A Multi-Subject Game-Based Operation Strategy for VPPs Integrating Wind-Solar-Storage

• Published in: Sustainability Vol. 15; no. 7; p. 6278
• Main Authors: Liu, Hengyu, Zhao, Qingqi, Liu, Yang, Xing, Zuoxia, Hu, Dawei, Zhang, Pengfei, Zhang, Zhi, Sun, Jiazheng
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.04.2023
• Subjects: Alternative energy sources; Carbon; Demand side management; Efficiency; Electric vehicles; Electricity; Electricity distribution; Energy consumption; Energy management; Energy storage; Game theory; Industrial plant emissions; Linear programming; Methods; Operating costs; Optimization; Power plants; Renewable resources; Scheduling; Solar energy; Sustainability; Wind power; China
• ISSN: 2071-1050; 2071-1050
• DOI: 10.3390/su15076278

Along with the continuous development of renewable energy sources (RES) such as wind power and photovoltaic, a large proportion of RES were connected to the power grid. However, the volatility and intermittency of RES threaten the safe and stable operation of the power system. Virtual power plants (VPPs) were introduced to solve such problems. In order to study the cooperation mode of integrating wind-solar-storage for multi VPPs, this paper established multi-objective individual and joint dispatching model for single VPP and multi VPPs with wind-solar-storage, respectively. Then, this paper analyzed the cooperation and the fair distribution of benefits between VPPs. By establishing the competitive strategies of the participating subjects and integrating the Shapley value to effectively distribute the benefits, the cooperative game theory was applied to effectively enhance the benefit in the VPP, to maximize the economic benefits, and to reduce the RES uncertainty risks and carbon emissions, which provided new ideas for the subsequent research on the optimal operation of RES and their engineering applications. NSGA-II was adopted to solve the multi-objective optimization problem. The strategy achieved a 10.1% reduction on the original peak load. It could effectively reduce the peak load of the VPP and ensure the accuracy of load regulation, to reach 12% of the total capacity of the VPP.