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Optimal Prosumer Operation with Consideration for Bounded Rationality in Peer-to-Peer Energy Trading Systems

Author

Listed:
  • Jianhong Hao

    (School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Ting Huang

    (School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Yi Sun

    (School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Xiangpeng Zhan

    (Marketing Service Center, State Grid Fujian Electric Power Co., Ltd., Xiamen 361006, China)

  • Yu Zhang

    (State Grid Energy Research Institute Co., Ltd., Beijing 100083, China)

  • Peng Wu

    (State Grid Energy Research Institute Co., Ltd., Beijing 100083, China)

Abstract

With the large-scale development of distributed energy on the demand side, the trend of “supply exceeding demand” has gradually become prominent, and regional peer-to-peer (P2P) energy trading has become an important measure to improve the local consumption of distributed energy. However, most existing studies usually assume that prosumers behave entirely rationally with the goal of maximum benefit, which has been proved to deviate from the observed actual behaviors. Aiming at the optimal energy of prosumers participating in the P2P market, a prospect theory-based two-stage stochastic optimization model considering the bounded rationality was proposed to accurately simulate the decision-making behavior. Then, a benefit maximization model for the energy trading service provider (ETSP) was constructed considering the power flow constraint to ensure the safe operation of the system. Finally, an improved R-ADMM algorithm considering timeout was proposed to solve the above model and improve the convergence speed. The effectiveness of the proposed model and algorithm was verified via simulation.

Suggested Citation

  • Jianhong Hao & Ting Huang & Yi Sun & Xiangpeng Zhan & Yu Zhang & Peng Wu, 2024. "Optimal Prosumer Operation with Consideration for Bounded Rationality in Peer-to-Peer Energy Trading Systems," Energies, MDPI, vol. 17(7), pages 1-22, April.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:7:p:1724-:d:1369804
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    References listed on IDEAS

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    1. Wang, Zibo & Yu, Xiaodan & Mu, Yunfei & Jia, Hongjie & Jiang, Qian & Wang, Xiaoyu, 2021. "Peer-to-Peer energy trading strategy for energy balance service provider (EBSP) considering market elasticity in community microgrid," Applied Energy, Elsevier, vol. 303(C).
    2. Wang, Xiaoyu & Jia, Hongjie & Jin, Xiaolong & Mu, Yunfei & Wei, Wei & Yu, Xiaodan & Liang, Shuo, 2024. "Bi-level optimal operations for grid operator and low-carbon building prosumers with peer-to-peer energy sharing," Applied Energy, Elsevier, vol. 359(C).
    3. Li, Weiwei & Qian, Tong & Zhao, Wei & Huang, Wenwei & Zhang, Yin & Xie, Xuehua & Tang, Wenhu, 2023. "Decentralized optimization for integrated electricity–heat systems with data center based energy hub considering communication packet loss," Applied Energy, Elsevier, vol. 350(C).
    4. Jing, Rui & Xie, Mei Na & Wang, Feng Xiang & Chen, Long Xiang, 2020. "Fair P2P energy trading between residential and commercial multi-energy systems enabling integrated demand-side management," Applied Energy, Elsevier, vol. 262(C).
    5. Xia, Yuanxing & Xu, Qingshan & Chen, Lu & Du, Pengwei, 2022. "The flexible roles of distributed energy storages in peer-to-peer transactive energy market: A state-of-the-art review," Applied Energy, Elsevier, vol. 327(C).
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