An operation control strategy based on short-term wind power prediction for hybrid energy storage is proposed in order to improve the wind farm’s output characteristics. Firstly, the low frequency signals is extracted from the wind signal by analytical mode decomposition(AMD) method, the penalty parameter and kernel function parameter of support vector machines(SVM) were found by using improved cuckoo search algorithms(ICSA) to predict the future wind power. Then, the power fluctuation index of the 1min time scale and the 30min time scale of low frequency predicted signal is established to judge whether the battery is triggered. If triggered, the cut-off frequency of low frequency predicted signals is adjusted to meet the requirement of grid-connected and determine the instruction of compensation power for battery. Finally, the cut-off frequency of original wind power is adjusted adaptively based on the state of charge(SOC) of battery and the instruction of compensation power of battery, the high frequency component is compensated by super capacitor through fuzzy control. The simulation results show that the proposed strategy can smooth the fluctuation of wind power effectively, reduce the number of battery recycling greatly, ensure the smooth capacity of battery, avoid overcharging and over discharging, extend the life of battery.