A Multi-Agent Game-Based Incremental Distribution Network Source–Load–Storage Collaborative Planning Method Considering Uncertainties

• Published in: Frontiers in energy research Vol. 10
• Main Authors: Yang, Nan, He, Ye, Dong, BangTian, Qin, Tao, Ding, Li, Yang, XingLei, Yao, JunWei, Huang, YueHua, Wang, ShuoHao, Zhang, Lei, Zhu, BinXin, Xiong, Wei, Ren, YuLun
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 14-03-2022
• Subjects: collaborative planning; dynamic–static joint game; iterative search method; multi-agent planning; robust optimization
• ISSN: 2296-598X; 2296-598X
• DOI: 10.3389/fenrg.2022.803716

How to obtain the optimal decision-making scheme based on the investment behavior of various stakeholders is an important issue that needs to be solved urgently in incremental distribution network planning. To this end, this article introduces the virtual player “Nature” to realize the combination of the game theory and robust optimization and proposes an incremental distribution network source–load–storage collaborate planning method with a multi-agent game. First, the planning and decision-making models of a DG investment operator, a distribution network (DN) company, power consumers, and a distributed energy storage (DES) investment operator are constructed, respectively. Then the static game behaviors between the DG investment operator and distribution network company, as well as the DG investment operator and the DES investment operator, are analyzed based on the transfer relations between these four participants. At the same time, robust optimization is used to deal with the uncertainty of the DG output, and the virtual player “Nature” is introduced to study the dynamic game behavior between the DG investment operator and the distribution company. Finally, a dynamic–static joint game planning model is proposed. The simulation results verify the correctness and effectiveness of the proposed method.