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Optimal operation of distribution networks and multiple community energy prosumers based on mixed game theory

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  • Zhao, Bingxu
  • Duan, Pengfei
  • Fen, Mengdan
  • Xue, Qingwen
  • Hua, Jing
  • Yang, Zhuoqiang

Abstract

Community energy systems are currently transitioning from conventional consumers to prosumers. Under this context, the coordinated management of multiple community energy prosumers (CEPs) is explored this study in accordance with the same distribution network. The aim of this study is to facilitate the coordination of unit operations, demand response, and peer-to-peer (P2P) energy trading among CEP coalitions based on the distribution network operator (DSO) by setting electricity prices. Thus, a mixed game-based optimal operation model of DSO and CEP alliances is developed, integrating Stackelberg and cooperative games. The upper layer aims at maximizing DSO revenue, whereas the lower layer minimizes the operation costs of CEP cooperative alliances while allocating benefits in accordance with the Nash-Harsanyi bargaining theory. The model is solved with a two-stage distributed algorithm that integrates the bisection method and the alternating direction method of multipliers (ADMM). Furthermore, cloud energy storage (CES) is introduced to optimize the economics of CEP. The effectiveness of the proposed method is verified through a case study, demonstrating the collaborative optimal scheduling of multiple CEPs and reasonable benefit distribution. Accordingly, this study is conducive to expediting the effective and economical management of CEPs under distribution networks.

Suggested Citation

  • Zhao, Bingxu & Duan, Pengfei & Fen, Mengdan & Xue, Qingwen & Hua, Jing & Yang, Zhuoqiang, 2023. "Optimal operation of distribution networks and multiple community energy prosumers based on mixed game theory," Energy, Elsevier, vol. 278(PB).
    • Handle: RePEc:eee:energy:v:278:y:2023:i:pb:s0360544223014196
    DOI: 10.1016/j.energy.2023.128025
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    References listed on IDEAS

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    1. Suryakiran, B.V. & Nizami, Sohrab & Verma, Ashu & Saha, Tapan Kumar & Mishra, Sukumar, 2023. "A DSO-based day-ahead market mechanism for optimal operational planning of active distribution network," Energy, Elsevier, vol. 282(C).
    2. Dong, Lei & Zhang, Shiming & Zhang, Tao & Wang, Zibo & Qiao, Ji & Pu, Tianjiao, 2024. "DSO-prosumers dual-layer game optimization based on risk price guidance in a P2P energy market environment," Applied Energy, Elsevier, vol. 361(C).
    3. Wang, Y.X. & Chen, J.J. & Zhao, Y.L. & Xu, B.Y., 2024. "Incorporate robust optimization and demand defense for optimal planning of shared rental energy storage in multi-user industrial park," Energy, Elsevier, vol. 301(C).
    4. Zhang, Sen & Hu, Weihao & Cao, Xilin & Du, Jialin & Zhao, Yincheng & Bai, Chunguang & Liu, Wen & Tang, Ming & Zhan, Wei & Chen, Zhe, 2024. "A two-stage robust low-carbon operation strategy for interconnected distributed energy systems considering source-load uncertainty," Applied Energy, Elsevier, vol. 368(C).
    5. Zhao, Wenna & Ma, Kai & Yang, Jie & Guo, Shiliang, 2024. "A multi-time scale demand response scheme based on noncooperative game for economic operation of industrial park," Energy, Elsevier, vol. 302(C).
    6. Yang, Yuyan & Xu, Xiao & Pan, Li & Liu, Junyong & Liu, Jichun & Hu, Weihao, 2024. "Distributed prosumer trading in the electricity and carbon markets considering user utility," Renewable Energy, Elsevier, vol. 228(C).

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