LI Zhengxi, ZHOU Wanpeng, CHEN Laijun, et al. Optimal Allocation Strategy for Decentralized Shared Energy Storage in Renewable Energy Station Clusters Based on Cooperative Game Theory[J]. 2025, 53(6): 43-49.
LI Zhengxi, ZHOU Wanpeng, CHEN Laijun, et al. Optimal Allocation Strategy for Decentralized Shared Energy Storage in Renewable Energy Station Clusters Based on Cooperative Game Theory[J]. 2025, 53(6): 43-49. DOI: 10.20204/j.sp.2025.06006.
Optimal Allocation Strategy for Decentralized Shared Energy Storage in Renewable Energy Station Clusters Based on Cooperative Game Theory
To address the low utilization and economic efficiency of energy storage when individual renewable energy power stations are independently equipped with storage systems, this paper proposes a decentralized shared energy storage optimization allocation strategy for renewable energy power station clusters based on cooperative game theory. First, a decentralized shared energy storage architecture for renewable energy power station clusters is designed, and its operational mechanism is elucidated. Second, a cooperative game model for shared energy storage is established, aiming to maximize the total revenue of the renewable energy station cluster. The rated power and capacity of the decentralized shared energy storage are defined as decision variables. By leveraging the operational characteristics of multiple wind and solar energy stations under a shared collector station, the optimal energy storage capacity allocation across stations is determined. Finally, simulations analyze the impacts of different cooperation modes and curtailment penalties on shared energy storage revenue. Results demonstrate that the proposed method effectively exploits the complementary characteristics of participating stations, reducing their energy storage construction requirements while enhancing operational economic performance.