By considering the very short-term wind power forecasting information，an optimal control strategy for energy storage system（ESS）based on the variable progressive steps and expected outputs is proposed.The strategy can improve the ESS utilization by setting the range of state of charge（SOC）limits and building the cyclical charge and discharge mode within SOC critical limits based on progressive control intervals，while guaranteeing the ESS operation state by restricting the times of charge-discharge state transition in each progressive control interval.To build the ESS charge and discharge strategy，the single charge and discharge interval is studied as the control progressive step.Moreover，a multi-objective optimization model is developed to increase the time of the progressive step and reduce the rate of fluctuation of the expected output，while coordinately controlling the wind power output and the expected output in the cyclical charge and discharge mode within the critical limits.Full use is made of ESS and the times of state transitions are reduced，as well as the rate of fluctuation of the expected output，which is conducive to improving the capability of dispatch.Finally，the Pareto optimal solution is obtained by the fast and elitist non-dominant sorting genetic algorithm.The effectiveness of the proposed method is verified through actual wind farm operating data.