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Optimal Scheduling of Multi-Energy Complementary Systems Based on an Improved Pelican Algorithm

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  • Hongbo Zou

    (College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China
    Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station, China Three Gorges University, Yichang 443002, China)

  • Jiehao Chen

    (College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China)

  • Fushuan Wen

    (Hainan Institute, Zhejiang University, Sanya 572025, China)

  • Yuhong Luo

    (College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China)

  • Jinlong Yang

    (College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China)

  • Changhua Yang

    (College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China)

Abstract

In recent years, the global power industry has experienced rapid development, with significant advancements in the source, network, load sectors, and energy storage technologies. The secure, reliable, and economical operation of power systems is a critical challenge. Due to the stochastic nature of intermittent renewable energy generation and the coupled time-series characteristics of energy storage systems, it is essential to simulate uncertain variables accurately and develop optimization algorithms that can effectively tackle multi-objective problems in economic dispatch models for microgrids. This paper proposes a pelican algorithm enhanced by multi-strategy improvements for optimal generation scheduling. We establish eight scenarios with and without pumped storage across four typical seasons—spring, summer, autumn, and winter—and conduct simulation analyses on a real-world case. The objective is to minimize the total system cost. The improved pelican optimization algorithm (IPOA) is compared with other leading algorithms, demonstrating the validity of our model and the superiority of IPOA in reducing costs and managing complex constraints in optimization.

Suggested Citation

  • Hongbo Zou & Jiehao Chen & Fushuan Wen & Yuhong Luo & Jinlong Yang & Changhua Yang, 2025. "Optimal Scheduling of Multi-Energy Complementary Systems Based on an Improved Pelican Algorithm," Energies, MDPI, vol. 18(2), pages 1-26, January.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:2:p:365-:d:1568257
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    References listed on IDEAS

    as
    1. Kangping Wang & Pengjiang Ge & Naixin Duan & Jili Wang & Jinli Lv & Meng Liu & Bin Wang, 2023. "The Multi-Objective Optimal Scheduling of the Water–Wind–Light Complementary System Based on an Improved Pigeon Flock Algorithm," Energies, MDPI, vol. 16(19), pages 1-18, September.
    2. Nwulu, Nnamdi I. & Xia, Xiaohua, 2017. "Optimal dispatch for a microgrid incorporating renewables and demand response," Renewable Energy, Elsevier, vol. 101(C), pages 16-28.
    3. Chaoyang Chen & Hualing Liu & Yong Xiao & Fagen Zhu & Li Ding & Fuwen Yang, 2022. "Power Generation Scheduling for a Hydro-Wind-Solar Hybrid System: A Systematic Survey and Prospect," Energies, MDPI, vol. 15(22), pages 1-31, November.
    4. Xiaohui Yang & Jiating Long & Peiyun Liu & Xiaolong Zhang & Xiaoping Liu, 2018. "Optimal Scheduling of Microgrid with Distributed Power Based on Water Cycle Algorithm," Energies, MDPI, vol. 11(9), pages 1-17, September.
    5. Shi, Mengshu & Wang, Weiye & Han, Yaxuan & Huang, Yuansheng, 2022. "Research on comprehensive benefit of hydrogen storage in microgrid system," Renewable Energy, Elsevier, vol. 194(C), pages 621-635.
    6. Bo, Yaolong & Xia, Yanghong & Wei, Wei & Li, Zichen & Zhao, Bo & Lv, Zeyan, 2023. "Hyperfine optimal dispatch for integrated energy microgrid considering uncertainty," Applied Energy, Elsevier, vol. 334(C).
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