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Power Dispatch Stability Technology Based on Multi-Energy Complementary Alliances

Author

Listed:
  • Yiming Zhao

    (School of Cyber Science and Engineering, Southeast University, Nanjing 210000, China)

  • Chengjun Zhang

    (School of Cyber Science and Engineering, Southeast University, Nanjing 210000, China)

  • Changsheng Wan

    (School of Cyber Science and Engineering, Southeast University, Nanjing 210000, China)

  • Dong Du

    (School of Cyber Science and Engineering, Southeast University, Nanjing 210000, China)

  • Jing Huang

    (Nicholas School of the Environment, Duke University, Durham, NC 27708, USA)

  • Weite Li

    (School of Artificial Intelligence, Chongqing Technology and Business University, Chongqing 400067, China)

Abstract

In the context of growing global energy demand and increasingly severe environmental pollution, ensuring the stable dispatch of new energy sources and the effective management of power resources has become particularly important. This study focuses on the reliability and stability issues of new energy dispatch considering the complementary advantages of multiple energy types. It aims to enhance dispatch stability and energy utilization through an innovative Distributed Overlapping Coalition Formation (DOCF) model. A distributed algorithm utilizing tabu search is proposed to solve the complex optimization problem in power resource allocation. The overlapping coalitions consider synergies between different types of resources and intelligently allocate based on the heterogeneous demands of power loads and the supply capabilities of power stations. Simulation results demonstrate that DOCF can significantly improve power grid resource utilization efficiency and dispatch stability. Particularly in handling intermittent power resources such as solar and wind energy, the proposed model effectively reduces peak shaving time and improves the overall network energy efficiency. Compared with the preference relationship based on selfish and Pareto sequence, the PGG-TS algorithm based on BMBT has an average utility of 10.2% and 25.3% in terms of load, respectively. The methodology and findings of this study have important theoretical and practical value for guiding actual energy management practices and promoting the wider utilization of renewable energy.

Suggested Citation

  • Yiming Zhao & Chengjun Zhang & Changsheng Wan & Dong Du & Jing Huang & Weite Li, 2025. "Power Dispatch Stability Technology Based on Multi-Energy Complementary Alliances," Mathematics, MDPI, vol. 13(13), pages 1-26, June.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:13:p:2091-:d:1687522
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    References listed on IDEAS

    as
    1. Tianrui Zhang & Weibo Zhao & Quanfeng He & Jianan Xu, 2025. "Optimization of Microgrid Dispatching by Integrating Photovoltaic Power Generation Forecast," Sustainability, MDPI, vol. 17(2), pages 1-30, January.
    2. Jian Feng & Yifan Yao & Zhenfeng Liu, 2025. "Developing an optimal building strategy for electric vehicle charging stations: automaker role," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(5), pages 12091-12151, May.
    3. Torge Wolff & Astrid Nieße, 2023. "Dynamic Overlapping Coalition Formation in Electricity Markets: An Extended Formal Model," Energies, MDPI, vol. 16(17), pages 1-28, August.
    Full references (including those not matched with items on IDEAS)

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