Алгоритм работы системы накопления энергии в структуре электротехнического комплекса объекта газовой отрасли
Ключевые слова:
алгоритм, электротехнический комплекс, система накопления энергии, оптимизация, целевая функция
Аннотация
В системах электроснабжения различных бытовых и технологических объектов все большее распространение получают системы накопления энергии на основе аккумуляторных батарей различных типов. Эксплуатация систем накопления характеризуется рядом технологических сложностей, связанных с физико-химическими особенностями работы аккумуляторов (ограниченное количество циклов заряда-разряда, ускоренное старение). Для рационального расходования накопленной энергии и оптимизации эксплуатационных характеристик аккумуляторных батарей необходима разработка специализированной системы управления работой системы накопления энергии. В рамках данного исследования разработано два алгоритма планирования работы электротехнического комплекса объекта газовой отрасли: алгоритм жестких правил и динамического планирования. Основными методами исследования были сценарный анализ работы электротехнических комплексов для построения алгоритмов автоматического управления на логических блоках, а также математическая многокритериальная оптимизации на основе целевых функций и алгоритма типа «хищник-жертва». Для каждого из разработанных алгоритмов проработаны сценарии функционирования, а также определено соотношение между типами систем управления и структурами существующих типовых электротехнических комплексов объектов газовой отрасли.
Литература
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#
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2. Cheng Y. et al. Profitably Scheduling the Energy Hub of Inhabitable Houses Considering Electric Vehicles, Storage Systems, Revival Provenances and Demand Side Management through a Modified Particle Swarm Optimization. – Sustainable Cities and Society, 2023, vol. 92, DOI: 10.1016/J.SCS.2023.104487.
3. Iwafune Y. et al. Cooperative Home Energy Management Using Batteries for a Photovoltaic System Considering the Diversity of Households. – Energy conversion and management, 2015, vol. 96, pp. 322–329, DOI: 10.1016/J.ENCONMAN.2015.02.083.
4. Hassanzadehfard H., Tooryan F., Dargahi V. Standalone Hybrid System Energy Management Optimization for Remote Village Considering Methane Production from Livestock Manure. – International Journal of Hydrogen Energy, 2023, vol. 48, No. 29, pp. 10778–10796, DOI: 10.1016/J.IJHYDENE.2022.12.085.
5. Шклярский Я.Э. и др. Энергоэффективность в минерально-сырьевом комплексе. – Записки Горного института, 2023, т. 261, с. 323–324.
6. Dehghani M. et al. Spring Search Algorithm for Simulta-neous Placement of Distributed Generation and Capacitors. – Electrical Engineering & Electromechanics, 2018, No. 6, pp. 68–73, DOI: 10.20998/2074-272X.2018.6.10.
7. Kumar R.P., Karthikeyan G. A Multi-Objective Optimization Solution for Distributed Generation Energy Management in Microgrids with Hybrid Energy Sources and Battery Storage System. – Journal of Energy Storage, 2024, vol. 75, DOI: 10.1016/J.EST.2023.109702.
8. Chreim B., Esseghir M., Merghem-Boulahia L. Recent Sizing, Placement, and Management Techniques for Individual and Shared Battery Energy Storage Systems in Residential Areas: A review. – Energy Reports, 2024, vol. 11, pp. 250–260, DOI: 10.1016/J.EGYR.2023.11.053.
9. Premadasa P.N.D. et al. A Multi-Objective Optimization Model for Sizing an off-Grid Hybrid Energy Microgrid with Optimal Dispatching of a Diesel Generator. – Journal of Energy Storage, 2023, vol. 68, DOI: 10.1016/J.EST.2023.107621.
10. Modu B. et al. Energy Management and Capacity Planning of Photovoltaic-Wind-Biomass Energy System Considering Hydro-gen-Battery Storage. – Journal of Energy Storage, 2023, vol. 73, DOI: 10.1016/J.EST.2023.109294.
11. Гашимов А.М., Гулиев Г.Б., Рахманов Н.Р. Улучшенный алгоритм нечеткой логики для управления реактивной мощностью и напряжением в распределительных сетях. – Энергетика. Известия высших учебных заведений и энергетических объединений СНГ, 2014, № 2, с. 29–39.
12. Алехин Р.А. и др. Обзор метаэвристических методов оптимизации, применяемых при решении электроэнергетических задач. – Вестник Самарского государственного технического университета. Серия: Технические науки, 2019, № 3 (63), с. 6–19.
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14. Dehghani M. et al. A New Methodology Called Dice Game Optimizer for Capacitor Placement in Distribution Systems. – Electrical Engineering and Electromechanics, 2020, No. 1, pp. 61–64, DOI: 10.20998/2074-272X.2020.1.10.
15. Nowdeh S.A. et al. Stochastic Optimization – Based Economic Design for a Hybrid Sustainable System of Wind Turbine, Combined Heat, and Power Generation, and Electric and Thermal Storages Considering Uncertainty: A Case Study of Espoo, Finland. – Renewable and Sustainable Energy Reviews, 2023, vol. 183, DOI: 10.1016/J.RSER.2023.113440.
16. Nair S.P., Sundari M.S.S. Optimizing Day-Ahead Energy Management with Demand Response in a PV-Diesel-Battery System Using a Hybrid GOA-SNN Strategy. – Journal of Energy Storage, 2024, vol. 76, DOI: 10.1016/J.EST.2023.109717.
17. Жуковский Ю.Л., Сизякова Е.В. Внедрение системы энергосбережения и энергоэффективности на предприятиях металлургического комплекса. – Записки Горного института, 2013, т. 202, с. 155–160.
18. Behzadi A., Sadrizadeh S. A Rule-Based Energy Management Strategy for a Low-Temperature Solar/Wind-Driven Heating System Optimized by the Machine Learning-Assisted Grey Wolf Approach. – Energy Conversion and Management, 2023, vol. 277, DOI: 10.1016/J.ENCONMAN.2022.116590.
19. Козярук А.Е. и др. Диагностика и оценка остаточного ресурса электромеханического оборудования, работающего в тяжелых условиях, по электрическим параметрам. – Записки Горного института, 2011, т. 192, с. 161.
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21. Hussain S. et al. Multi-Stage Optimization for Energy Management and Trading for Smart Homes Considering Operational Constraints of a Distribution Network. – Energy Build, 2023, vol. 301, DOI: 10.1016/J.ENBUILD.2023.113722.
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