To improve the schedulability of wind-photovoltaic-storage hybrid system

the control model of the windphotovoltaic-storage hybrid system is established. Combined with the actual operation of the wind-photovoltaic power station

the power prediction results of the wind-photovoltaic-storage power station are expressed as fuzzy variables. It's actual power data curve is given

its short-term prediction curve is taken as the planned output curve.The objective is to minimize the root mean square error between the actual and the planned output curve

maximize the predicted qualification rate

slow charging and discharging rate

and maintain a reasonable range of energy storage

and generation limit of the wind-photovoltaic-storage power station and energy storage station is the constraint condition. The multi-objective task is tracked by the relevant opportunity target planning method. The fuzzy simulation and dynamic particle swarm optimization algorithm are used to solve the problem. The rolling calculation is carried out according to the ultra short-term prediction data

then the actual output curve in the control period is obtained. The simulation results show that

the energy storage control strategy is practical and the windphotovoltaic-storage hybrid system tracks the planned output curve well.