Peer-to-peer electricity trading of interconnected flexible distribution networks based on non-cooperative games

Zhao, Jinli, Tian, Zhen, Ji, Haoran, Ji, Jie, Yan, Jinyue, Wu, Jianzhong ORCID: https://orcid.org/0000-0001-7928-3602, Li, Peng and Wang, Chengshan 2023. Peer-to-peer electricity trading of interconnected flexible distribution networks based on non-cooperative games. International Journal of Electrical Power & Energy Systems 145 , 108648. 10.1016/j.ijepes.2022.108648

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Abstract

With the integration of power electronic devices represented by soft open points (SOPs), distribution networks have gradually evolved into interconnected flexible distribution networks (FDNs). Considering the deregulation of electricity market and user privacy, multiple stakeholders have participated in the operation of FDNs. Peer-to-peer (P2P) electricity trading is promising to alleviate operational problems of interconnected FDNs. As multiple regions pursue the maximum profits individually, non-cooperative game methods can be utilized to realize fair profit allocation in P2P trading. In this paper, a non-cooperative game-based P2P trading method is proposed to meet the electricity trading needs of multi-region interconnected FDNs. First, based on non-cooperative games, a two-layer P2P electricity trading framework is established to realize cost reduction and voltage profile improvement of multi-region interconnected FDNs. Then, a P2P trading adjustment mechanism is designed to improve the operational profits of SOP, in which spatial active power trading adjustment, temporal dispatching of energy storage (ES) link and reactive power support are incorporated. Finally, the effectiveness of the proposed method is verified based on a practical distribution network with four-terminal SOP in Tianjin. The results show that the proposed P2P electricity trading method can promote the economic operation performance of interconnected FDNs and improve the operational profit of SOP.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Publisher:	Elsevier
ISSN:	0142-0615
Date of Acceptance:	14 September 2022
Last Modified:	08 Nov 2022 11:01
URI:	https://orca.cardiff.ac.uk/id/eprint/153471

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