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Optimal techno-economic energy management strategy for building’s microgrids based bald eagle search optimization algorithm

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  • Ferahtia, Seydali
  • Rezk, Hegazy
  • Abdelkareem, Mohammad Ali
  • Olabi, A.G.

Abstract

This research proposes an effective energy management strategy (EMS) for the economic operation under standalone and grid-connected operating modes of integrated solar renewables microgrid. The proposed microgrid is composed of a photovoltaic generator (PV), a fuel cell system (FC), and a battery storage system. The random nature of the renewable and the load power imposed some stability problems and economic problems, including operating costs. The suggested technique was based on the bald eagle search optimization algorithm (BES), which was designed for a one-day scheduling horizon. The key objectives of this paper were to satisfy the load power with the lowest operating costs under a stable direct current (DC) bus voltage, enhance the overall system efficiency and protect the battery from deep discharge and overcharge. To demonstrate the effectiveness of the proposed strategy, the obtained results were compared with other optimizers, including particle swarm optimization (PSO), salp swarm algorithm (SSA), artificial eco-system optimizer (AEO), COOT optimizer, and political optimizer (PO). The comparison confirmed the superiority of the proposed strategy in terms of minimum operating energy cost (0.1577c€/kW), high efficiency (87.395%) and final SoC (33.268%).

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  • Ferahtia, Seydali & Rezk, Hegazy & Abdelkareem, Mohammad Ali & Olabi, A.G., 2022. "Optimal techno-economic energy management strategy for building’s microgrids based bald eagle search optimization algorithm," Applied Energy, Elsevier, vol. 306(PB).
    • Handle: RePEc:eee:appene:v:306:y:2022:i:pb:s0306261921013568
    DOI: 10.1016/j.apenergy.2021.118069
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    References listed on IDEAS

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    1. Mohana Alanazi & Abdulaziz Alanazi & Zulfiqar Ali Memon & Ahmed Bilal Awan & Mohamed Deriche, 2024. "Multi-Objective Energy Management in Microgrids: Improved Honey Badger Algorithm with Fuzzy Decision-Making and Battery Aging Considerations," Energies, MDPI, vol. 17(17), pages 1-31, September.
    2. Ferahtia, Seydali & Rezk, Hegazy & Olabi, A.G. & Alhumade, Hesham & Bamufleh, Hisham S. & Doranehgard, Mohammad Hossein & Abdelkareem, Mohammad Ali, 2022. "Optimal techno-economic multi-level energy management of renewable-based DC microgrid for commercial buildings applications," Applied Energy, Elsevier, vol. 327(C).
    3. Ferahtia, Seydali & Houari, Azeddine & Cioara, Tudor & Bouznit, Mohammed & Rezk, Hegazy & Djerioui, Ali, 2024. "Recent advances on energy management and control of direct current microgrid for smart cities and industry: A Survey," Applied Energy, Elsevier, vol. 368(C).
    4. Li, Ze & Guo, Junfei & Gao, Xinyu & Yang, Xiaohu & He, Ya-Ling, 2023. "A multi-strategy improved sparrow search algorithm of large-scale refrigeration system: Optimal loading distribution of chillers," Applied Energy, Elsevier, vol. 349(C).
    5. Ziad M. Ali & Martin Calasan & Shady H. E. Abdel Aleem & Francisco Jurado & Foad H. Gandoman, 2023. "Applications of Energy Storage Systems in Enhancing Energy Management and Access in Microgrids: A Review," Energies, MDPI, vol. 16(16), pages 1-41, August.
    6. Yin, Linfei & Cao, Xinghui & Liu, Dongduan, 2023. "Weighted fully-connected regression networks for one-day-ahead hourly photovoltaic power forecasting," Applied Energy, Elsevier, vol. 332(C).
    7. Tostado-Véliz, Marcos & Kamel, Salah & Aymen, Flah & Rezaee Jordehi, Ahmad & Jurado, Francisco, 2022. "A Stochastic-IGDT model for energy management in isolated microgrids considering failures and demand response," Applied Energy, Elsevier, vol. 317(C).
    8. Seydali Ferahtia & Hegazy Rezk & Rania M. Ghoniem & Ahmed Fathy & Reem Alkanhel & Mohamed M. Ghonem, 2023. "Optimal Energy Management for Hydrogen Economy in a Hybrid Electric Vehicle," Sustainability, MDPI, vol. 15(4), pages 1-19, February.
    9. Deng, Xiangtian & Zhang, Yi & Jiang, Yi & Zhang, Yi & Qi, He, 2024. "A novel operation method for renewable building by combining distributed DC energy system and deep reinforcement learning," Applied Energy, Elsevier, vol. 353(PB).
    10. Hegazy Rezk & Rania M. Ghoniem & Seydali Ferahtia & Ahmed Fathy & Mohamed M. Ghoniem & Reem Alkanhel, 2022. "A Comparison of Different Renewable-Based DC Microgrid Energy Management Strategies for Commercial Buildings Applications," Sustainability, MDPI, vol. 14(24), pages 1-22, December.
    11. Sheng, Wanxing & Li, Rui & Yan, Tao & Tseng, Ming-Lang & Lou, Jiale & Li, Lingling, 2023. "A hybrid dynamic economics emissions dispatch model: Distributed renewable power systems based on improved COOT optimization algorithm," Renewable Energy, Elsevier, vol. 204(C), pages 493-506.

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