Asymmetric Nash bargaining-based community-centric energy sharing strategy for numerous prosumers

被引:2
|
作者
Yu, Hongfei [1 ]
Xu, Fucong [2 ]
Chen, Changming [1 ]
Chen, Yuge [3 ]
Zhang, Weijun [3 ]
Yang, Li [1 ]
Lin, Zhenzhi [1 ]
机构
[1] Zhejiang Univ, Coll Elect Engn, Hangzhou 310027, Peoples R China
[2] State Grid Fujian Elect Power Co Ltd, Fuzhou 350003, Peoples R China
[3] State Grid Fujian Elect Power Co Ltd, Elect Power Res Inst, Fuzhou 350003, Peoples R China
关键词
Distributed energy resources; Peer-to-peer energy sharing; Asymmetric nash bargaining; Bargaining power; Distributed optimization;
D O I
10.1016/j.energy.2025.134468
中图分类号
O414.1 [热力学];
学科分类号
摘要
The increasing of distributed energy resources has prompted the need for effective peer-to-peer energy sharing among prosumers. To reduce the complexity of energy sharing and encourage active participation among numerous prosumers, this paper proposes an asymmetric Nash bargaining (ANB) based community-centric energy sharing strategy. Firstly, a two-layer energy scheduling method with the coordination of community aggregators (CAs) is established for intra- and inter-community energy sharing. Secondly, the contributions of communities and prosumers to energy sharing are quantified, considering the risk of insufficient power supply from sharing renewable energy; and an ANB-based two-layer cooperative benefit allocation approach is proposed to sequentially allocate benefits at the community and prosumer layers. Finally, a distributed collaborative solving algorithm based on an improved alternating direction method of multipliers algorithm is proposed, achieving privacy protection and prosumers' efficient participation by reducing the shared data and leveraging the CAs' coordination. Case studies using real-world datasets demonstrate that the cooperative alliance's collective interests increased by 43.74 %, garnering high acceptance and effectively motivating prosumers' participation in energy sharing. The proposed algorithm shows a 57.14 % improvement in computational efficiency with numerous prosumers compared to the standard algorithm, and its stability has also been enhanced.
引用
收藏
页数:13
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