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

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.

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Publication Details

Journal
Sustainability
Published
2025-03-28
DOI
https://doi.org/10.3390/su17073020
Citations
2
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
1.46

Funders

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article

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

Jiangping Liu, Bolun Xu, Xue Liu, Wei Zhang et al.
2 citations
Sustainability
Smart Grid Energy Management
1.46
article

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

Jiangping Liu, Bolun Xu, Xue Liu, Wei Zhang, Guang Hu, Xue Cui, Jun Zhao
article en
2 citations

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.

SustainabilityVol. 17(7)
Wuhan University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 19%
Smart Grid Energy Management
1.46
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Master–Slave Game Pricing Strategy of Time-of-Use Electricity Price of Electricity Retailers Considering Users’ Electricity Utility and Satisfaction — Jiangping Liu, Bolun Xu, et al. · Sustainability (2025) | TGRS Research Map | TGRS