Double-layer Game Optimization Strategy for Virtual Power Plants Considering Free Trading of Energy Storage Systems

• Published in: 2024 7th International Conference on Energy, Electrical and Power Engineering (CEEPE) pp. 1291 - 1296
• Main Authors: Li, Zhuangzhuang, Liu, Wei, Zhang, Junfang, Xing, Xinran, Chen, Xi, Li, Yantao, Lang, Jinqi, Hua, Fan
• Format: Conference Proceeding
• Language: English
• Published: IEEE 26.04.2024
• Subjects: double-layer optimization; energy storage system; Games; Mathematical models; non-cooperative game; particle swarm algorithm; Power system reliability; Simulation; Smart grids; Spatiotemporal phenomena; virtual power plant; Virtual power plants
• DOI: 10.1109/CEEPE62022.2024.10586460

With the vigorous promotion of new energy and energy storage technology, virtual power plants (VPP), an important energy aggregation subject of smart grid construction and global energy interconnection, have broad development space. However, the traditional centralized control method makes it difficult to meet the scheduling requirements of multi-VPPs. Hence, we propose a double-layer game optimization strategy for VPP that considers the free trading of energy storage systems (ESS). To solve the efficient control of VPP on source load storage and promote the coordination and interaction of multi-VPPs. The proposed method establishes a double-layer game model of the VPP, and the improved double-level particle swarm optimization algorithm is used to maximize the inter-plant revenue and minimize the internal generation cost of the VPP. Furthermore considering the free trading strategy of the ESS, five energy storage charging and discharging intervals are divided to make full use of the adjustable resources in each VPP. Eventually, a simulation model is performed in MATLAB to demonstrate the proposed control method's effectiveness and economy.