Abstract: The increasing integration of new energy generating units into the power system and the rising penetration rate of new energy generation pose challenges to the safe, stable, and flexible economic operation of the power grid. A control method for wind storage power station to actively participate in the power grid voltage regulation is proposed based on the the voltage regulation characteristics of grid-connected wind storage power station. The wind power output of typical days is obtained by Latin hypercube sampling (LHS) scene generation method and the Kantorovich distance scene reduction technique. Considering absence of any correlation between wind power output and grid load, the load rates of both the wind storage power station and the local grid are considered, so as to determine the control objective and control principle of the wind storage power station’s active participation in the voltage regulation of the grid. By establishing an intelligent algorithm-based double-layer optimization model of wind storage power station, the reactive power is optimized for each reactive power compensation link of wind storage power station, thereby achieving active voltage regulation control. The intelligent algorithm of particle swarm optimization (PSO) is adopted in the upper layer model to determine the voltage control target of the node union for the lower layer. The lower model adopts multi-objective particle swarm optimization (MOPSO) intelligent algorithm to get the simulation results of voltage mean square error and active power loss. Finally, an example is provided to verify the validity and reliability of the method.