Existing intelligent optimization algorithms for reactive power optimization in distribution networks are perplexed by problems of slow convergence speed and easy falling into local optima.Here,a new approach based on the Multi-Objective Sand Cat Swarm Optimization (MOSCSO) is proposed to solve the reactive power optimization of wind and solar power storage and distribution networks.MOSCSO integrates the update and selection mechanism of external save sets in multi-objective algorithms,and has good global optimization ability.Meanwhile,the unique search and attack population update method of the sand cat swarm algorithm ensures its fast convergence speed and good optimization ability.An IEEE 33 bus system mathematical model with Energy Storage System (ESS) was established as the control variable,and then the MOSCSO was applied for simulation verification.The results demonstrate that the proposed approach can reduce grid loss and improve grid stability while balancing the wind and solar power generation systems,which verify the effectiveness and stability of MOSCSO in reactive power optimization.