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Master–Slave Game Pricing Strategy of Time-of-Use Electricity Price of Electricity Retailers Considering Users’ Electricity Utility and Satisfaction

Author

Listed:
  • Jiangping Liu

    (Hubei Power Exchange Center, Wuhan 430077, China)

  • Wei Zhang

    (Hubei Power Exchange Center, Wuhan 430077, China)

  • Guang Hu

    (Hubei Power Exchange Center, Wuhan 430077, China)

  • Bolun Xu

    (Hubei Power Exchange Center, Wuhan 430077, China)

  • Xue Cui

    (School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China)

  • Xue Liu

    (School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China)

  • Jun Zhao

    (School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China)

Abstract

With the establishment of a competitive electricity retail market, how to optimize the retail electricity price mechanism has become the core of all kinds of retail companies to explore. Aiming at the pricing problem of time-of-use electricity price, this paper proposes a pricing strategy based on the master–slave game model. Firstly, considering the user’s electricity utility and satisfaction factors, the comprehensive benefit function of the electricity selling company with electricity price as the decision variable and the user’s comprehensive benefit function with electricity consumption as the decision variable are established, respectively. Then, a master–slave game model is established with the electricity selling company as the leader and the user as the follower, and the reverse induction method is used to solve the model. Finally, considering the influencing factors of user response ability, different electricity price types and user types are set up for simulation. The results show that the revenue of electricity retailers can be increased by up to 170,000 yuan, and the average electricity price of users can be reduced by up to 8 yuan. It is verified that the model can effectively achieve a win-win situation for both sides and promote peak shaving and valley filling. At the same time, it is proved that the role of the model is positively related to electricity price flexibility and user response capability.

Suggested Citation

  • Jiangping Liu & Wei Zhang & Guang Hu & Bolun Xu & Xue Cui & Xue Liu & Jun Zhao, 2025. "Master–Slave Game Pricing Strategy of Time-of-Use Electricity Price of Electricity Retailers Considering Users’ Electricity Utility and Satisfaction," Sustainability, MDPI, vol. 17(7), pages 1-19, March.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:7:p:3020-:d:1622978
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    References listed on IDEAS

    as
    1. Gang Liang & Yu Wang & Bing Sun & Zheng Zhang, 2024. "An Optimization Method for the Distributed Collaborative Operation of Multilateral Entities Considering Dynamic Time-of-Use Electricity Price in Active Distribution Network," Energies, MDPI, vol. 17(2), pages 1-19, January.
    2. Amiri-Pebdani, Sima & Alinaghian, Mahdi & Safarzadeh, Soroush, 2022. "Time-Of-Use pricing in an energy sustainable supply chain with government interventions: A game theory approach," Energy, Elsevier, vol. 255(C).
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