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ARTICLE
Peer-to-Peer Energy Trading Method of Multi-Virtual Power Plants Based on Non-Cooperative Game
Yancheng Power Supply Company of State Grid Jiangsu Electric Power Co., Ltd., Yancheng, 224008, China
* Corresponding Author: Jingjing Bai. Email:
Energy Engineering 2023, 120(5), 1163-1183. https://doi.org/10.32604/ee.2023.025553
Received 19 July 2022; Accepted 25 October 2022; Issue published 20 February 2023
Abstract
The current electricity market fails to consider the energy consumption characteristics of transaction subjects such as virtual power plants. Besides, the game relationship between transaction subjects needs to be further explored. This paper proposes a Peer-to-Peer energy trading method for multi-virtual power plants based on a non-cooperative game. Firstly, a coordinated control model of public buildings is incorporated into the scheduling framework of the virtual power plant, considering the energy consumption characteristics of users. Secondly, the utility functions of multiple virtual power plants are analyzed, and a non-cooperative game model is established to explore the game relationship between electricity sellers in the Peer-to-Peer transaction process. Finally, the influence of user energy consumption characteristics on the virtual power plant operation and the Peer-to-Peer transaction process is analyzed by case studies. Furthermore, the effect of different parameters on the Nash equilibrium point is explored, and the influence factors of Peer-to-Peer transactions between virtual power plants are summarized. According to the obtained results, compared with the central air conditioning set as constant temperature control strategy, the flexible control strategy proposed in this paper improves the market power of each VPP and the overall revenue of the VPPs. In addition, the upper limit of the service quotation of the market operator have a great impact on the transaction mode of VPPs. When the service quotation decreases gradually, the P2P transaction between VPPs is more likely to occur.Keywords
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