BULLETIN
OF PERM NATIONAL RESEARCH POLYTECHNIC UNIVERSITY ISSN (Print): 2224-9397 ISSN (Online): 2305-2767 | ||
ENERGY RECOVERY TRANSFORMATIONS IN URBAN ELECTRIC TRANSPORT A.V. Katsay, M.V. Shevlyugin Received: 27.08.2022 Received in revised form: 03.10.2022 Published: 22.12.2022 ![]() Abstract:
Improving the energy efficiency of passenger transportation by urban electric transport is one of the most important tasks in the activities of traffic services and energy services of GET enterprises. The widespread introduction of traction frequency converters on rolling stock made it possible to create conditions for the reuse of regenerative braking energy of electric rolling stock (EPS) for the performance of transport work. However, due to the impossibility of full synchronization of regenerative braking and traction load in the contact network, only part of the regenerative energy finds useful use. The other – excess part is dissipated on the brake resistors of the wagons. The use of buffer energy storage devices of various designs and installation methods allows for more complete use of excess energy recovery. The purpose of the study: to study the processes of energy conversion during the operation of stationary and on-board energy storage devices of various designs during the reception and delivery of energy from excessive recovery of braking EPS, to compare the efficiency of these energy storage devices during tests conducted in Russia in urban electric transport. Methods: structural analysis of electrical circuits of energy storage devices, comparative quantitative analysis of energy processes of operation of buffer energy storage devices of various types. Results: the processes of energy conversion during braking of rolling stock with recuperation into electrical energy for wagons with various types of traction control systems, as well as with the use of on-board and stationary energy storage devices of various types are considered. The calculation of the volumes of energy of regenerative braking of EPS returned to useful transport work for circuits with stationary and on-board, flywheel, supercapacitor and capacitive energy storage devices based on the actual data of their tests is carried out. As a result of the analysis, it was revealed that the preservation of inter-train flows of useful regenerative electricity generated during braking of rolling stock provides a more complete return of energy than in the case of elimination of such flows using onboard storage devices. It is also established that the maximum return of recovered energy is provided by stationary storage devices, and the total net return of recovery energy by onboard supercapacitor storage devices with the prohibition of inter-train exchange of regenerative energy is less than the inter-train flows of useful recovery in wagons not equipped with any buffer storage devices. Practical significance: the results of the research were used to calculate the efficiency of energy saving for performing transport work during tests in the tram contact network of a stationary energy storage device of the NKE-3G type. Also, the conclusions obtained in the course of the study can be used at GET enterprises to plan tasks for the use of buffer energy storage devices to reduce energy consumption for transport work. Keywords: Regenerative braking, recovery, energy conversion, energy storage, traction control system, contact network, traction power consumption, efficiency, traction substation, rolling stock. Authors:
Alexander V. Katsay (Moscow, Russian Federation) – Candidate of Philosophical Sciences, General Director of Kinemak LLC (115201, Moscow, 13, Kashirsky Proezd, e-mail: proton764@mail.ru). Maxim V. Shevlyugin (Moscow, Russian Federation) – Doctor of Technical Sciences, Associate Professor, Head of the Department "Electric Power Engineering of Transport" RUT (MIIT) (127994, Moscow, 9, Obraztsova str., p. 9, e-mail: mx_sh@mail.ru). References: 1. Biriukov V.V. Energosberezhenie na elektricheskom transporte [Energy saving in electric transport]. Irkutsk: Irkutskii gosudarstvennyi tekhnicheskii universitet, 2009, 244 p. 2. Rozenfel"d V.E., Isaev I.P., Sidorov N.N. Teoriia elektricheskoi tiagi [Theory of electric traction]. 3nd ed. Moscow: Transport, 1995, 294 p. 3. Efremov I.S., Kosarev G.V. Teoriia i raschet elektrooborudovaniia podvizhnogo sostava gorodskogo elektricheskogo transporta [Theory and calculation of electrical equipment of rolling stock of urban electric transport]. 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Sablin O.I. Povyshenie effektivnosti rekuperatsii energii v sisteme elektrotransporta pri ogranichennom tiagovom elektropotreblenii [Improving the efficiency of energy recovery in the electric transport system with limited traction power consumption]. Tekhnologicheskii audit i rezervy proizvodstva, 2014, vol. 6, no. 1 (20). pp. 21-25. NUMERICAL SIMULATION OF THE HEAT RESISTANCE TEST OF A CLOSED THREE-PHASE 10 kV BUS DUCT IN THE THREE-PHASE SHORT CIRCUIT SITUATION U.N. Abasheva, V.E. Frizen, S.L. Nazarov Received: 28.06.2022 Received in revised form: 18.10.2022 Published: 22.12.2022 ![]() Abstract:
In order to avoid the costs of repeated expensive qualification tests, to reduce the material consumption of the bus duct, it is advisable to perform numerical modeling of thermal and electrodynamic processes in the bus duct during emergency state at the design stage [1, 2]. In addition, with numerical modeling, the accuracy of determining electrical parameters increases 2-2.5 times compared to traditional (analytical) calculation methods [3]. The purpose of the study was to review published articles on heating bus ducts up to 10 kV in short circuit situation, to develop a model of a power transformer – bus duct – load system with a three-phase short circuit (three phase S/C), to conduct a comparative analysis of the simulation results obtained with experimental data. Methods: the authors used the method of numerical simulation in the three phase S/C situation, implemented with the help of related non-stationary problems of the magnetic field and heat transfer. Non-stationary magnetic field problem simulated a short circuit jump and calculated the heat dissipation capacities in the buses at each moment of time. The specific volumetric heat dissipation power obtained in the program for the bus duct was as initial data to the problem of non-stationary heat transfer. Results: the result of the work is a simulated 10 kV power transformer system – bus duct – load corresponding to the section of a real substation with bus duct. The simulation data have a good convergence with the experimental data, the error in maximum heating temperatures was 3 %. The practical significance is with using the developed model it is possible to determine the real values of currents at the considered section of the substation, real heating temperatures. Accordingly, it is possible to choose the necessary and sufficient cross-sections of the bus duct, the distance between the base insulators, without excessive stocks. Also, with the help of the developed model, it is possible to justify the need for modernization proposals. Keywords: closed three-phase bus duct, three-phase short circuit situation, heating simulation, thermal resistance, thermal resistance test. Authors:
Uliana N. Abasheva (Ekaterinburg, Russian Federation) – Graduate Student EETS Department Ural Power Engineering Institute URFU (620010, Yekaterinburg, 19, Mira str., e-mail: uliana.abasheva@urfu.ru). Vasiliy E. Frizen (Ekaterinburg, Russian Federation) – Doctor of Technical Sciences, Professor, Head of the EETS Department Ural Energy Institute URFU (620010, Yekaterinburg, 19 Mira str., e-mail: vefrizen@urfu.ru). Sergey L. Nazarov (Ekaterinburg, Russian Federation) – Ph. D. in Technical Sciences, Associate Professor of the EETS Department Ural Energy Institute URFU (620010, Yekaterinburg, 19 Mira str., e-mail: nazarovsl.ekb@yandex.ru). References:
COIL CONTROL OF TUBULAR HEATING FURNACES IN HYDROGEN PRODUCTION BY STEAM CONVERSION BASED ON GENETIC ALGORITHMS A.A. Pimenov, E.A. Muravyova, I.F. Karimov Received: 04.04.2022 Received in revised form: 01.08.2022 Published: 22.12.2022 ![]() Abstract:
The object of the study of this work are tubular heating furnaces, which today are one of the dangerous objects in oil and gas production, since during the analysis at the enterprises a high proportion of accidents associated with nporapom in the zones of internal deposits and, as a consequence, the depressurization of coils, their deformation and the occurrence of explosions and fires in the further. In order to increase the service life of coils, increase the reliability of the furnace, control the coke formation of it and, thus, reduce the occurrence of accidents in production, it is necessary to develop a system for automatic control of the coking of the coil of a tubular furnace using genetic algorithms. Purpose: development of an automatic control system for coking the coil of a tubular furnace in the production of hydrogen by steam conversion based on genetic algorithms. Methods: construction of a system simulating the control of coking of tubular furnaces by maintaining a temperature not exceeding the limits at which coke is formed on the coils of the furnace. To quantify the level of coking of tubular coils of furnaces in real time, an evaluation criterion is proposed – the rate of coke formation, formed from a set of technological and technical parameters using empirical dependencies of a genetic algorithm, the value of the evaluation criterion (more than 0,8 kg / day) corresponding to the maximum permissible level of coking of the coil of a tubular heating furnace is determined. Results: in the process of investigating the problem of increasing the coking of the coil of tubular heating furnaces in the production of hydrogen by steam convection, genetic algorithms were used to build systems with complex behavior, since this method is relatively simple to implement, and a model of PID regulation with their use was also proposed, modeled in the "Simulink C" environment in nporpamme "Matlab". Practical relevance: as a result of the research, the actual problem of increasing the level of fire and industrial safety of tubular furnaces has been solved by building a system that simulates the control of coking of tubular furnaces in production. Keywords: furnace, control, coking, development, genetic algorithm, temperature, pressure. Authors:
Andrey A. Pimenov (Sterlitamak, Russian Federation) – Student of the Department of "Automated technological and information systems" branch of the Ufa State Petroleum Technological University, Institute of Chemical Technology and Engineering (453118, Sterlitamak, 2, October ave., e-mail: samcave@mail.ru). Elena A. Muravyova (Tomsk, Russian Federation) – Ph. D. in Technical Sciences, Associate Professor, Professor of the Department of "Automated technological and information systems" branch of the Ufa State Petroleum Technological University, Institute of Chemical Technology and Engineering (453118, Sterlitamak, 2, October ave., e-mail: muraveva_ea@mail.ru). Ilyosjon F. Karimov (Sterlitamak, Russian Federation) – Student of the Department of "Automated technological and information systems" branch of the Ufa State Petroleum Technological University, Institute of Chemical Technology and Engineering (453118, Sterlitamak, 2, October ave., e-mail: ilyos.karimov08@gmail.ru). References:
A METHOD OF MAXIMUM LIKELIHOOD GENERALIZATION OF MULTISPECTRAL IMAGES USING A SET OF ORDERED HETEROGENEOUS TEST SITES H.G. Asadov, A.J. Aliyeva Received: 26.06.2022 Received in revised form: 01.08.2022 Published: 22.12.2022 ![]() Abstract:
The main problem in validating satellite measurement data is that the spatial resolution of remote and ground-based measurement data is very different. As a result, it is relevant to solve the issues of validation of images of low spatial resolution using high-resolution images and vice versa. The purpose of the study. The purpose of the research is to carry out optimal generalization of ground-based measurement data. Methods: the operation of generalization of ground data may include the following: a) averaging of the results of the measurements carried out, suitable for processing data of homogeneous test sites; b) calculation of the empirical transition function between radiometric signals and the results of ground measurements, in the case of heterogeneity of test sites. The heterogeneity of test sites is an important factor, the correct accounting of which is necessary for the validation of on-board data in the most reliable way. Results: the problem of maximally plausible generalization of the results of onboard multispectral measurements of vegetation indices using ground-based ordered test plots is considered. The problem is solved using an integral logarithmic likelihood function, which is represented as an optimized functional depending on the optimized function of the relationship between the mean square root of the index measurement results separately for heterogeneous test sites and the average values of this index for the same sites. The optimal type of this relationship is determined in which, if some identified condition is met, the logarithmic integral likelihood function reaches its maximum value Keywords: optimization, validation, test site, likelihood, functional. Authors:
Asadov Hikmet Hamid oglu (Baku, Republic of Azerbaijan) – Doctor of Technical Sciences, Professor, Head of the Department of the Research Institute of Aerospace Informatics, Baku, Republic of Azerbaijan. Address-Baku city, AZ1145, st. S.S.Akhundova, 1, tel. +994 50 324 72 40 E-mail asadzade@rambler.ru Aliyeva Amida Jabrayil gizi (Baku, Republic of Azerbaijan) – Doctor of Philosophy in Engineering, Senior Specialist of the National Aerospace Agency, Baku, AZ1145, st. S.S. Akhundova, 1, e-mail amidec.b@gmail.com References:
OPTIMIZATION OF LASER DIODE OPTICAL POWER CONTROLLER V.D. Zagvozkin Received: 13.04.2022 Received in revised form: 20.07.2022 Published: 22.12.2022 ![]() Abstract:
The control of the operating modes of a laser diode is traditionally associated with the use of PI controllers. However, the laser diode must meet a number of technical requirements, such as the relative instability of the output power of radiation in the range of operating temperatures, the relative instability of the output power of radiation at a steady temperature, the time of functional readiness after power-up. The above requirements determine the quality of the laser diode. To comply with the technical requirements, the correct setting of the existing regulators is necessary. One of the effective ways to solve this problem is to build a mathematical model of an automatic control system (ACS) for the optical power of a laser diode and adjust the controller parameters using optimization methods. In this case, it is advisable to use the MatLab application package to identify the ACS model and adjust the controller. Purpose: optimization of the laser diode optical power controller. Methods: development of a mathematical model of a system for automatically controlling the optical power of a laser diode, using MatLab Identification Toolbox to identify a laser diode as a control object using experimental data. Results: optimization of the optical power controller of the laser diode made it possible to reduce the time to reach the operating power and increase the noise immunity. The developed mathematical model of the ACS with the optical power of the laser diode confirmed the correctness of the identification. Thanks to the optimization of the laser diode optical power controller, the ACS satisfies the technical requirements. Practical relevance: the results of the research were used in the development of the automatic control system for the optical power of the laser diode, which made it possible to reduce the time of functional readiness and reduce the instability of the output power of the laser diode radiation. Keywords: laser diode, identification, optimization, PI controller. Authors:
Vladimir V. Zagvozkin (Perm, Russian Federation) – Graduate Student of the Department of Automation and Telemechanics of Perm National Research Polytechnic University (614990, Perm, 29, Komsomolsky pr., References:
METHODOLOGY OF STRUCTURAL MANAGEMENT OF ORGANIZATIONAL SYSTEMS BASED ON COMPETITIVE MECHANISMS V.A. Kharitonov, D.N. Krivogina, A.S. Salamatina Received: 06.09.2022 Received in revised form: 04.10.2022 Published: 22.12.2022 ![]() Abstract:
The dynamics of the development of the intellectualization of management processes is directly related to the change and formation of technological structures. In this regard, it is necessary to study the real capabilities of a person, the process of subjectivism's influence on decision-making, the possibility of protection from environmental manipulation and the feasibility of using artificial intelligence as a decision support tool. All these factors influence the recruitment process, which in the current conditions should be carried out using a new technology that allows both professional technical skills and the formed skills of humanitarian disciplines to be taken into account at the same time. Purpose: to develop a new approach that allows for a comprehensive assessment of potential applicants for new, previously non-existing positions. Methods: the procedure of complex assessment based on a simulation model of behavior based on the construction of certificates of functions of reduction to the scale of complex assessment [1-4]. Results: the problems of the methodology of competitions of this type are described, the formulation and solution of problems based on the construction of analytical (algebraic solutions) and simulation (behavioral) models are presented. An algorithm for assessing the competencies of applicants is described, which is based on a model of complex assessment, including ranking and selection procedures on a variety of alternatives. A distinctive feature of these models is the construction of the "image" (model) of decision-making. An algorithm for creating artificial intelligence is presented, which will be the basis for choosing specialists. It is noted that, if necessary, the appearance of artificial intelligence can be adjusted. The parameters of artificial intelligence determine the parameters of convolution, taking into account the preferences of the subject of management and his ideas about the results of previous contests. Discussion: application of a new approach to evaluating potential applicants for the position of BIM coordinator. In the process of creating a model, the requirements for specialists of a new direction are formalized and structured. Keywords: projective management, competitive mechanism, interdisciplinarity, technological structure, BIM technologies, integrated assessment, correction, artificial intellect. Authors:
Valerij A. Kharitonov (Perm, Russian Federation) – Doctor of Technical Sciences, Professor, Professor Department of Construction Engineering and Material, Honored Worker of Higher School of the Russian Federation Perm National Research Polytechnic University (614990, Perm, 29, Komsomolsky pr., e-mail: cems@pstu.ru). Darya N. Krivogina (Perm, Russian Federation) – Ph.D. in Technical Sciences, Associate Professor Department of Construction Engineering and Material Perm National Research Polytechnic University (614990, Perm, 29, Komsomolsky pr., e-mail: darya.krivogina@gmail.ru). Anna S. Salamatina (Perm, Russian Federation) – Graduate Student Department of Construction Engineering and Material Perm National Research Polytechnic University (614990, Perm, 29, Komsomolsky pr., e-mail: salamatina@cems.pstu.ru) References: 1. Glaz'ev S.Iu. Ryvok v budushchee. Rossiia v novykh tekhnologicheskom i mirokhoziaistvennom ukladakh [A leap into the future. 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Infrmatsionnye modeli zdanii (BIM) [Building Information Models (BIM)]. Molodezhnyi nauchnyi vestnik, 2017, no. 12 (25), pp. 167-175. 13. Batekhova A.A., Goriushkin K.N. BIM-proektirovanie: rol' informatsionnykh modelei v real'nom stroitel'stve [BIM design: the role of information models in real construction]. Pokolenie budushchego: vzgliad molodykh uchenykh - 2021. Sbornik nauchnykh statei 10-i Mezhdunarodnoi molodezhnoi nauchnoi konferentsii, Kursk, 11-12 November 2021. Kursk: Iugo-Zapadnyi gosudarstvennyi universitet, 2021, pp. 146-149. 14. Pastukh O.A., Kurakov A.Iu. Rol' BIM-tekhnologii v proektirovanii, stroitel'stve i podgotovke kvalifitsirovannykh kadrov [The role of BIM technologies in design, construction and training of qualified personnel]. BIM-modelirovanie v zadachakh stroitel'stva i arkhitektury. Materialy III Mezhdunarodnoi nauchno-prakticheskoi konferentsii, Sankt-Peterburg, 15-17 April 2020. Saint Petersburg: Sankt-Peterburgskii gosudarstvennyi arkhitekturno-stroitel'nyi universitet, 2020, pp. 344-354. 15. Epstein M. PreDictionary: experiments in verbal creativity. USA: Lulu.com, 2011, 131 p. 16. Kharitonov V.A., Alekseev A.O. Kontseptsiia sub"ektno-orienti¬rovannogo upravleniia v sotsial'nykh i ekonomicheskikh sistemakh [The Concept of Agent-based Control in Social and Economic Systems]. Politematicheskii setevoi elektronnyi nauchnyi zhurnal Kubanskogo gosudarstvennogo agrarnogo universiteta, 2015, no. 109, pp. 690-706. 17. Burkov V.N., Korgin N.A., Novikov D.A. Vvedenie v teoriiu upravleniia organizatsionnymi sistemami [Introduction to the theory of management of organizational systems]. Ed. chlen-korrespondent RAN 18. Novikov D.A. Teoriia upravleniia organizatsionnymi sistemami [Theory of management of organizational systems]. Moscow: Moskovskii psikhologo-sotsial'nyi universitet, 2005, 581 p. 19. Lykov M.V., Alekseev A.O., Kharitonov V.A. Innovatsionnye tekhnologii upravleniia konkursnoi deiatel'nost'iu [Innovative technologies for managing competitive activities]. Vestnik Samarskogo gosudarstvennogo ekonomicheskogo universiteta, 2010, no. 6 (68), pp. 31-35. 20. Lykov M.V., Novopashina E.I. Konkursnye sistemy liberal'nogo upravleniia deiatel'nost'iu liudei v zadannoi predmetnoi oblasti [Competitive System Activities of Liberal ìanagement of People's Occupations in the Specific Subject Area]. Upravlenie bol'shimi sistemami. Sbornik trudov VI Vserossiiskoi shkoly-seminara molodykh uchenykh. Izhevsk, 2009, 21. Gureev K.A., Lykov M.V. Shaidulin R.F. Protsedura podderzhki priniatiia kollegial'nykh reshenii s ispol'zovaniem aktivnoi ekspertizy [The Procedure of Collective Decision Taking Support Within Active Expertise Use/Active Systems Theory]. Teoriia aktivnykh sistem. Trudy mezhdunarodnoi nauchno-prakticheskoi konferentsii, Moscow, 17-19 November 2009. Ed. V.N. Burkov, D.A. Novikov. Moscow, 2009, vol. 1, 22. Alekseev A.O. Klassifikatsiia mekhanizmov kompleksnogo otsenivaniia slozhnykh ob"ektov [Classification of mechanisms of complex assessment of complex objects]. Informatsionnye i matematicheskie tekhnologii v nauke i upravlenii, 2018, no. 2 (10), pp. 106-120. 23. Rapaport D. Projective techniques and the theory of thinking. J. of Projective Techniques, 2010, vol. 16, pp. 269-275. 24. Kharitonov V.A., Alekseev A.O., Vychegzhanin A.V., Grevtsev A.M., Dmitriukov M.S., Krivogina D.N., Spirina V.S., Shaidulin R.F., Geikhman L.K. Kvantifikatsiia predpochtenii khoziaistvuiushchikh sub"ektov upravleniia v zadachakh tsifrovoi ekonomiki: monografiia [Quantification of preferences of economic management entities in the tasks of the digital economy: monograph]. Ed. V.A. Kharitonov. Perm': Permskii natsional'nyi issledovatel'skii politekhnicheskii universitet, 2018, 171 p. 25. Belykh A.A., Gorlov Iu.G., Kalinin N.P. Funktsional'nye vozmozhnosti mekhanizmov kompleksnogo otsenivaniia [Functional capabilities of integrated assessment mechanisms]. Vestnik Permskogo universiteta, 2007, no. 9 (14), pp. 103-107. 26. Kharitonov V.A. Shaidulin R.F., Melekhin M.I. et al. Svidetel'stvo o gosudarstvennoj registracii programmy dlja JeVM ¹ 2022611581 Dekon-Tandem [Certificate of state registration of the computer program INTELLIGENT TECHNOLOGIES IN THE ELECTRICAL EQUIPMENT OPERATION PROCESS ORGANIZATION D.K. Eltyshev Received: 20.08.2022 Received in revised form: 30.08.2022 Published: 22.12.2022 ![]() Abstract:
The functioning of modern systems of energy production, transmission and distribution is considered in the context of the use of digital technologies to ensure their high security, flexibility, adaptability and economy. Information about the installations and equipment condition included in such systems is the basis for making decisions regarding the strategy for its operation in the short and long term. The purpose of the study is to formalize the principles of managing the electrical equipment operation based on reliable data on its technical condition. Methods: We considered the task of managing the equipment operation process as the formation of scenarios determined by its technical condition. The condition is evaluated using the intelligent data processing and analysis and machine learning methods. The source of such information is software and hardware tools that allow non-destructive testing of equipment, its components and assemblies. Results: the key features of the technique for selecting the equipment operation scenario in accordance with its actual (forecast) condition were considered. The technique can be applied to various types of equipment of the power grid facilities, as well as to various solutions in the field of monitoring technical parameters. The principles of using machine learning methods in the implementation of the methodology were shown. In particular, the features of applying the methods of decision trees and random forest for a reliable assessment of the equipment condition were investigated. As an example, a simplified model for assessing the thermal condition of high-voltage electrical equipment based on infrared monitoring data was proposed. The results of applying decision tree and random forest algorithms to determine the defects of equipment with a classification error of no more than 9% were presented. Practical significance: the proposed approach allows you to make informed decisions to take timely measures for the maintenance and repair of equipment and reduce the occurrence of emergency situations. The technique is universal and can be applied to objects of any structure and configuration, and also allows you to improve the accuracy of assessing the selected object condition by accumulating statistical data and using the mechanisms of tuning and adaptive selection of various algorithms when forming diagnostic models. Keywords: electrical equipment, non-destructive testing, technical condition, data analysis, machine learning, decision trees, random forest. Authors:
Eltyshev Denis Konstantinovich (Perm, Russian Federation) – Ph. D. in Technical Sciences, Associate Professor of Microprocessor Automation Means Department Perm National Research Polytechnic University (614990, Perm, 29, Komsomolsky pr., e-mail: eltyshev@msa.pstu.ru). References: 1. Mozokhin A.E., Mozokhin A.E. Analiz perspektivnogo razvitiia energeticheskikh sistem v usloviiakh tsifrovoi transformatsii rossiiskoi ekonomiki [Analysis of the prospective development of energy systems in the context of the digital transformation of the Russian economy]. Nauchno-tekhnicheskii vestnik informatsionnykh tekhnologii, mekhaniki i optiki, 2020, vol. 20, no. 1, pp. 82-93. 2 Eltyshev D.K. Vybor prioritetov pri obsluzhivanii, modernizatsii i obespechenii bezopasnosti ob"ektov energetiki [Priority ranking for maintenance, renovation, and ensuring security of power facilities]. Energobezopasnost' i energosberezhenie, 2017, no. 2, pp. 5-10. 3. Sitnikov V.F., Skopintsev V.A. Intellektual'naia elektroenergeticheskaia sistema s aktivno-adaptivnoi set'iu [Intelligent electric power system with an active-adaptive grid]. Elektrichestvo, 2012, no. 3, pp. 2-7. 4. Giordano V., Meletiou A., Covrig C.F., Mengolini A., Ardelean V., Fulli G., Jiménez M., Filiou C. Smart grid projects in Europe: lessons learned and current developments. Luxembourg: Publications Office of the European Union, 2012, 142 p. 5. Bayindir R., Colak Ilhami, Fulli Gianluca, Demirtas Kenan. Smart grid technologies and applications. Renewable and Sustainable Energy Reviews, 2016, no. 66, pp. 499-516. 6. Massel' L.V. Sovremennyi etap razvitiia iskusstvennogo intellekta (II) i primenenie metodov i sistem II v energetike [The current stage of development of artificial intelligence (AI) and the application of AI methods and systems in the energy sector]. Informatsionnye i matematicheskie tekhnologii v nauke i upravlenii, 2021, no. 4 (24), pp. 5-20. 7. Nazarychev A.N. et al. Osnovy upravleniia tekhnicheskim sostoianiem elektrooborudovaniia [Basics of electrical equipment technical condition management]. Saint Peterburg: Politekhnicheskii universitet, 2015, 204 p. 8. Eltyshev D.K., Kostygov A.M. Kontseptsiia effektivnogo upravleniia sostoianiem elektrotekhnicheskogo oborudovaniia po dannym nerazrushaiushchego kontrolia [The concept of efficient control of the condition of electrical equipment according to nondestructive testing data]. Elektrotekhnika, 2020, no. 11, pp. 45-50. 9. Li S., Li J. Condition monitoring and diagnosis of power equipment: Review and prospective. High Volt, 2017, no. 2, pp. 82-91. 10. Eltyshev D.K. Osobennosti kompleksnoi otsenki sostoianiia elektrotekhnicheskogo oborudovaniia na osnove nerazrushaiushchego kontrolia i intellektual'nogo analiza dannykh [Features of the electrical equipment complex condition assessment based on non-destructive control and intelligent data analysis]. Vestnik Permskogo natsional'nogo issledovatel'skogo politekhnicheskogo universiteta. Elektrotekhnika, informatsionnye tekhnologii, sistemy upravleniia, 2021, no. 39, pp. 109-127. 11. Khoroshev N.I., Kazantsev V.P. Management Support of Electroengineering Equipment Servicing Based on the Actual Technical Condition. Automation and Remote Control, 2015, vol. 76, no. 6, pp. 1058-1069. 12. Contreras-Valdes Arantxa, Juan P. Amezquita-Sanchez, David Granados-Lieberman, Martin Valtierra-Rodriguez. Predictive data mining techniques for fault diagnosis of electric equipment: A Review. Applied Sciences, 2020, no. 10 (3), 950 p. 13. Eltyshev D.K., Kostygov A.M. Intellektual'nyi diagnosticheskii kontrol' i upravlenie sostoianiem elektrotekhnicheskogo oborudovaniia [Intelligent Diagnostic Control and Management Of The Condition Of Electrotechnical Equipment]. Elektrotekhnika, 2019, no. 11, pp. 42-47. 14. Ahmad T., Zhu H., Zhang D., Tariq R., Bassam A., Ullah F., AlGhamdi A.S., Alshamrani S.S. Energetics systems and artificial intelligence: applications of industry 4.0. Energy Reports, 2022, no. 8, pp. 334-361. 15. Sarita K., Kumar S., Saket R.K. Fault detection of smart grid equipment using machine learning and data analytics. Advances in Smart Grid Automation and Industry 4.0. Lecture Notes in Electrical Engineering, 2021, vol. 693. 16. Pan S., Morris T., Adhikari U. Developing a hybrid intrusion detection system using data mining for power systems. IEEE Trans. Smart Grid, 2015, no. 6 (6), pp. 3104-3113. 17. Jamil M., Sharma S.K., Singh R. Fault detection and classification in electrical power transmission system using artificial neural network. SpringerPlus, 2015, no. 4, 334 p. 18. Eltyshev D.K. Electric equipment operation scenarios based on the results of non-destructive condition control. Journal of Physics: Conference Series. 2: International Conference on Innovation Energy 2020, IE 2020, 2021, 012010 p. 19. Eltyshev D.K. Mnogokriterial'nyi analiz reshenii v intellektual'nykh sistemakh otsenki i upravleniia sostoianiem energeticheskogo oborudovaniia [Multi-criteria decision analisys in intelligent systems for asses sing and managing of power equipment condition]. Informatika i sistemy upravleniia, 2018, no. 2 (56), pp. 96-107. 20. Breiman L. Random Forests. Machine Learning, 2001, vol. 45, 21. Hastie T, Tibshirani R, Friedman J. The Elements of Statistical Learning: Data Mining, Inference and Prediction, Second Edition (Springer), 2016, 764 p. 22. Chistiakov S.P. Sluchainye lesa: obzor [Random Forests Overview]. Trudy Karel'skogo nauchnogo tsentra RAN, 2013, no. 1, pp. 117-136. 23. Kaftannikov I.L., Parasich A.V. Osobennosti primeneniia derev'ev reshenii v zadachakh klassifikatsii [Features of the use of decision trees in classification problems]. Vestnik IuUrGU. Komp'iuternye tekhnologii, upravlenie, radioelektronika, 2015, vol. 15, no. 3, pp. 26-32. 24. Powers David M.W. Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation. Journal of Machine Learning Technologies. 2011. vol. 2, no. 1, pp. 37-63. 25. Jadin M.S., Taib S. Recent progress in diagnosing the reliability of electrical equipment by using infrared thermography. Infrared Physics & Technology, 2012, vol. 55, no. 4, pp. 236-245. 26. Eltyshev D.K. Intellektual'nye modeli kompleksnoi otsenki tekhnicheskogo sostoianiia vysokovol'tnykh vykliuchatelei [Intelligent models for complex assessment of technical condition of high-voltage circuit breakers]. Informatsionno-upravliaiushchie sistemy, 2016, no. 5 (84), pp. 45-53. SOLUTION OF MULTI-CRITERIA OPTIMIZATION PROBLEM OF NEURAL NETWORK DECOMPOSITION OPTIONS AND THE LAYOUT OF A CASCADE OF COMPUTING DEVICES BY THE PARETO METHOD V.V. Bakhtin, I.A. Podlesnykh, S.F. Tyurin Received: 10.10.2022 Received in revised form: 22.10.2022 Published: 22.12.2022 ![]() Abstract:
Improving the functionality of a computing system is often necessary in real work tasks in production and in the digital sphere. At the same time, increasing functionality often requires the acquisition and implementation of additional computing devices into the system. At the same time, there are often situations when the computing power of existing devices is not fully used. The aim of the study is to solve a multi-criteria optimization problem for finding the most suitable circuit model of a cascade of devices and finding the most optimal decomposition of a neural network. The research methodology is based on circuit modeling of cascades of neural network devices, programming the decomposition of a block neural network, the Pareto optimization method, and analysis of the experimental results. As a result of the study, it is planned to obtain a solution to the problem of multi-criteria optimization of options for implementing a cascade of neural network devices for the functioning of a block neural network. The article formulates and solves the problem of multi-criteria optimization, which makes it possible to determine the optimal way to decompose a neural network within the framework of the device synthesis method. Various schemes for implementing a computational cascade with a different number of devices and different computing capabilities of nodes are considered. All variants of the decomposition of a monolithic neural network proposed within the framework of the improved synthesis method are considered, experimental launches of cascades of devices are carried out and the best configurations of computational cascades are selected according to the proposed set of parameters, which confirmed the applicability of the method of synthesis of neural network devices. Keywords: circuit modeling, synthesis method, distributed artificial neural network, decomposition, fog computing, microcontroller, multi-criteria Pareto optimization. Authors:
Vadim V. Bakhtin (Perm, Russian Federation) – Graduate Student, junior researcher of the Department of Automation and Telemechanics Perm National Research Polytechnic University (614990, Perm, 29, Komsomolsky pr., e-mail: bakhtin_94@bk.ru), Senior lecturerat the Department of Information Security and Communication Systems Perm State University (614990, Perm, 15, Bukireva str.). Ivan A. Podlesnykh (Perm, Russian Federation) – Graduate Student of the Department of Automation and Telemechanics Perm National Research Polytechnic University (614990, Perm, 29, Komsomolsky pr., e-mail: podlesnihwork@gmail.com), Mathematician at Novomet (614065, Perm, 395, shosse Kosmonavtov). Sergey F. Tyurin (Perm, Russian Federation) – Honored Inventor of the Russian Federation, Doctor of Technical Sciences, Professor, Professor at the Department of Automation and Telemechanics Perm National Research Polytechnic University (614990, Perm, 29, Komsomolsky pr., e-mail: tyurinsergfeo@yandex.ru), Professor at the Department of Software Computing Systems Perm State University (614990, Perm, 15, Bukireva str.). References:
APPLICATION OF THE THEORY OF SOLVING INVENTIVE PROBLEMS FOR THE DEVELOPMENT OF A METHOD FOR CLEANING POWER LINES FROM ICE I.S. Ulman, S.A. Gandzha, D.V. Korobatov, E.M. Lekerova, M.S. Kozlov Received: 10.10.2022 Received in revised form: 21.10.2022 Published: 22.12.2022 ![]() Abstract:
Today there is a problem of protecting overhead power lines from the formation of ice. It remains relevant for regions with a humid winter climate and a significant amount of precipitation. With the existing numerous methods of combating ice applied in practice, so far none of them fully satisfies the network companies operating this equipment. As a rule, direct current melting is used to eliminate ice, but this is not economical. The purpose of the study: based on the analysis and criticism of existing methods of cleaning overhead lines from ice, to offer a reliable and economical way to solve this problem. Methods: to achieve this goal, an Algorithm for Solving Inventive Problems (ASIP) was used, developed and described in detail by the Soviet inventor Altshuller G.S. in his works on the theory of solving inventive problems (TSIP). Results: based on the algorithmic steps of ARIZ, the main technical contradiction of the system was revealed, internal and external resources were determined, the ideal final result was formulated, the parameters of the additional X-element introduced into the system were specified, several options for the constructive implementation of this element were proposed. The following methods are considered: the use of hydrophobic insulation, a drive based on an asynchronous motor with shielded poles, a vibration drive with spacers between wires, an electromagnet-based drive located between the insulator and the wire. An analysis of each method was carried out and the most optimal one was selected. A drive based on an electromagnet located between an insulator and a wire is recommended as the main device having the greatest reliability and cost-effectiveness for implementation into practice. Practical significance: the concept of an anti-ice device is proposed, which is a vibrating electromagnet that creates an oscillatory effect on the wire. At the same time, on the one hand, the possibility of ice formation in conditions of high humidity and low temperatures is excluded, on the other hand, mechanical cleaning of the overhead line occurs if the frost has already settled on the wires. The device can operate in automatic mode from humidity and temperature sensors and in automated mode at the operator's command. Discussion: the proposed method relates to mechanical methods of cleaning overhead lines, but unlike existing devices of this type, such as robotic devices moving between spans, a drive with a micro-motor that rotates the cutter and moves along the wire, the swing of wires between spans, the design of the proposed device is simpler, cheaper and reliable. It does not require disconnecting the line from the consumer during cleaning, special maintenance, or the involvement of additional personnel for the operation. The introduction of this proposal into the practice of operating overhead lines will significantly reduce the number of cases of emergency shutdowns due to ice formation, which will reduce material damage from under-supply of electricity and the cost of repairing electrical equipment Keywords: power transmission line, icing, theory of inventive problem solving, algorithm for solving inventive problems, vibrating electromagnet. Authors:
Iaroslav S. Ulman (Cheljabinsk, Russian Federation) – Master of the Department of Electric Drive, Mechatronics and Electromechanics of the South Ural State University (454080, Chelyabinsk, Prospekt Lenina, 76, Sergey A. Gandzha (Cheljabinsk, Russian Federation) – Doctor of Technical Sciences, Professor of Department of Electric Drive, Mechatronics and Electromechanics of the South Ural State University (454080, Chelyabinsk, Prospekt Lenina, 76, e-mail: gandzhasa@susu.ru). Denis V. Korbatov (Cheljabinsk, Russian Federation) – Ph. D. in Technical Sciences, Associate Professor of the Department of Power Stations and Power Supply Systems of the South Ural State University (454080, Chelyabinsk, Prospekt Lenina, 76, e-mail: korobatovdv@susu.ru). Ekaterina M. Lekerova (Cheljabinsk, Russian Federation) – Master of the Department of Electric Drive, Mechatronics and Electromechanics of the South Ural State University (454080, Chelyabinsk, Prospekt Lenina, 76, e-mail: lekerovaekaterina99@mail.ru). Maxim S. Kozlov (Cheljabinsk, Russian Federation) – Master of the Department of electric drive, mechatronics and electromechanics of the South Ural State University (454080, Chelyabinsk, Prospekt Lenina, 76, References:
APPLICATION OF NEURAL NETWORK IDENTIFICATION FOR ADAPTIVE CONTROL OF GASÅ TURBINE POWER PLANTS I.V. Bakhirev, B.V. Kavalerov Received: 25.10.2022 Received in revised form: 07.11.2022 Published: 22.12.2022 ![]() Abstract:
Gas turbine power plants are used to generate electricity as part of various power systems. Electric load behavior can vary greatly from system to system, depending on its topology and composition of electromechanical elements. Adaptive control algorithms are used to improve control system reliability and power quality. The control system of a gas turbine plant, which is part of a gas turbine power plant, has a complex structure based on the selection of control channels. The adaptive control algorithms considered in the article complement the standard control system by interacting with the selected control loops. Thanks to this approach, the development and adjustment time of the adaptive controller is reduced. Improving the quality of control brings a reduction in fuel consumption associated with power overflows and long transients, thus increasing the environmental friendliness of gas turbine power plants. Research objective: modification of adaptive control algorithm of gas turbine power plant, simplifying the process of identification in real time adjustable model through the use of neural network identification of gas turbine plant parameters. Methods: the study of the proposed modification of the identification process of parameters in real-time tunable model of gas turbine power plant was conducted by mathematical modeling, the modification of the identification process was carried out using the mathematical apparatus of neural networks and optimization methods. Results: the process of identification in real-time tunable model is much easier in comparison with the previously considered method based on the Lyapunov function. Practical significance: the presented modification allows to create adaptive control systems with a tunable model for gas turbine units that are part of gas turbine power plants. Keywords: gas turbine power plant, gas turbine unit, adaptive control, reference model, tunable model. Authors:
Ivan V. Bakhirev (Perm, Russian Federation) – Ph. D. in Technical Sciences, Associate Professor of the Department of Electrical Engineering and Electromechanics of Perm National Research Polytechnic University (614990, Perm, 29, Komsomolsky pr., e-mail: bahirevy@mail.ru). Boris V. Kavalerov (Perm, Russian Federation) – Doctor of Technical Sciences, Associate Professor, head of Electrical Engineering and Electromechanics of Perm National Research Polytechnic University (614990, Perm, 29, Komsomolsky pr., e-mail: kbv@pstu.ru). References: 1. Khizhniakov Iu.N. Sovremennye problemy teorii upravleniia [Modern problems of control theory]. Perm': Permskii natsional'nyi issledovatel'skii politekhnicheskii universitet, 2015, 237 p. 2. Miroshnik I.V., Nikiforov V.O., Fradkov A.L. Nelineinoe i adaptivnoe upravlenie slozhnymi dinamicheskimi sistemami [Nonlinear and adaptive control of complex dynamic systems]. Saint Petersburg: Nauka, 2000, 549 p. 3. Khizhniakov Iu.N., Iuzhakov A.A. Adaptivnoe upravlenie parallel'noi rabotoi sinkhronnykh generatorov s set'iu beskonechnoi moshchnosti [Adaptive control of parallel operation of synchronous generators with an infinite power network]. Izvestiia vysshikh uchebnykh zavedenii. Problemy energetiki, 2011, no. 5, pp. 65-72. 4. Bakhirev I.A., Basargin Sh.D., Kavalerov B.V. Adaptivnoe upravlenie gazoturbinnoi ustanovkoi s etalonnoi model'iu i signal'noi nastroikoi [Adaptive control of a gas turbine plant with a reference model and signal tuning]. Sistemy upravleniia i informatsionnye tekhnologii, 2015, no. 2, pp. 71-76. 5. Ziiatdinov I.R., Kavalerov B.V., Bakhirev I.V. Issledovanie sistemy upravleniia s etalonnoi model'iu i signal'noi nastroikoi dlia elektroenergeticheskoi gazoturbinnoi ustanovki [Study of a control system with a reference model and signal tuning for an electric power gas turbine plant]. Fundamental'nye issledovaniia, 2015, no. 62, pp. 235-240. 6. Bakhirev I.V. Kavalerov B.V. 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