Stackelberg game for shared energy storage and wind farm bilateral trading with multi-market participation

To address the high investment costs, low utilization, and long payback periods of single-service energy storage, this study proposes a shared energy storage strategy integrating wind-storage bilateral transactions and ancillary peak-shaving services. By leveraging multi-service synergy, the strategy improves energy storage utilization and economic benefits while optimizing WF's bidding strategies in the day-ahead market. A revenue maximization model is developed based on the Weibull distribution of wind power, incorporating capacity degradation costs. A Stackelberg game framework is formulated to determine optimal participation strategies for shared energy storage operators (SESO) and WFs, solved using a hybrid approach that combines an improved genetic algorithm and an interior-point method. Case studies demonstrate that, compared to single leasing, the proposed model increases SESO and WF benefits by 2.35 %, 5.69 %, and 6.81 %, respectively, while SESO revenue rises by 255.46 % compared to ancillary services alone. Additionally, the model reduces WF leasing costs, mitigates wind curtailment and grid deviation penalties, and enhances overall economic efficiency. This study provides a structured framework for wind-storage collaboration, offering theoretical insights into optimizing energy storage participation in electricity markets and supporting the advancement of smart grids and renewable energy integration.