Aiming at the problem that a large number of electric vehicles randomly connected to the grid poses a huge challenge to the security of the power grid, this paper proposes a strategy to guide the orderly charging of electric vehicles by using the time-of-use electricity price policy. Firstly, an orderly charging scheduling model for electric vehicles taking into account the response level to the policy is constructed. Then, a hybrid algorithm combining Spider Wasp Optimization (SWO) and Particle Swarm Optimization (PSO) is used to optimize the peak-valley electricity price period. Finally, by using the Monte Carlo and probability statistics theory methods to simulate the daily charging load of electric vehicles, the experiment of different response level are carried out. And results of different optimization methods for solving the scheduling model are compared. Comparison results show that the proposed method achieves the smallest peak to valley difference with the lest iterations. The proposed method can provides an effective strategy for peak shaving and valley filling.