Topology Optimization of the Network with Renewable Energy Sources Generation Based on a Modified Adapted Genetic Algorithm
Электронный научный архив УРФУ
Информация об архиве | Просмотр оригинала| Поле | Значение | |
| Заглавие |
Topology Optimization of the Network with Renewable Energy Sources Generation Based on a Modified Adapted Genetic Algorithm
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| Автор |
Bramm, A. M.
Khalyasmaa, A. I. Eroshenko, S. A. Matrenin, P. V. Papkova, N. A. Sekatski, D. A. |
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| Тематика |
DISTRIBUTED GENERATION
DISTRIBUTION NETWORK GENETIC ALGORITHM LOAD CURVE METAHEURISTIC METHODS MODE OPTIMIZATION POWER LOSSES RESTRUCTURING SOLAR ENERGY |
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| Описание |
The article presents an adaptive genetic algorithm developed by the authors, which makes it possible to optimize the topology of a power network with distributed generation. The optimization was based on bioinspired methods. The objects of the study was a 15-node circuit of a power network with photovoltaic stations and a 14-node IEEE augmented circuit with distributed generation sources (three wind farms and two photovoltaic plants). The simulation of the modes of electric power systems was performed using the Pandapower library for the Python programming language, which is in the public domain. Three types of electric load of consumers were considered, reflecting the natures of electricity consumption in the nodes of real electric power systems, the results of numerical studies were presented. The proposed genetic algorithm used two different functions of interbreeding, the function of mutation, selection of the best individuals and mass mutation (complete population renewal). At the end of each iteration of the algorithm operation, statistical dependencies were derived that characterized its work: the best (minimal losses) and average adaptability in the population, a list of the best individuals throughout all iterations, etc. The verification was carried out in comparison with the results obtained by a complete search of possible radial configurations of the system, and it showed that the developed genetic algorithm had fast convergence, high accuracy and was able to work correctly with different configurations of electrical circuits, generation and load structures. The algorithm can be used in conjunction with renewable energy sources generation forecasting systems for the day ahead when planning the operating modes of power units in order to minimize the costs of covering electricity losses and improve the quality of electricity supplied. © 2022 Belarusian National Technical University. All rights reserved.
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| Дата |
2024-04-08T11:05:32Z
2024-04-08T11:05:32Z 2022 |
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| Тип |
Article
Journal article (info:eu-repo/semantics/article) Published version (info:eu-repo/semantics/publishedVersion) |
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| Идентификатор |
Bramm, AM, Khalyasmaa, AI, Eroshenko, SA, Matrenin, PV, Papkova, NA & Sekatski, DA 2022, 'Оптимизация топологии сети с ВИЭ-генерацией на основе модифицированного адаптированного генетического алгоритма', Energetika. Proceedings of CIS Higher Education Institutions and Power Engineering Associations, Том. 65, № 4, стр. 341-354. https://doi.org/10.21122/1029-7448-2022-65-4-341-354
Bramm, A. M., Khalyasmaa, A. I., Eroshenko, S. A., Matrenin, P. V., Papkova, N. A., & Sekatski, D. A. (2022). Оптимизация топологии сети с ВИЭ-генерацией на основе модифицированного адаптированного генетического алгоритма. Energetika. Proceedings of CIS Higher Education Institutions and Power Engineering Associations, 65(4), 341-354. https://doi.org/10.21122/1029-7448-2022-65-4-341-354 1029-7448 Final All Open Access; Gold Open Access; Green Open Access https://energy.bntu.by/jour/article/download/2180/1835 https://energy.bntu.by/jour/article/download/2180/1835 http://elar.urfu.ru/handle/10995/131171 10.21122/1029-7448-2022-65-4-341-354 85138083595 |
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| Язык |
ru
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| Права |
Open access (info:eu-repo/semantics/openAccess)
cc-by https://creativecommons.org/licenses/by/4.0/ |
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| Формат |
application/pdf
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| Издатель |
Belarusian National Technical University
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| Источник |
ENERGETIKA. Proceedings of CIS higher education institutions and power engineering associations
Energetika. Proceedings of CIS Higher Education Institutions and Power Engineering Associations |
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