A reactive power optimization method for wind and solar power storage and distribution networks based on the Multi Objective Sand Cat swarm optimization (MOSCSO) is proposed to address the problems of slow convergence speed and easy falling into local optima in existing intelligent optimization algorithms for reactive power optimization in distribution networks. MOSCSO integrates the update and selection mechanism of external save sets in multi-objective algorithms, and has good global optimization ability. At the same time, the unique search and attack population update method of the sand cat swarm algorithm ensures its fast convergence speed and good optimization ability. Establish an IEEE 33 node system mathematical model with Energy Storage System (ESS) as the control variable, and apply MOSCSO for simulation verification. The results demonstrate that the proposed method in this paper can reduce grid losses and improve grid stability while balancing the wind and solar power generation system. Compared with traditional algorithms, the results verify the effectiveness and stability of MOSCSO in the reactive power optimization model of this paper.