi.org/10.25045/jpis.v14.i2.02 7. Harada, K., Yabe, K., Takami, H., Goto, A., Sato, Y., Hayashi, Y. (2023). Two-step approach for quasi-optimization of energy storage and transportation at renewable energy site. Renewable Energy, 211, 846–858. https://doi.org/10.1016/j.renene.2023.04.030 80 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 3  Table 3.2 Brief description of key technologies of waste processing [18] Production technology Features Clean material recovery facility Dirty material recovery facility Mechanical biological treatment Mechanical heat treatment Feedstock Mixed/Commingled recyclables (Municipal & Commercial) Mixed Residual Waste (Mainly C&D municipal & commercial waste) Mixed putrescible residual waste (mostly municipal) Mixed residual wastes (Municipal and Commercial) Product/outputs – Separated recyclable materials: paper, cardboard, plastics, glass, steel and aluminum. – Glass fines for potential further processing. – Light residuals-potential RDF. – Residual to landfill – Separated recyclable materials including paper, cardboard, plastics, glass, steel, aluminum, masonry product, soil, timber. – RDF. – Residuals to landfill – Low grade soil amendment/compost. – Recyclable material including rigid plastics, steel and aluminum. – RDF. – Residuals to landfill – Organic rich fiber-low grade soil amender, fuel. – RDF from inorganic fraction-to thermal process. – Recyclables (low grade)  Fig. 3.1 RDF production technology removes non-combustible components improves treatment effect reduces volume removes foreign materials improves storing and handling capabilities by peletization increases the calorific value and storing capability The steps and necessary equipment for the production of RDF are given below [17]: 1. Waste reception, sampling, manual sorting and bag opening area: MSW arriving by appropriate transport is unloaded for sampling, manual sorting of large components and transported to bag opening machines. 2. Sorting includes the separation of municipal solid waste into biodegradable, glass, textiles, paper, plastic, leather and rubber, metals and other hazardous municipal solid waste, as well as 81 chapter 3. Improvement of the method of linear-quadratic control of azimuthal drivers of the combined propulsion complex CHAPTER 3 inert materials. Secondary raw materials are extracted, which are then processed. The main components used in the production of RFD include directly combustible materials. 3. Primary crushing: the two-shaft primary crusher is designed for crushing residual waste to a size of less than 100 mm. 4. During drying, the material is dehydrated. This can happen both under the influence of solar radiation and in special dryers. This process increases the calorific value of the material, reduces the mass, and also increases the ability to store fuel for a long time. 5. A rotary drum is used to separate the material by size. Separation usually occurs in two or more stages of the process. This is done by passing the waste through drum screens, most often roller drums with different hole sizes. At various stages of processing, conveyor belts are attached to conveyor belts and positioned at an angle to allow oversized materials to pass over them. Remaining material is thrown onto the conveyor belt, which transports the material for further processing. Magnetic separators are used to remove any metals from remaining material. The device uses eddy currents that create a powerful magnetic field that makes separation possible. The eddy current separator is applied to a conveyor belt that transports a layer of mixed waste. At the end of the conveyor belt is an eddy current rotor. Fans on the air separation stage are used to create a column of air moving upwards. Light materials are blown up, and dense materials fall. Air carrying lightweight materials such as paper and plastic bags enters a separator where these items fall out of the air stream. The quality of separation at this stage depends on the strength of air currents and the method of introducing materials into the column. Moisture content is also critical, as water can weigh down some materials or cause them to stick together. 6. The two-roller secondary chopper is designed for secondary crushing of material to a thickness of less than 50 mm. After that happens finer crushing to an RDF particle size of less than 25 mm. 7. The compacting of material is intended for the production of fuel pellets with a diameter of 16–25 mm by extrusion. The crushed material is fed into the granulator by gravity. The roller pushes the material through holes of the die and extrudes the material. The knife under the press die can adjust the size of the granules. Then the granules are cooled on a cooling conveyor and sent to storage. The choice of municipal solid waste processing technology directly depends on the characteristics of the waste. The defining characteristics are the morphological, fractional and chemical composition, density, heat of combustion and moisture content of municipal solid waste [11]. These characteristics depend on the place and time of waste generation. The average annual morphological composition for large cities of Ukraine is presented in Fig. 3.2 [22]. The largest share is food waste, which has high moisture content and low calorific value, so it is not recommended to use it for the production of RDF. If the non-combustible components to separate, it is possible to predict the composition of fuel that can be obtained in large cities of Ukraine. In this case, RDF can contain polymer materials, paper and cardboard, textiles, wood, leather and rubber (Fig. 3.3). 82 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 3  Fig. 3.2 Morphological composition of MSW for large cities of Ukraine  Fig. 3.3 Average morphological composition of combustible solid waste, which can be raw materials for RDF 83 chapter 3. Improvement of the method of linear-quadratic control of azimuthal drivers of the combined propulsion complex CHAPTER 3 Analysis of technological stages of RDF production showed that all stages of production are energy consuming. The drying stage is characterized by particularly high energy consumption. Drying processes account for about 40–50% of the total energy consumption, and in cases of drying municipal solid waste with high humidity, the consumption increases to 70%. Low energy efficiency is characteristic of the stages of raw material preparation, which affects the energy efficiency of production in general and the cost of fuel. Thus, about 10–20% of the total energy consumption is spent on crushing. Granulation is the final stage of solid fuel production and 10–30% of total energy is spent on its implementation. Granulation costs depend on the physico-mechanical and physico-chemical properties of the fuel components, pressure and temperature in the compaction zone. Due to the insufficient amount of experimental data on the physico-chemical and physico-mechanical properties of municipal solid waste, there may be energy overspending during the production of fuel from this type of raw material. Therefore, research and identification of influencing factors on raw material preparation and drying processes will improve fuel quality and ensure a stable year-round production cycle. The study of methods of preparing raw materials for drying and modeling the kinetics of dehydration in drying devices will allow to develop ways and directions of energy saving. Increasing the calorific value of composite fuel based on MSW requires combining components, the physical and chemical properties of which are not sufficiently studied. Combustion of RDF also requires knowledge of kinetics of thermal decomposition of components and generation of heat. The efficiency of using RDF is determined by obtaining its characteristics during the combustion process. The results of the thermal analysis, as well as the determination of the calorific value, are important. 3.2 Study of regularity of RDF convective drying 3.2.1 Preparation of municipal solid waste for drying 1. The composition of municipal solid waste in Ukraine was analyzed, among which RDF was allocated (40% of the total mass of waste). The main components are highlighted: wood, textile materials, polymer materials, paper, cardboard, leather, rubber, bones. 2. 4 types of mixtures are made from 5 groups of materials, including: wood (5 – 23%), textile materials (12 – 16%), polymer materials (25 – 50%), paper, cardboard (25 – 50%), leather, rubber, bones (3 – 4%) (Table 3.3). 3. The initial moisture content of the obtained mixtures was determined, which is from 5 to 6%, which depends on the composition. 4. The mixtures were dried to a completely dry mass at a coolant temperature of 150°С and duration of 4 hours for the subsequent uniform moistening of these mixtures. 84 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 3  Table 3.3 Composition of RDF (100 g) The name of the component RDF Composition of mixtures, %/g І mixture ІІ mixture ІІІ mixture ІV mixture Wood (pine) 23 5 5 5 Textile materials (cotton, synthetic fabrics) 12 15 16 16 Polymer materials (PET bottles, polyethylene film) 31 40 50 25 Paper, cardboard 31 37 25 50 Skin, rubber, bones 3 3 4 4 5. Before conducting research, it is possible to determine the initial moisture content of RDF. The RDF mixture is placed into boxes and dried in a laboratory dryer for 5 hours at a temperature of 105°С. After drying, the boxes are removed from the laboratory dryer and placed in a desiccator to cool for 15–30 minutes. Cooled boxes with material are weighed in a closed state on scales. The moisture content of the material relative to the mass of the dry substance is calculated as a percentage Wmm mm = − − ⋅ 23 31 100 %, (3.1) where m1 – mass of the empty box (with a lid), g; m2 – mass of the box with the research sample before drying, g; m3 – mass of the box with research sample after drying, g. 6. Research on the drying of RDF samples begins with setting the drying mode on a convective stand [23], then the sample is placed on a grid of scales in the drying chamber, and a computer program for collecting and processing information is turned on, which continuously records the time and change in the mass of the sample, the heat carrier temperature and the temperature in the middle of sample. 7. After drying, RDF samples are removed from the drying chamber and analyzed for quality characteristics and the final moisture content of the material is determined according to item 5 and formula (3.1). 8. After determining the absolutely dry mass of the sample, the computer program determines the current moisture content of the material W during drying and calculates and plots drying curves and drying rates: W = f(τ), dW/dτ = f(W). 9. The characteristics are calculated using a specially developed program "Sooshka". 10.1. Kinetic of the drying process W t Gt G G ad ad () = () − ⋅ .. .. %, 100 (3.2) where G t () – calculations of mass of sample, g; Ga.d. – absolutely dry mass, g. 85 chapter 3. Improvement of the method of linear-quadratic control of azimuthal drivers of the combined propulsion complex CHAPTER 3 10.2. The drying speed is determined NdW d = τ. (3.3) 10.3. The drying temperature coefficient is an estimate of the derivative of the average temperature of the sample from the moisture content bdt dU aver = , (3.4) where U W=100 – moisture content of the sample, %; taver – calculated as the average value of the temperature calculation on the surface and in the sample material, °С. 10.4. Rebinder number is equal to the ratio of the amount of heat expended to heat the body to the amount of heat to evaporate moisture in an infinitesimally small period of time Rb c r b= , (3.5) where с – specific heat capacity of the material, kJ/(kg·°С); r – specific heat of phase transformation, kJ/kg. 10.5. The heat flux per unit surface of the sample is calculated from the ratio q rg dU dRbτ τ () =      + () 1, (3.6) where g = Ga.d./Sm – the ratio of the mass of absolutely dry body to the surface of the material. 10.6. The heat transfer coefficient is determined by the formula ατ θ = ⋅ () − 1000 q t, (3.7) where t – heat carrier temperature; θ – sample temperature. 3.2.2 Research of drying modes of RDF The study of drying modes is carried out with the determination of the influence of the following factors: the heat carrier temperature (80–120°С), the speed of movement of the heat car rier (1.5–2.5 m/s) and the composition of the mixture (No. 1–4). The influence of heat carrier temperature on the kinetic of the drying process. When the temperature of the heat carrier increases from 80 to 120°С, the drying duration is accelerated by 56%. 86 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 3 eating of the material in a layer of 15 mm to the final temperature takes place within 10–15 minutes. The material at a heat carrier temperature of 80°С heats up to a temperature of 78.8°С, at a temperature of 100°С – 98.9°С, at a temperature of 120°С – 119.8°С (Fig. 3.4). The process of drying municipal solid waste is in 2 stages: a period of heating up to the maximum drying speed and a period of falling drying speed (Fig. 3.5).  Fig. 3.4 Effect of heat carrier temperature on the kinetics of the RDF drying process: V = 2.5 m/s, d = 10 g/kg dry air, δ = 15 mm, mixture No. 1: 1, 1′ – 80°С; 2, 2′ – 100°С; 3, 3′ – 120°С  Fig. 3.5 Influence of heat carrier temperature on RDF drying speed V = 2.5 m/s, d = 10 g/kg dry air, δ = 15 mm, mixture No. 1: 1 – 80°С; 2 – 120°С 87 chapter 3. Improvement of the method of linear-quadratic control of azimuthal drivers of the combined propulsion complex CHAPTER 3 To compare the effect of coolant temperature on the drying speed of RDF mixtures, heat carrier temperatures of 80 and 120°С were selected. The maximum drying speed increases by 1.82 times when the heat carrier temperature increases (Fig. 3.5). The influence of the heat transfer speed on the kinetics of the drying process. Conducted studies of the effect of temperature on the kinetics of drying process showed that increasing the heat carrier temperature to 120°С significantly intensifies the drying process. Therefore, the effect of the speed of movement of the heat carrier on the kinetics of the drying process is carried out at a temperature of the heat carrier of 120°С. To compare the speeds of movement of heat carrier, speeds of 1.5 and 2.5 m/s were selected. Increasing the heat carrier speed from 1.5 to 2.5 m/s reduces the drying time by 6 minutes or by 38%. The heating temperature of the material at a heat carrier speed of 1.5 m/s is 115°С, which is 4.8°С lower than the heat carrier speed of 2.5 m/s (Fig. 3.6).  Fig. 3.6 The influence of the heat carrier speed on the kinetics of the RDF drying process t = 120°С, d = 10 g/kg dry air, δ = 15 mm, mixture No. 1: 1, 1′ – 2.5 m/s; 2, 2′ – 1.5 m/s The influence of the RDF mixture composition on the kinetics of drying process. According to Table 3.3, there are 4 types of RDF mixtures that can significantly affect the kinetics of the drying process. To study the kinetics of the drying process, it is possible to choose the drying mode studied earlier: coolant temperature 120°С, coolant movement speed 2.5 m/s. The analysis of the influence of the composition of RDF mixture on the kinetics of the drying process showed that it is appropriate to separate the comparison of mixtures No. 1, 2, 3 and No. 1, 4. The duration of drying of mixtures No. 1, 2, 3 (with the content of polymeric materials 88 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 3 from 31 to 50%) is 16 minutes, but the heating of the material occurs in different ways, which is connected with the composition of solid fuel. Thus, the final heating temperature of mixture No. 1 is 119.8°С, mixture No. 2 is 116.7°С, and mixture No. 3 is 117.6°С (Fig. 3.7). The influence of mixtures No. 1, 4 (with cardboard content from 31 to 50%) on the kinetics of the drying process was also analyzed (Fig. 3.8). When changing mixtures from No. 1 to No. 4, the duration of drying increases by 28%.  Fig. 3.7 Influence of the composition of mixture (1, 2, 3) on the kinetics of the RDF drying process t = 120°С, V = 2.5 m/s, d = 10 g/kg dry air, δ = 15 mm: 1 – mixture No. 1; 2 – mixture No. 2; 3 – mixture No. 3  Fig. 3.8 Influence of the composition of the mixture (1,4) on the kinetics of the RDF drying process t = 120°С, V = 2.5 m/s, d = 10 g/kg dry air, δ = 15 mm: 1 – mixture No. 1; 2 – mixture No. 4 89 chapter 3. Improvement of the method of linear-quadratic control of azimuthal drivers of the combined propulsion complex CHAPTER 3 3.2.3 Research of heat and mass exchange processes during drying RDF The kinetics of heat exchange during drying can be fully revealed by the data of the kinetics of moisture exchange. Value of magnitude dtdW determines the change in the average temperature of the dried material per unit of change in its average humidity over an infinitesimally small period of time and is called the drying temperature coefficient bdt dW = . (3.8) Magnitude b is a function of integral humidity bf W= () . Based on the ratio of RDF heating and moisture evaporation, as can be seen from Fig. 3.9, the most appropriate drying mode is 100°С.  Fig. 3.9 Change in the temperature coefficient depending on the moisture content of the material and the heat carrier temperature during the RDF drying process V = 2.5 m/s, d = 10 g/kg dry air, δ = 15 mm, mixture No. 1: 1 – 80°С, 2 – 100°С, 3 – 120°С General variable bcr () is an integral characteristic of the kinetics of the drying process. It determines the ratio heat amount of the heating of the material during drying and to the evaporation of moisture in an infinitesimally small period of time. This basic drying criterion is called the Rebinder number Rb b c r c r dt dW ==       . (3.9) 96 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 3  Table 3.7 Derivatograms of thermal decomposition of RDF samples and their description RDF A RDF A description Dehydration occurs in the range of 23–166°С. The moisture content of the sample is the highest among all fuel samples due to the high content of cardboard. The thermal decomposition of organic substances occurs in three stages differing in the decomposition rate and thermal effects. Decomposition of 43.99% DM occurs in the range of 166–352°С at a rate of 1.87% DM/min (Table 3.6). At the same time, heat generation is constantly increasing. At this stage, the maximum decomposition rate was registered at a temperature of 313°С. The decomposition rate increases to 2.41% DM/min in the second stage (352–470°С) due to polyethylene. The intense emission of gases outside the crucible leads to heat loss, which is registered on the DTA curve in the form of an endothermic peak with a maximum at 463°С. The decomposition of organic substances is completed at the third stage in the range of 470–530°С. A further increase in temperature causes the decomposition of mineral substances. Sample mass loss (TG and DTG curves) and heat absorption (DTA curve) are observed at temperatures of 648–733°С. This is a consequence of the thermal dissociation of calcium carbonate in the cardboard. The ash content of RDF A is 4.87% DM, and the determined net calorific value is 23.03 MJ/kg RDF В RDF В description Dehydration of RDF B ends at 166°С, as for RDF A, after which the stage of decomposition of organic substances begins (Table 3.5). This stage is also characterized by three stages of decomposition (Table 3.6). At the first stage (166–353°С), 35.67% DM is removed at a rate of 1.52% DM/min. At the second stage (353–476°С), the intensity of decomposition increases 1.9 times due to the high content of polyethylene film in the fuel. In the range of 419–501°С, a strong endothermic peak 97 chapter 3. Improvement of the method of linear-quadratic control of azimuthal drivers of the combined propulsion complex CHAPTER 3 is registered on the DTA curve, which was observed during the decomposition of the polyethylene sample. At the third stage (476–538°С), the intensity of decomposition of organic substances decreases. Increasing the polyethylene film content and decreasing the cardboard content in RDF B causes changes in the nature of the destruction of organic substances. The impact of polyethylene as a fuel component becomes more noticeable and causes a powerful release of decomposition products. At the same time, the net calorific value of RDF B increases to 27.01 MJ/kg compared to RDF A due to the contribution of the net calorific value of polyethylene film (42.56 MJ/kg) RDF С RDF С description The thermal decomposition of RDF C, in which PET bottle material was added instead of polyethylene film, is generally similar to RDF B. Water is removed in the range of 20–165°С (Table 3.5). A slight increase in heat release is observed (DTA curve) at the first stage of decomposition of organic substances (165–351°С). At the second stage, intense destruction is observed – the rate of decomposition increases by 2.4 times (Table 3.6) and reaches a maximum at 410°С. Against the background of general heat generation, a small endothermic peak indicates a slight release of gaseous decomposition products outside the crucible. In the range of 457–573°С (third stage), the rate of decomposition decreases and completely stops when reaching 573°С (DTG and DTA curves). Thermal dissociation of calcium carbonate in cardboard is registered in the range 655–726°С (DTG and DTA curves). The calorific value of fuel is reduced to 18.85 MJ/kg due to the replacement of polyethylene film with material from a PET bottle in the composition of RDF C RDF D  Continuation of Table 3.7 98 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 3 RDF D description The thermal decomposition of the RDF D occurs according to the decomposition patterns of RDF C. The moisture content of RDF D is 4.13% due to the low content of cardboard (Table 3.5). The stages of decomposition of organic substances differ significantly in decomposition rates (Table 3.6). A high content of polymer materials (50%) causes an increase in the rate of decomposition in the second stage (351–455°С) and the formation of a significant amount of gaseous products. These products escape the sample and cause a large heat loss, reflected as an endothermic peak in the DTA curve appears as an endothermic peak on the DTA curve with a maximum at 417°С. The destruction of organic substances ends at 560°С and is accompanied by a decrease in heat generation. The calorific value of this fuel is 24.60 MJ/kg RDF E RDF E description Water removal ends earlier by 8–10°С compared to previous fuel samples (Table 3.5). The decomposition of organic substances occurs in three stages, as for all experimental fuel samples. The highest intensity is characteristic of the second stage due to the high content of polymer components. Decomposition of 44.44% DM occurs at a rate of 2.78% DM/min. In the range of 435–498°С, an endothermic peak is registered on the DTA curve with a maximum at 458°С. It is a consequence of heat loss due to the formation of a significant amount of gaseous products leaving the sample location. The destruction of organic substances ends at 536°С. The net calorific value of the fuel is 26.46 MJ/kg due to the high content of polyethylene film RDF F  Continuation of Table 3.7 99 chapter 3. Improvement of the method of linear-quadratic control of azimuthal drivers of the combined propulsion complex CHAPTER 3 RDF F description Water is removed from RDF F in the temperature range of 20–165°С, after which the organic substances of RDF fuel decompose in three stages (Table 3.5). In the first and third stages, a slightly lower rate of decomposition is observed than in the second (Table 3.6), which is a consequence of deeper destruction processes in the second stage and the influence of the kinetics of polyethylene film decomposition. Heat generation increases in the second stage and reaches its maximum at 481°С (DTA curve). In this case, the endothermic peak accompanying the formation of gaseous substances is not observed. Thermally unstable mineral substances degrade in fuel components in the range of 534–1000°С with the formation of simpler molecules. The ash content is determined to be 3.52% DM. The process of calcium carbonate dissociation was observed in the range of 643–725°С. The net calorific value of this fuel composition is 25.22 MJ/kg RDF G RDF G description Water removal occurs in the narrowest range of all samples (23–154°С) due to the absence of cardboard in the composition. The decomposition of organic substances is accompanied by intense gas formation, as evidenced by three endothermic peaks (323–370, 370–428, 428–512°С) of different intensity. Most organic substances is removed at a rate of 2.89% DM/min in the second stage of decomposition. The lowest content of mineral substances (2.19% DM) and ash content (1.89% DM) is observed in RDF G among all experimental fuel samples due to the absence of cardboard in the fuel composition. The selected fuel composition provided the highest calorific value – 30.82 MJ/kg RDF H  Continuation of Table 3.7 100 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 3 RDF H description RDF H contains cardboard and polyethylene film in equal proportions and has the lowest moisture content (3.81%). The destruction of organic substances occurs according to the patterns characteristic of the above fuel samples, in particular RDF B and RDF E. The net calorific value of the fuel sample is 28.89 MJ/kg The analysis of the obtained data makes it possible to compare the destructive processes occurring in the fuel when it is heated to 1000°С. Dehydration of all RDF samples is completed at a temperature of 154–166°С (Table 3.5). The lowest temperature of the dehydration completion (154°С) is found in the RDF G sample, which does not contain cardboard. RDF A has a narrower range of decomposition of organic compounds (364 K). This is explained by the presence of a significant amount of cardboard in the composition, the decomposition of which is completed earlier by 23 K than polyethylene and by 79 K than PET. The widest range (408 K) is registered in RDF C, which has the highest PET content. The highest values of the average rate of decomposition have RDF A, B and F, which do not contain PET. It follows from this that an increase in the PET content in fuel causes an expansion of the temperature range of decomposition and a decrease in the overall rate of the decomposition of organic substances. DTA profiles (Table 3.7) indicate that for RDF containing only polyethylene polymers (Table 3.5), the release of gaseous substances occurs with an endothermic peak located in the range of 456–465°С. The same behavior and a similar maximum of the endothermic peak (459°С) were observed during the decomposition of polyethylene film. The PET presence in the fuel accelerates the release of gaseous substances. The maximum of the endothermic peak is registered at 410°С (RDF С) and 417°С (RDF D). In PET, this maximum was registered at 418°С. Determination of the calorific value Qn d of experimental fuel compositions showed (Fig. 3.13) that the highest calorific value is for RDF G, which does not contain cardboard, and the lowest is for RDF C, which does not contain polyethylene film. Conditional thermal effects (CTE) of thermal decomposition of organic substances were also determined using the "Derivatograph" application program (Fig. 3.13). CTE was calculated as the area between the DTA curve and the most likely estimated DTA baseline divided by the mass of the organic substances of the sample. The baseline is a straight line connecting the points of complete dehydration and completion of heat release. The area under the curves of exothermic thermal effects was determined by the trapezoidal method using the "Derivatograph" program. According to the obtained data, RDF E has the highest value of the specific thermal effect, and RDF D has the lowest value. As it is possible to see, this does not correspond to the results for determining the lower calorific value (Fig. 3.13). This confirms the assumption that the registered endothermic peak (DTA curves) underestimates the CTE value due to the loss of heat of thermal decomposition due to the emission of gaseous substances outside the crucible. Therefore, more accurate research results, namely a determined net calorific value of samples, should be taken into account when assessing the thermal characteristics of multicomponent RDF.  Continuation of Table 3.7 101 chapter 3. Improvement of the method of linear-quadratic control of azimuthal drivers of the combined propulsion complex CHAPTER 3  Fig. 3.13 Conditional thermal effects (CTE) and net calorific value Qn d of RDF samples Thermal analysis of experimental RDF based on combustible components of the MSW showed that the temperature of the drying agent should be such as to prevent overheating of the material above the temperature of its complete dehydration during convective drying. This measure will prevent ignition of RDF in the dryer. The following conclusions can be drawn from the results of experimental studies: 1. The thermal decomposition of RDF was investigated using thermal analysis methods in the range of 20–1000°С. Temperatures characterizing different stages of destruction, moisture and ash content of samples, rate of thermal decomposition of organic substances, conditional thermal effect and calorific value were determined. 2. It was established that the high polyethylene content in RDF leads not only to a high calorific va lue of the fuel, but also to a powerful release of volatile thermal decomposition products. This improves combustion kinetics. Polyethylene terephthalate also intensively emits gaseous products during thermal decomposition. However, increasing the polyethylene terephthalate content reduces the calorific value of the fuel due to its significantly lower calorific value compared to polyethylene. Therefore, it is better to send PET products to recycling as much as possible at the stage of waste sorting. 3. Destruction of cardboard does not cause emissions of harmful compounds. However, it should be taken into account that a high content of cardboard causes an increased ash content of the fuel. It was established that the ash content can vary in the range of 1.8–16% DM for different samples of paper and cardboard. In addition, it is necessary to take into account the presence of chalk in them. Because the decomposition of chalk requires additional energy at sufficiently high temperatures. Based on the obtained data, it is possible to recommend the presented compositions RDF A and F, which satisfy the conditions set for fuel, as well as RDF B, D and E while ensuring the neutralization of harmful emissions. 102 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 3 Conclusions 1. Analysis of technological stages of RDF production shows that all stages of production are energy consuming. The consumption is especially large for drying processes. They account for about 40–50% of total energy consumption. The consumption increases up to 70% in cases of drying MSW with high moisture content. Increasing the calorific value of composite fuel based on MSW requires combining components whose thermal properties have not been sufficiently studied. RDF combustion also requires knowledge of the kinetics of thermal decomposition and heat generation. 2. The kinetics of convective drying of RDF of different compositions was studied depending on the temperature (80–120°С) and the rate of the heat carrier (1.5–2.5 m/s). The drying time is reduced by 56%, and the maximum drying rate increases by 1.82 times when the heat carrier temperature increases from 80 to 120°С. Increasing the rate of the heat carrier from 1.5 to 2.5 m/s reduces the drying time by 38% at a temperature of the heat carrier of 120°С. The drying time increases by 28% when the RDF composition changes from the content of polymer materials (31–50%) to the content of paper and cardboard (31–50%). 3. The study of heat and mass transfer during drying of fuels, in particular the temperature coefficient, Rebinder number and heat flow, depending on the moisture content of fuels at constant temperatures, showed the feasibility of drying at higher temperatures. 4. RDF was studied in the range of 20–1000°С using thermogravimetry and differential thermal analysis methods. It is shown that the thermal decomposition of organic substances is staged in RDF. The stages differ in both temperature ranges and decomposition rates. 5. Based on the obtained data, it is possible to recommend the compositions RDF A and F, which satisfy the conditions set for fuel, as well as RDF B, D and E while ensuring the neutralization of harmful emissions. 6. It would be rational to have the maximum amount of polymers, especially polyethylene, in the fuel based on the calorific value and kinetics of thermal decomposition of experimental RDF. However, in practice, the polymer content in the fuel will be determined by the air emission treatment system of a particular energy enterprise. References 1. Daskalopoulos, E., Badr, O., Probert, S. D. (1997). Economic and Environmental Evaluations of Waste Treatment and Disposal Technologies for Municipal Solid Waste. 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Scientific Works of National University of Food Technologies, 26 (3), 137–146. https://doi.org/10.24263/2225-2924-2020-26-3-16 23. Paziuk, V. M., Petrova, Zh. O., Tokarchuk, O. A., Polievoda, Yu. (2021). Special aspects of soybean drying with high seedling vigor. University. Pjlstehnica of Buharest Scientific Bulletin, Series D, 83 (2), 327–336. 24. Li, X., Ma, B., Xu, L., Hu, Z., Wang, X. (2006). Thermogravimetric analysis of the co-combustion of the blends with high ash coal and waste tyres. Thermochimica Acta, 441 (1), 79–83. https://doi.org/10.1016/j.tca.2005.11.044 25. Kaniowski, W., Taler, J., Wang, X., Kalemba-Rec, I., Gajek, M., Mlonka-M ę drala, A. et al. (2022). Investigation of biomass, RDF and coal ash-related problems: Impact on metallic heat exchanger surfaces of boilers. Fuel, 326, 125122. https://doi.org/10.1016/j.fuel. 2022.125122 26. Sever Akda ğ , A., Atimtay, A., Sanin, F. D. (2016). Comparison of fuel value and combustion characteristics of two different RDF samples. Waste Management, 47, 217–224. https:// doi.org/10.1016/j.wasman.2015.08.037 27. Gug, J., Cacciola, D., Sobkowicz, M. J. (2015). Processing and properties of a solid energy fuel from municipal solid waste (MSW) and recycled plastics. Waste Management, 35, 283–292. https://doi.org/10.1016/j.wasman.2014.09.031 28. DSTU ISO 1928:2006. (2008). Solid mineral fuels. Determination of the highest heat of combustion by the method of combustion in a calorimetric bomb and calculation of the lowest 105 chapter 3. Improvement of the method of linear-quadratic control of azimuthal drivers of the combined propulsion complex CHAPTER 3 heat of combustion (ISO 1928:1995, IDT). To replace GOST 147-95 (ISO 1928-76). Kyiv: Derzhspozhivstandard of Ukraine, 40. 29. EN ISO 21654:2021. (2021). Solid recovered fuels – Determination of calorific value. Replaces EN 15400:2011. 30. Skliarenko, E., Vorobiov, L. (2023). Technique for determining the heat of combustion in the production of fuel from solid municipal waste with preferred characteristics. SWorldJournal, 1 (20-01), 11–20. https://doi.org/10.30888/2663-5712.2023-20-01-008 112 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 4 4.1.2.1 Disadvantages of modern wind power plants Along with the obvious advantages of wind power plants (autonomy, available energy resource, etc.), one cannot fail to note the characteristic disadvantages [14]: 1. Instability and wind dependence. It is impossible to accurately predict how much electricity will be received in a certain period of time, and in the absence of wind, energy production will completely cease. 2. High construction cost. Installation of a plant capable of producing 1 MW of electricity is more than 1 million USD. 3. Interference with radio communications and telecommunications. The operation of wind power plants causes signal distortion. 4. Change in the natural landscape. 5. Large area required to install an entire generator unit. 6. Danger to living creatures. The blades of turbines that constantly rotate pose a potential threat to certain species of living organisms, in particular, birds. For example, according to statistics, such turbines are the cause of the death of about 5 birds per year. 7. Noise pollution (up to 50 decibels at a distance more than 1 km). The noise created by «windmills» causes concern not only for wildlife, but also for people living near such structures. 8. The emergence of dangerous infrasound with a frequency of 6–7 Hz, which causes vibration. 9. Low energy output. Wind generators are much smaller in rank than other sources of electricity. Wind turbines are inefficient at high loads. 4.1.3 Solar energy Solar energy is one of the new types of energy production based on renewable sources, in particular, solar energy. The main goal is to convert solar radiation into other technological types of energy. In Ukraine, as of the end of the first half of 2021, the total installed capacity of solar power plants (SPPs) is 7284 MW, including: – 6,351 MW – solar power plants; – 933 MW – household SPPs. The main determining factors in the use of solar energy are the intensity of solar radiation (Fig. 4.4) and the duration of sunshine hours (Fig. 4.5). Solar radiation intensity is the power of the Sun’s radiation per unit surface area, measured in watts per square meter (W/m2). To calculate the amount of solar radiation that is converted into thermal energy, it is also necessary to take into account the duration of radiation (Fig. 4.5). The total energy of solar radiation is the power for a selected period of time, measured as watt-hours (W·h). The period can be taken as: day, month, year, etc. 113 chapter 4. Intelligentization of control systems for local electric power systems CHAPTER 4  Fig. 4.4 Solar energy potential in Ukraine Average annual solar radiation < 1000 kWh/m21400 kWh/m2 Donetsk Mykolaiv Kyiv Cherkasy Poltava Kropyvnytskyi Dnipro Kharkiv Chernihiv Sumy Lviv Uzhhorod Chernivtsi Lutsk Rivne Zhytomyr Vinnytsia Khmelnytskyi Ivano-Frankivsk Ternopil Odesa Kherson Simferopol Sevastopil Zaporizhzhia Luhansk Source: [15]  Fig. 4.5 Duration of sunshine hours 1600 1800 2000 2200 2400 up to over3800 4200 4600 5000 Number of hours of sunshine per year Total annual solar radiation (MJ/m) under average cloud conditions 2400 2200 4200 2000 3800 4200 1800 1800 1800 1800 1600 1600 1600 1600 2000 4600 2400 5000 Donetsk Mykolaiv Kyiv Cherkasy Poltava Kropyvnytskyi Dnipro Kharkiv Chernihiv Sumy Lviv Uzhhorod Chernivtsi Lutsk Rivne Zhytomyr Vinnytsia Khmelnytskyi Ivano-Frankivsk Ternopil Odesa Kherson Simferopol Sevastopil Zaporizhzhia Luhansk Source: [16] 114 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 4 The maximum daily total solar radiation in Ukraine is about 8 kWh/m2 in the summer. Sometimes on a sunny winter day, the total solar radiation can reach a value of up to 3 kWh/m2. The total average annual solar radiation in the territory of Ukraine, according to long-term observations, varies from 1,000 kWh/(m2) in the northern and central parts of the country to 1,350 kWh/(m2) in the Crimean Peninsula and the southern part of the Odesa region. For the convenience of analysis, these calculations were divided into 4 zones. All southern regions of Ukraine are located in the first and second zones; more than half of the country’s territory is located in the third zone, the fourth zone is the least favorable for the use of solar energy. The highest value of solar radiation in the first zone is 1350 kWh/km2 per year, and the lowest is in the fourth zone 1000 kWh/km2 per year. In the second and third zones, these values are, respectively, 1250 kWh/km2 and 1150 kWh/km2 per year. In general, the territory of Ukraine belongs to the zone of medium solar intensity. The average monthly level of solar radiation for Ukrainian cities is given in Table 4.3 [17].  Table 4.3 Average monthly level of solar radiation (solar constant) in Ukrainian cities (kWh/m2/day). Average over the last 22 years Regions / Months January February March April May June July August September October November December Average 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Simferopol 1.27 2.06 3.05 4.30 5.44 5.84 6.20 5.34 4.07 2.67 1.55 1.07 3.58 Vinnytsia 1.07 1.89 2.94 3.92 5.19 5.3 5.16 4.68 3.21 1.97 1.10 0.9 3.11 Lutsk 1.02 1.77 2.83 3.91 5.05 5.08 4.94 4.55 3.01 1.83 1.05 0.79 2.99 Dnipro 1.21 1.99 2.98 4.05 5.55 5.57 5.70 5.08 3.66 2.27 1.20 0.96 3.36 Donetsk 1.21 1.99 2.94 4.04 5.48 5.55 5.66 5.09 3.67 2.24 1.23 0.96 3.34 Zhytomyr 1.01 1.82 2.87 3.88 5.16 5.19 5.04 4.66 3.06 1.87 1.04 0.83 3.04 Uzhhorod 1.13 1.91 3.01 4.03 5.01 5.31 5.25 4.82 3.33 2.02 1.19 0.88 3.16 Zaporizhzhia 1.21 2.00 2.91 4.20 5.62 5.72 5.88 5.18 3.87 2.44 1.25 0.95 3.44 Ivano-Frankivsk 1.19 1.93 2.84 3.68 4.54 4.75 4.76 4.40 3.06 2.00 1.20 0.94 2.94 Kyiv 1.07 1.87 2.95 3.96 5.25 5.22 5.25 4.67 3.12 1.94 1.02 0.86 3.10 Kropyvnytskyi 1.20 1.95 2.96 4.07 5.47 5.49 5.57 4.92 3.57 2.24 1.14 0.96 3.30 Luhansk 1.23 2.06 3.05 4.05 5.46 5.57 5.65 4.99 3.62 2.23 1.26 0.93 3.34 Lviv 1.08 1.83 2.82 3.78 4.67 4.83 4.83 4.45 3.00 1.85 1.06 0.83 2.92 Mykolaiv 1.25 2.10 3.07 4.38 5.65 5.85 6.03 5.34 3.93 2.52 1.36 1.04 3.55 Odesa 1.25 2.11 3.08 4.38 5.65 5.85 6.04 5.33 3.93 2.52 1.36 1.04 3.55 115 chapter 4. Intelligentization of control systems for local electric power systems CHAPTER 4  Continuation of Table 4.3 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Poltava 1.18 1.96 3.05 4.00 5.40 5.44 5.51 4.87 3.42 2.11 1.15 0.91 3.25 Rivne 1.01 1.81 2.83 3.87 5.08 5.17 4.98 4.58 3.02 1.87 1.04 0.81 3.01 Sumy 1.13 1.93 3.05 3.98 5.27 5.32 5.38 4.67 3.19 1.98 1.10 0.86 3.16 Ternopil 1.09 1.86 2.85 3.85 4.84 5.00 4.93 4.51 3.08 1.91 1.09 0.85 2.99 Kharkiv 1.19 2.02 3.05 3.92 5.38 5.46 5.56 4.88 3.49 2.10 1.19 0.9 3.26 Kherson 1.30 2.13 3.08 4.36 5.68 5.76 6.00 5.29 4.00 2.57 1.36 1.04 3.55 Khmelnytskyi 1.09 1.86 2.87 3.85 5.08 5.21 5.04 4.58 3.14 1.98 1.10 0.87 3.06 Cherkasy 1.15 1.91 2.94 3.99 5.44 5.46 5.54 4.87 3.40 2.13 1.09 0.91 3.24 Chernihiv 0.99 1.80 2.92 3.96 5.17 5.19 5.12 4.54 3.00 1.86 0.98 0.75 3.03 Chernivtsi 1.19 1.93 2.84 3.68 4.54 4.75 4.76 4.40 3.06 2.00 1.20 0.94 2.94 Note: according to NASA In most cases, the average annual solar radiation intensity level of 11–12 kWh/m2 is sufficient for the construction of a solar power plant to be economically feasible. Based on the intensity of solar radiation, which is the main factor determining the power of a photovoltaic cell, the SPP parameters are calculated. The electrical power (N, W) for a solar power plant with photovoltaic cells is determined by the formula [18] N=ηPV·FPV·I, (4.1) where ηPV – efficiency of photovoltaic converters (0.12–0.17); FPV – total area, m2; I – solar radiation intensity, W/m2. 4.1.3.1 Disadvantages of solar energy The existing advantages of solar energy (silence, autonomy, available energy resource, etc.) are reduced by significant disadvantages. Intermittent cycle. Dependence on weather and time of day. Energy can only be generated during the day in clear weather. In adverse weather conditions (cloudy weather), solar panels simply do not work, which leads to a sharp reduction in the production of electricity by SPPs. Low power per square meter. One of the most important parameters of electricity is the average power density per square meter (m2), which is measured in W/m2 and the amount of energy that can be obtained from a unit of area. For solar energy, this figure is on average 170 W/m2, this value is greater than for all used renewable energy sources, but compared to traditional energy 116 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 4 sources (oil, coal, gas, nuclear energy), this figure is much lower. Which leads to an increase in the area of solar panels for the production of 1 kW of energy. Impact on the ecosystem. Solar vacuum power plants are equipped with mirrors with precise focus. If a bird falls into the focus of the mirrors, it dies instantly. According to some sources, one bird dies every two minutes above large solar installations. Environmental pollution. Solar energy as a source is the most environmentally friendly type of energy. But for its production it is necessary to produce solar panels, during the production and utilization of which greenhouse gases are emitted into the atmosphere, and chemical compounds containing: lead, cadmium, gallium, arsenic, etc. [18], which are dangerous for the environment and humans. 4.1.4 Bioenergy Bioenergy is a branch of the global energy industry based on the production and use of biofuels based on the use of biomass, including the following technologies: direct combustion and pyrolysis of wood fuel and solid household waste; biogas technologies; production of liquid biofuels for vehicles. Biomass is biologically renewable substances of organic origin that undergo biological decomposition (wastes from agriculture (crop and livestock farming), forestry and technologically related industries, as well as the organic part of industrial and household waste). The main sources of biomass for use in energy purposes can be divided into primary and secondary (waste). Primary sources are biomass of trees, shrubs, some perennial grasses, algae. For these purposes, special “energy plantations” of fast-growing crops in natural conditions such as willow, poplar, reed, corn, oats, sorghum and others are created for their direct use as biofuel in power plants of thermal power plants, in boiler rooms, etc. Secondary sources include: – waste from the forestry, woodworking and pulp and paper industries, agricultural waste – residues of primary biomass (straw, husks of grain crops, oilseed cake) and waste from livestock and poultry farming (manure, litter); – industrial liquid waste from industrial production (food industry, sugar industry, winemaking, etc.); – municipal waste from urban treatment plants and landfills. Depending on the sources and properties of organic raw materials, various technologies for its transformation and energy use are possible. The simplest classification divides the initial raw materials into “dry” (for example, wood waste) and “wet” (for example, livestock farm effluents). For the use of dry biomass, thermochemical technologies (direct combustion, gasification, pyrolysis) are most effective. For wet biomass, biochemical processing technologies with the production of biogas (anaerobic decomposition of organic raw materials) or liquid biofuels (alcoholic fermentation processes, etc.) are used. 117 chapter 4. Intelligentization of control systems for local electric power systems CHAPTER 4 Solid fuels include: firewood and their new modifications: fuel granules and briquettes, including pellets, which are pressed products from wood waste (sawdust, chips, bark, substandard wood, logging residues), straw, agricultural waste (sunflower husks, nut shells, manure), etc. As a result of the application of modern thermochemical and biotechnologies, the energy stored in biomass is converted into biofuel, heat and electricity. The most common types of biomass used as raw materials for obtaining fuel and using it to produce electricity or heat include: – straw, corn stalks, sunflower; husks and other waste from processing sunflower, grain and other agricultural crops, etc. (in the processing process, granules (pellets), briquettes are obtained); – annual and perennial plant biomass, energy plants (energy willow, sorghum, miscanthus, millet, etc.); – wood, its waste and products of its processing (in the processing process, granules, pellets, briquettes are obtained); – livestock and poultry waste; – vegetable crop waste and their processing; – plant waste from the food industry, peat; – fruit biomass, etc. For energy production, solid biomass is used, as well as liquid and gaseous fuels obtained from it: biogas, biodiesel, bioethanol [19]. Biomass can also be used for energy purposes by direct combustion (wood, straw, sewage sludge), as well as in the processed form of liquid (rapeseed oil esters, alcohols, liquid pyrolysis products) or gaseous biofuels (biogas from agricultural and crop waste, sewage sludge, solid household waste, gasification products of solid fuels) (Fig. 4.6). Renewable energy production is rapidly developing in most European countries and the USA. The annual growth of biomass in the world is estimated at 200 billion tons in terms of dry matter, which is energy equivalent to 80 billion tons of oil. During 2021, 992 million kWh of “green” electricity was produced in Ukraine from biomass and biogas, which is 7.7% of the total electricity production from renewable sources in 2021 [20]. According to the Ministry of Energy, bioenergy in Ukraine as of 2021 operated with a total capacity of 275.9 MW [20]. The steady trend of increasing biomass energy production observed in Ukraine indicates its desire to comply with global trends in the development of alternative energy. In terms of resources, the presence in the country of powerful agricultural and forestry enterprises, with a favorable climate and large areas of free land suitable for traditional agricultural production creates all the necessary prerequisites for an increase in the share of biofuels produced from biomass. The agrarian orientation of the economy of our state determines the state’s special interest in the priority development of the bioenergy complex, the foundation of which will be built in agriculture. Over the past 20 years, the supply of primary energy from biomass and biofuels in the world has increased by 118 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 4 a third and is about 11% of the total primary energy supply (TPES), or almost 70% of TPES from renewable sources. The supply of primary energy from biofuels and waste reached 4.241 million tons of oil equivalent in 2020, which replaces about 5.2 billion m3 of natural gas (Fig. 4.7) [21].  Fig. 4.6 Methods of energy production from biomass Livestock waste, organic fraction Plant residues and waste Energy plantations Plants with sugar, starch content Oil crops Anaerobic fermentation Gasification Pyrolysis Granulation Combustion Leaching, fermentation of sugars Fuel from vegetable oils Pressing Gas Liquid fuel Solid fuel Heat, electrical energy, mechanical work Alcohol fuel Source: [19]  Fig. 4.7 Primary energy supply from biofuels 4500 4000 3500 3000 2500 2000 1500 1500 1000 500 0 1458 1476 1580 1563 1565 1522 1923 1875 2399 1934 2606 2102 3348 2832 3575 2989 3726 3209 3786 3349 4438 4241 Energy supply from biofuels thnd tons o.e./year Average annual growth rate of bioenergy in Ukraine is 11 % Year Biofuel production 2010 20122011 2013 2014 20162015 2017 20192018 2020 Ukraine has a large potential of biomass available for energy production, which is a good prerequisite for the dynamic development of the bioenergy sector. The economically feasible energy % 119 chapter 4. Intelligentization of control systems for local electric power systems CHAPTER 4 potential of biomass in the country is about 20–25 MTOE per year. The main components of the potential are agricultural waste (straw, corn stalks, sunflower stalks, etc.) – more than 11 MTOE per year (according to 2015 data) and energy crops – about 10 MTOE per year. At the same time, agricultural waste is a real part of the biomass potential, and data on energy crops reflect the amount of biomass that can be obtained by growing these crops on free land in Ukraine. It should be noted that this process has been actively developing in the last few years. Every year in Ukraine, about 2 million tons of biomass of various types are used for energy production. Wood accounts for the highest percentage of use of economically feasible potential – 80%, while for other types of biomass (except for sunflower husks) this figure is an order of magnitude lower. The least actively (at the level of 1%) is the energy potential of straw of grain crops and rapeseed (Table 4.4) [22].  Table 4.4 Energy potential of biomass in Ukraine Biomass type Theoretical potential, million tons Part available for energy production, % Economic potential, MTOE Cereal straw 32.8 30 3.36 Rapeseed straw 4.9 40 0.68 By-products of corn production (stalks, cobs) 46.5 40 3.56 By-products of sunflower production (stalks, baskets) 26.9 40 1.54 Secondary agricultural residues (sunflower husks) 2.4 100 1.00 Wood biomass (fuel wood, logging residues, wood processing waste) 8.8 96 2.06 Wood biomass (deadwood, wood from protective forest belts, waste from pruning and uprooting of perennial agricultural plantations) 8.8 45 1.02 Biodiesel (from rapeseed) – – 0.39 Bioethanol (from corn and sugar beets) – – 0.82 Biogas from waste and by-products of the agricultural and industrial complex 2.8 billion m3 СН442 0.99 Biogas from solid waste landfills 0.6 billion m3 СН429 0.14 Biogas from wastewater (industrial and municipal) 0.4 billion m3 СН428 0.09 Energy plants: – willow, poplar, miscanthus 11.5 billion m3 СН4100 4.88 – corn (for biogas) 3.0 billion m3 СН4100 2.57 Peat – – 0.40 Total – – 23.10 Source: [22] 120 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 4 The potential for “total primary energy supply from biofuels and waste” by 2050 is given in Table 4.5 [22].  Table 4.5 Summary indicators of the Roadmap for the development of bioenergy in Ukraine by 2050 Year Installed capacity Biofuel consumption*, MTOE Natural gas displacement, billion m3 Gasoline and diesel displacement, million tons CO2 emissions reduction, million tons per year MWt MWel 2020 8,206 202 3.77 4.34 0.17 8.90 2025 12,276 844 5.83 6.35 0.25 14.31 2030 19,087 1,846 8.57 9.11 0.39 21.35 2035 30,237 2,804 12.01 12.62 0.50 30.37 2040 39,338 3,609 15.13 15.77 0.67 38.66 2045 45,351 4,299 17.64 17.98 0.96 45.79 2050 49,655 5,230 20.28 19.92 1.23 54.40 Source: [22] 4.1.4.1 Advantages and disadvantages of bioenergy The main advantages of bioenergy [23] are the utilization of organic waste, reducing environmental pollution. Biofuels are made from various raw materials, such as manure, crop waste and plants grown specifically for fuel. These are renewable resources that are unlikely to run out in the near future. Biofuels reduce greenhouse gas emissions. In addition, when growing crops for biofuels, they partially absorb carbon monoxide, which makes the biofuel system even more sustainable. Biofuels are quite easy to transport, they have stability and a fairly high “energy density”, they can be used with minor modifications to existing technologies and infrastructure. The disadvantages of biofuels [23] include: – limitations in regional suitability (in some areas it is simply impossible to grow biofuel crops, for example in areas with a cold or arid climate); – water use – the less water used to grow crops, the better, as water is a limited resource; – food security (too much biofuels can lead to famine). The problem with growing crops for fuel is that they will take up land that could be used to grow food; – destruction of animal habitats and the risk of environmental change due to the use of fertilizers and pesticides when growing biofuel crops (most often monocultures for ease of cultivation). 121 chapter 4. Intelligentization of control systems for local electric power systems CHAPTER 4 4.1.5 Thermal power The main part of the electricity in the world as of the end of 2021 is produced at thermal power plants (TPPs). This is followed by hydroelectric power plants (HPPs) and nuclear power plants (NPPs) (Table 4.1) [1]. Thermal power plants. Coal, black oil, gas, and oil shale are usually used as fuel for thermal power plants. Fossil fuels are non-renewable resources. According to many estimates, coal on the planet will last for 100–300 years, oil for 40–80 years, and natural gas for 50–120 years. It is known that thermal power plants are decisive in water and oxygen consumption, as well as in thermal pollution. A typical TPP with a capacity of 2 million kW consumes 18,000 tons of coal, 2,500 tons of black oil, and 150,000 m3 of water daily. 7 million m3 of water are used daily to cool the exhaust steam at thermal power plants, which leads to thermal pollution of the cooling reservoir. The following are emitted with the products of fuel combustion (of the total amount): ~30% of solid aerosol particles, ~60% of sulfur oxides (SO2) and nitrogen oxides (NOX), as well as the main share of CO2 as a determining factor in the greenhouse effect, which leads to climate warming. The impact of the energy sector on the environment strongly depends on the type of fuel used. The most “clean” fuel is natural gas, which produces the least amount of substances that pollute the atmosphere when burned. This is followed by oil (black oil), hard coal, brown coal, shale, peat. As mentioned above, many by-products are formed during the combustion of fuel. When burning coal, a significant amount of ash and slag is formed. Most of the ash can be captured, but not all. All exhaust gases are potentially harmful, even water vapor and carbon dioxide CO2. These gases absorb infrared radiation from the Earth’s surface, and some of it is reflected back to the Earth, creating the so-called “greenhouse effect”. If the level of CO2 concentration in the Earth’s atmosphere increases, global climate change may occur. When fuel is burned, heat is generated, some of which is released into the air, leading to thermal pollution of the atmosphere. This, ultimately, entails an increase in the temperature of water and air basins, melting glaciers, etc. This, ultimately, causes an increase in the temperature of water and air basins, melting glaciers, and similar phenomena. In turn, an increase in temperature can cause profound climate changes throughout the Earth. The effect of a large number of solid particles entering the atmosphere can be equally catastrophic. Tables 4.6, 4.7 provide quantitative data on various substances formed during the operation of a typical 1000 MW thermal power plant using organic fuel [24].  Table 4.6 Emissions of pollutants during the operation of a 1000 MW thermal power plant Contaminant SОx, t NxOx, t СО2, t СО, t Solid particles, t Radioactivity*, Bq Flue gases, GJ Heat of condensation, GJ Per year 1 100 350 72 500 94 300 259 1 350 4 050 Note: *Radioactivity is mainly caused by the radium isotopes 235Ra and 238Ra. Data are given for coal. For oil, this figure is 50 times lower 128 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 4 The use of wind, also due to the insufficient density of the energy flow, turns out to be economically insufficiently justified. Sources with high energy density – fuel cells – are characterized by a low rate of its transmission, so the real energy consumption does not exceed 200 W/m2. In addition, it is worth considering such an indicator as the installed capacity utilization factor (ICUF). It indicates the efficiency of the operation of electric power enterprises. It is calculated as the ratio of the arithmetic average capacity to the installed capacity of the electric power plant for a certain time interval [50]. Thus, if there are two power plants – nuclear and solar, with the same nominal capacity (720,000 MWh/month), the solar power plant will produce only 15–30% of this value, since it directly depends on the sun. This indicator will be its ICUF. Taking into account the above, there is a need to introduce the “General indicator for the selection and development of energy production taking into account the environmental component” of the Paris Agreement [51]. 4.2.1 Comprehensive assessment of efficiency indicators of energy resources Analysis of the distribution and use of energy resources convincingly shows that energy production traditionally follows the availability of resources in the region and the need for energy. In this regard, an uneven concentration of industry and its accompanying environmental impact are created. To level the situation, it is necessary to have indicators that allow a comprehensive assessment of the possibilities of regions for the development of the economic sector, taking into account the availability of resources and minimal environmental impact. In order to justify the choice of the preferred type of energy resource, using the example of the energy supply of the region (Odesa), the “Method of expert assessments of the use of energy resources (system efficiency)” was formed. The most common energy resources are divided into two main categories: fossil and non-fossil [52] (Table 4.15). Fossil resources are represented by hydrocarbons in various phase states. Non-fossil resources, in turn, consist of renewable and manufactured resources.  Table 4.15 Main categories of energy resources Fossil Non-fossil Renewable Manufactured Coal, peat Oil Gas Solar Wind Hydropower Biogas Household waste Hydrogen Nuclear 129 chapter 4. Intelligentization of control systems for local electric power systems CHAPTER 4 Fossil fuels – coal, natural gas and oil are the main sources of primary energy for thermal energy (thermal power). In Ukraine, about 30% of all electricity [53] is provided by thermal power. It works both on its own and on imported raw materials. The operation of thermal power plants is accompanied by emissions of many greenhouse gases, the main of which are water vapor and carbon dioxide, which are formed during the combustion of all types of hydrocarbon fuels. The products of coal combustion and anthropogenic emissions of carbon dioxide accumulate in the atmosphere, contributing to the development of the greenhouse effect. The annual emission of CO2 by all TPPs in the world is approaching 10 billion tons of carbon dioxide, accounting for about 30% of all anthropogenic emissions of greenhouse gases into the atmosphere of the planet [54]. An important element of the study is the establishment of a comprehensive assessment of the efficiency indicators of the choice of the type of energy resource, favorable for electricity and heat supply in the conditions of a specific region. To conduct such an assessment, the method of expert assessments [55] was used using a random number generator to form an information field about the values of the characteristics of energy resources and statistical processing of data on acceptable energy resources in the conditions of the regions under consideration. The developed methodology was applied to analyze and form a number of preferences by type of energy resources of the large southern region of Ukraine – Odesa region. The aim of the presented methodology is to form a comprehensive assessment of the degree of efficiency of electricity generation and pollution of the territories of energy production facilities based on the analysis of the values of the observed environmental indicators. The methodology proposes two mutually complementary criteria, the resource preference index and the environmental preservation index, which evaluate a number of preferences of energy resources from the standpoint of accessibility and impact on the environment of a particular region. To achieve the formulated aim, it is necessary to solve the following tasks: – forming a list of observed indicators; – forming limit or normalizing values of the observed indicators; – consistent normalization according to permissible values, amounts of resources under consideration, and observed indicators. The existing global trend provides for the preferential development of the use of non-fossil resources [56]. Each of the types of energy resources specified in (Table 4.15) is characterized by qualities, the totality of which in dimensionless form can be a criterion for making a decision on the preferential acceptability of using a particular resource. The algorithm for constructing a comprehensive assessment of the efficiency of the system is the sequence of procedures is presented in Table 4.16 [57]. 130 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 4  Table 4.16 Algorithm for constructing a comprehensive assessment of the efficiency of systems Stage Procedure Stage 1 Selection of a set of indicators characterizing the state of systems Stage 2 Selection of reference systems by indicators Stage 3 Assessment of intervals of partial indicators of system functioning Stage 4 Average point estimate of values of temporary indicators of system functioning Stage 5 Assessment of weighting coefficients for temporary indicators Stage 6 Integral assessment of system functioning efficiency Factors reflecting the applicability of the resource formed 6 groups, which include 27 indicators that have a positive (+) or negative (–) trend of change [57] (Table 4.17).  Table 4.17 Factors reflecting the applicability of the resource No. Group Indicators 1 2 3 1 TECHNOLOGICAL FACTORS are variables related to the existence, availability and development of technology 1 + Availability of the resource in the region 2 – Need to import resources 3 + Availability of delivery transport 4 + Availability, readiness 5 + Productivity 6 + Quality of the resources supplied 7 + Final carbon intensity of energy 2 ENVIRONMENTAL FACTORS are variables that are caused by the interaction of resources and the environment 8 – Volume of waste 9 – Level of emissions in general 10 – Level of CO2 emissions per TPES 11 + Waste recycling 12 – Waste disposal 13 + Safety of maintenance 3 RELIABILITY FACTORS are caused by the quality of service, the interaction of the system and the environment (technical, software, operational) 14 + Reliability, failure 15 + Repairability 16 + Duration of operation 17 + Level of renewal of fixed assets 18 + Support of the life cycle of objects 131 chapter 4. Intelligentization of control systems for local electric power systems CHAPTER 4  Continuation of Table 4.17 1 2 3 4 WEIGHT FACTORS are used to assess the need for space for implementation 19 – Capital investments 20 – Dimensions 21 – Material intensity 5 TECHNICAL FACTORS include the need for resources for their own needs 22 – Own energy consumption 23 – Consumption of reagents 24 + Possibility of utilization 6 INSTITUTIONAL FACTORS are related to management, regulation 25 + Level of remuneration 26 + Quality of management 27 + Quality of personnel 4.2.1.1 Analysis of existing comprehensive assessments The comprehensive approach is based on the formation of groups of indicators that reflect individual aspects of the state of the system. Siemens Corporation, together with the Economist Intelligence Unit, developed an expert methodology for a comprehensive assessment of cities, which includes eight groups of indicators: 1) greenhouse gas emissions; 2) energy consumption; 3) urban management; 4) transport; 5) water use; 6) waste and land use; 7) air quality; 8) environmental management, ensuring the reflection of all aspects of the functioning of the system. For comparison, all indicators are normalized in a dimensionless form. The overall index is constructed as a quantitative sum of all groups, taking into account the weight assignment [57]. Similar expert assessments by international organizations Mercer Human Resource Consulting and The Blacksmith Institute [58] are also known in urban planning. Other indices for assessing the state of cities are constructed in a similar way. For example, in the ecological safety of cities, the atmospheric pollution index, the threshold mass index of hazardous substances, the total hazard index of individual components polluting a particular biogeochemical environment (water, air and soil), etc. are used. Indicators are estimated using the normalization of indicators. If the change intervals are known, the ratio is used for normalization 132 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 4 I pp pp i iimin imax imin =   , ,, , (4.2) where pi – the value of the i-th indicator for a certain object; pi min, pi max – respectively, the minimum and maximum value of this indicator in the group of objects under study; Ii – the corresponding indicator. When assessing surface water pollution, the water pollution index is often used IC MPC pw i i i    1 61 6, (4.3) where Ci – the values of the observed indicators; MPCi – the maximum permissible concentrations of pollutants in water. Integral indicators for assessment are determined by the relationship [59] Ia I ii i m    1 , (4.4) where Ii – indicators in the form of values of indicators that are normalized; аi – weighting factors. It seems effective to supplement relative indices with multi-stage normalization, which is used in [59]. Based on expert assessments, a reliable complex indicator for comparing the ecological load of the environment was obtained. 4.2.1.2 Environmental pollution indicators and their standardization The methodology presented below differs from that used in [57] by replacing expert assessments with monitoring control data or project documentation. To assess the pollution of territories, 6 groups were used, which contain 33 indicators (Table 4.18). The technological group concentrates indicators that characterize the capabilities and needs of the analyzed systems. The environmental group includes a list of all possible undesirable impurities and their emission levels. The third group combines system reliability indicators. Other groups concentrate indicators of the general characteristics of the systems. All available limit indicators are used as standardizing parameters: permissible limit values of the indicator (рmax; рmin), maximum permissible emissions (MPE) and maximum permissible concentrations (MPC). The current values of the indicators are taken according to operational monitoring data or project technical documentation of the systems. 133 chapter 4. Intelligentization of control systems for local electric power systems CHAPTER 4  Table 4.18 Groupings and types of pollution indicators No. Type No. Type 1 – Technological 19 51Cr 1 Productivity 20 Thorium 2 Energy consumption 21 Uranium 3 Water consumption as a reagent 22 Tritium into the atmosphere 4 Cooling water consumption 23 Suspensions 2 – Environmental (Emission level) 24 Tritium into the hydrosphere 5 Heat 25 Liquid waste 6 Water vapor 3 – Reliability 7 CO2 on TPES 26 Duration of operation 8 Carbon monoxide (CO) 27 Level of renewal of fixed assets 9 NOx28 Quality of resources supplied 10 SOx29 Security of service 11 Hydrocarbons (5–20%) 4 – Technical 12 Inert radioactive gases 30 Own energy consumption 13 131I5 – Institutional 14 137Cs 31 Level of management 15 60Со 6 –Dimensions 16 90Sr 32 Area occupied by the object 17 89Sr 33 Territory of the region 18 54Mn – – 4.2.1.3 Combined normalization of resource efficiency and environmental pollution indicators Normalization of current indicator values is performed in several stages. The primary normalization of current indicator values was performed according to relations (4.2)–(4.4). If data on MPC were available, normalization was performed according to the relation IC MPC i i i =, (4.5) where Ci – the current values of the i-th indicator; MPCi – the MPC value of the i-th indicator. 134 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 4 After the primary normalization, the individual indicator values are normalized by their sums for the systems being compared. The obtained normalized indicator values are summed for each system and the obtained sums are normalized by their total sum. 4.2.2 Results of polluting capacity assessment Comparison of the polluting capacity of power plants using fossil resources, carried out according to the presented algorithm, confirmed the distribution of the latter by the degree of saturation of the environment with undesirable impurities (Fig. 4.8).  Fig. 4.8 Environmental pollution index by power plants depending on the energy resource Environmental pollution index by power plants NPP Coal Oil Gas 4.00E-01 3.50E-01 3.00E-01 2.50E-01 2.00E-01 1.50E-01 1.00E-01 5.00E-02 0.00E+00 It should be noted that the initial data are of the most general nature without reference to specific objects. The calculations adopted weighting factors in accordance with the recommendations [58, 60]. The results obtained are characterized by high stability, which indicates the stability of the methodology. The maximum permissible value of the environmental pollution index by power plants is determined according to the given normalization scheme for its own values and is therefore equal to 1. 4.2.3 Using a complex indicator for resource selection The environmental pollution index obtained according to the given methodology is a measure of the share of the maximum permissible relative pollution (Fig. 4.9). 135 chapter 4. Intelligentization of control systems for local electric power systems CHAPTER 4 The indicators of the environmental group, inherent in the nuclear resource and absent from the carbon group resources, neutralize the advantages of nuclear power plants with their quantity. The indicators of the technological group and part of the environmental group, which are inherent in all types of resources, have the predominant values. In the normalization process, the predicted pollution is reduced to unit productivity.  Fig. 4.9 Acceptability index values for energy resources 1.40 1.20 1.00 0.80 0.60 0.40 0.20 0.00 Acceptability index coal, peat oil gas solar wind hydropower biogas household waste hydrogen nuclear The lowest acceptability index values in the region under consideration are characteristic of traditional solid and liquid fossil resources, as well as for some resources made from waste and natural raw materials (0.8–0.9). Fossil gas and hydropower are characterized by an acceptability index slightly higher than 1. Renewable resources (solar and wind energy) are distinguished by a noticeably higher index value (about 1.2). The most promising resource for the region was the nuclear energy resource, which reached an acceptability value of 1.3. A comparison of the trends in the change in the acceptability index and the environmental protection index (Fig. 4.10) allows to note their synchronicity. At the same time, the module of the environmental protection index is slightly higher than the acceptability index for nuclear energy. The comparison made suggests that the acceptability of a particular energy resource for the region under consideration is largely regulated by the environmental characteristics of the resources. The reliability of the results obtained when using the expert assessment method can be assessed by the degree of consistency of expert positions regarding each indicator using the Kendall concordance coefficient [61] 136 PROCESSES AND CONTROL SYSTEMS: SYNTHESIS, MODELING, OPTIMIZATION CHAPTER 4 WS nmm     12 1 22 , where S – the sum of the squares of deviations of all estimates of the ranks of each object of expertise from the average value; n – the number of experts; m – the number of objects of expertise.  Fig. 4.10 The value of the environmental conservation index 1.60 1.40 1.20 1.00 0.80 0.60 0.40 0.20 0.00 Environmental conservation index coal, peat oil gas solar wind hydropower biogas household waste hydrogen nuclear The concordance coefficient (Fig. 4.11) varies in the range 0 < W < 1, with the value W = 0 indicating complete disagreement, and W = 1 indicating complete unanimity. For different indicators, the value of the concordance coefficient does not exceed 0.5. There is no specific trend in the change in the coefficient, which confirms the random nature of the data being analyzed. This allows to extend the obtained patterns proportionally to the distribution of electricity production by type of resources (Table 4.19).  Table 4.19 Electricity production and pollution by region and resource (%) Region NPP TPP Coal Oil Gas World 10.3/3.1 36.7/18.6 2.8/1 23.5/4.4 Ukraine 55/14.5 19.3/8.5 0.5/0.16 9.3/1.5 137 chapter 4. Intelligentization of control systems for local electric power systems CHAPTER 4  Fig. 4.11 Concordance coefficient 0.60 0.50 0.40 0.30 0.20 0.10 0.00 Concordance coefficient Availability of АER in the region Need to import resources Availability of delivery transport Availability, readiness Productivity Quality of resources supplied Final carbon intensity of energy Volume of waste Level of emissions in general Level of CO2 emissions per TPES Waste recycling Waste disposal Safety of maintenance Reliability Repairability Duration of operation Level of renewal of fixed assets Life cycle support Capital investments Dimensions Material intensity Own energy consumption Consumption of reagents Possibility of utilization Level of remuneration Quality of management Quality of personnel  Fig. 4.12 Environmental pollution index by power plants depending on the energy resource for electricity production in the world and Ukraine 0.2 0.16 0.12 0.08 0.04 0 World production NPP Coal Oil Gas In Ukraine The results obtained differ in absolute values of acceptability for different types of resources and different methods. At the same time, the trends of change by resource are preserved.