Research on the Operation Mode of Shared Energy Storage of New Energy Station Groups under Incomplete Information: Energy Synergy and Capacity Leasing Mechanism

With the abolition of mandatory energy storage allocation policies for large-scale new energy stations, centralized shared energy storage has become a key means to reduce investment costs and improve the complementary efficiency of new energy sources. However, in practical engineering, the opacity of information interaction between new energy stations and shared energy storage systems leads to conflicts in multi-stakeholder benefit distribution. Traditional game theory methods struggle to effectively coordinate private information, resulting in insufficient interaction among participating entities. To address this, this paper proposes an operational model for clusters of new energy stations and shared energy storage under incomplete information. This model constructs a four-stage dynamic game framework, including capacity and type declaration, allocation decisionmaking, charging-discharging strategy optimization, and profit distribution. Simulation results show that the proposed method can effectively resolve benefit biases caused by information asymmetry: the rental price for high-volatility stations is $7 \%$ higher than that for low-volatility stations, quantifying the uncertainty risk premium; the Bayesian update mechanism maintains a stable accuracy of over $\mathbf{9 5 \%}$ in identifying the true types of stations; compared with the complete information game, the operator’s revenue increases by $7 \%$, and the dynamic investment payback period is shortened by $\mathbf{1. 6}$ years. This study provides new theoretical and methodological support for optimizing multi-agent collaborative shared energy storage systems.