Abstract：Aiming at the adverse effects of large-scale electric vehicle charging load on the distribution

network，based on vehicle to grid（V2G）technology，a V2G reactive dispatching strategy combining the nondominated sorting genetic algorithm and the local optimization of global objectives algorithm was proposed. The superstructure was based on the ordered charging strategy of electric vehicles based on the non-dominating ranking genetic algorithm，and the standard deviation of the user's starting charging time distribution was optimized with load mean square deviation，charging cost and voltage offset rate as the target，and the starting charging parameters that meet the needs of users were obtained. The sub-architecture was a local optimization algorithm for global targets，which optimizes the amount of reactive power compensation with voltage offset rate as the target for vehicles that can provide reactive power compensation. Finally，taking the IEEE100 node system as an example to simulate，it was found that this method can provide charging station operators with better load peak-valley difference，charging cost，voltage quality and other charging methods，and the hierarchical scheduling strategy can better ensure the safety and economy of the power grid compared with the single-layer scheduling strategy.

      Key words：vehicle to grid（V2G）；reactive power compensation；scheduling architecture；voltage deviation；recharger