Energy storage generators can enhance the grid connection efficiency of wind power generation and reduce the phenomenon of wind power abandonment, presenting a promising development prospect. In the control strategy of the energy storage station, the particle swarm optimization algorithm has better adaptability and convenience, but it has the drawback of being prone to getting stuck in local optima. In view of this defect, the chaotic improved particle swarm optimization (PSO) algorithm is adopted to control the energy storage power generation station. Due to the random, exhaustive, regular and sensitive characteristics of the chaotic particle swarm movement process, it can alternately achieve stable and continuous chaotic particle swarm changes, thereby achieving global optimization. Finally, a specific example is given to compare the effects before and after the improvement algorithm to verify the feasibility and practical application value of the algorithm.