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Research on Renewable Energy Trading Strategies Based on Evolutionary Game Theory

Author

Listed:
  • Fei Huang

    (Guangxi Power Exchange Center Co., Ltd., Nanning 530023, China)

  • Hua Fan

    (Guangxi Power Exchange Center Co., Ltd., Nanning 530023, China)

  • Yunlong Shang

    (Guangxi Power Exchange Center Co., Ltd., Nanning 530023, China)

  • Yuankang Wei

    (Guangxi Power Exchange Center Co., Ltd., Nanning 530023, China)

  • Sulaiman Z. Almutairi

    (Department of Electrical Engineering, College of Engineering, Prince Sattam bin Abdulaziz University, Al Kharj 16278, Saudi Arabia)

  • Abdullah M. Alharbi

    (Department of Electrical Engineering, College of Engineering in Wadi Addawasir, Prince Sattam bin Abdulaziz University, Wadi Addawasir 11991, Saudi Arabia)

  • Hengrui Ma

    (Hubei Engineering and Technology Research Center for AC/DC Intelligent Distribution Network, School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
    School of Electrical and Automation, Wuhan University, Wuhan 430072, China)

  • Hongxia Wang

    (Hubei Engineering and Technology Research Center for AC/DC Intelligent Distribution Network, School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
    School of Electrical and Automation, Wuhan University, Wuhan 430072, China
    Department of Electrical & Computer Engineering, University of Denver, Denver, CO 80208, USA)

Abstract

The authors construct a tripartite evolutionary game model that considers renewable energy, traditional coal-fired power plants, and market users. We propose multiple income matrices under different strategies, conduct evolutionary stability analysis, and form a series of assumptions that meet the stability of the game. We also simulate and analyze the impact of key factors—such as assessment costs, different pricing behaviors of coal-fired power plants, electricity prices of renewable energy, and green electricity demand—on the stability of the game. In addition, the market equilibrium points that can be achieved by optimizing trading strategies and their optimization status in promoting renewable energy consumption are analyzed. Based on the operational characteristics of the Guangxi electricity market in China and the trading situation of renewable energy, an evolutionary game method is applied to conduct empirical research. The trading behavior and evolution of all parties in the market are fully analyzed and are then applied to the construction and mechanism improvement of the electricity market.

Suggested Citation

  • Fei Huang & Hua Fan & Yunlong Shang & Yuankang Wei & Sulaiman Z. Almutairi & Abdullah M. Alharbi & Hengrui Ma & Hongxia Wang, 2024. "Research on Renewable Energy Trading Strategies Based on Evolutionary Game Theory," Sustainability, MDPI, vol. 16(7), pages 1-26, March.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:7:p:2671-:d:1363049
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    References listed on IDEAS

    as
    1. Chen, Rongkai & Fan, Ruguo & Wang, Dongxue & Yao, Qianyi, 2023. "Effects of multiple incentives on electric vehicle charging infrastructure deployment in China: An evolutionary analysis in complex network," Energy, Elsevier, vol. 264(C).
    2. Hu, Yu & Chi, Yuanying & Zhou, Wenbing & Li, Jialin & Wang, Zhengzao & Yuan, Yongke, 2023. "The interactions between renewable portfolio standards and carbon emission trading in China: An evolutionary game theory perspective," Energy, Elsevier, vol. 271(C).
    3. Wang, Delu & Li, Chunxiao & Mao, Jinqi & Yang, Qing, 2023. "What affects the implementation of the renewable portfolio standard? An analysis of the four-party evolutionary game," Renewable Energy, Elsevier, vol. 204(C), pages 250-261.
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