Wind storage combined power generation can ensure the reliable realization of the wind power grid connection plan to a certain extent, but its key technology cannot be separated from effective energy storage energy management and control. A double-layer fuzzy control strategy for energy storage is proposed in this paper. First, an improved genetic algorithm is used to optimize the adaptive neural fuzzy inference system to obtain future wind power. Then, combined with the actual energy storage charge state and the wind power grid-connected plan dynamic tracking adjustment requirements, the huff and puff power of the energy storage system is repeatedly modified by double-layer fuzzy control rules to ensure the safe working of the energy storage system and the multi-task execution of the power plan tracking target. Finally, the existing simulation platform and the actual operation data of the wind farm are used. The advantages of the proposed strategy are verified by comparing the simulation results with traditional fuzzy control. The simulation results show that the double-layer fuzzy control strategy can further improve the grid-connected power generation capacity of wind turbines while reducing the number of times the energy storage charge state exceeds the limit. This work is supported by National Natural Science Foundation of China (No. 61673226) and Project of Nantong Science and Technology Bureau (No. JC2018116).