Stackelberg Game for Bilateral Transactions between Energy Storage and Wind Farms Considering the Day-Ahead Electricity Market

The participation of wind farms in the former energy market faces challenges such as power fluctuations and energy storage construction costs. To this end, this paper proposes a joint energy storage operation scheme for multiple wind farms based on a leasing model, which assists wind farms in bidding for participation in the former energy market through leasing services, thereby enhancing energy storage efficiency and maximizing economic benefits. In this paper, based on the Weibull probability distribution to portray the uncertainty of wind power, and considering the lifetime capacity loss caused by charging and discharging of energy storage, we construct a bilateral transaction model aiming at maximizing the multi-objective revenue of wind farms and shared energy storage. The trading strategy is designed based on the Stackelberg game framework and solved jointly by the improved genetic algorithm and interior point method. By exploring the effects of different lease price intervals on the overall system performance, and analyzing the system state under multiple charging and discharging scenarios. The results show that a reasonable lease price range can significantly improve the energy storage system utilization and wind farm revenue. The program provides new ideas to enhance the economic benefits of wind farms and promote the application of shared energy storage, and promotes the wide application of shared energy storage systems.