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Modeling of Collusion Behavior in the Electrical Market Based on Deep Deterministic Policy Gradient

Author

Listed:
  • Yifeng Liu

    (Hubei Electric Power Co., Ltd., Power Exchange Center, Wuhan 430073, China)

  • Jingpin Chen

    (Hubei Electric Power Co., Ltd., Power Exchange Center, Wuhan 430073, China)

  • Meng Chen

    (Hubei Electric Power Co., Ltd., Power Exchange Center, Wuhan 430073, China)

  • Zhongshi He

    (Hubei Electric Power Co., Ltd., Power Exchange Center, Wuhan 430073, China)

  • Ye Guo

    (Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China)

  • Chenghan Li

    (Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China)

Abstract

The evolution of the electricity market has brought the issues of market equilibrium and collusion to the forefront of attention. This paper introduces the Deep Deterministic Policy Gradient (DDPG) algorithm on the IEEE three-bus electrical market model. Specifically, it simulates the behavior of market participants through reinforcement learning (DDPG), and Nash equilibrium and the collusive equilibrium of the power market are simulated by setting different reward functions. The results show that, compared with the Nash equilibrium, collusion equilibrium can increase the price of nodal marginal electricity and reduce total social welfare.

Suggested Citation

  • Yifeng Liu & Jingpin Chen & Meng Chen & Zhongshi He & Ye Guo & Chenghan Li, 2024. "Modeling of Collusion Behavior in the Electrical Market Based on Deep Deterministic Policy Gradient," Energies, MDPI, vol. 17(22), pages 1-9, November.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:22:p:5807-:d:1525564
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    References listed on IDEAS

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