An intelligent electric vehicle orderly charging and discharging strategy is proposed to reduce the impact of a large number of electric vehicles disorderly charging on the power grid. Based on the idea of a cooperative game, a dynamic time-sharing optimization charging and discharging model is established with the goal of maximizing the benefits of the cooperative alliance between electric vehicle agents and electric vehicle users. A particle swarm optimization algorithm is used to solve the dynamic time-sharing trading price between agents and users and guide electric vehicle charging and discharging period planning. The actual calculation results prove the effectiveness and economy of the proposed strategy. Through comparative analysis with the fixed electricity price strategy, it is shown that the proposed strategy can not only effectively reduce the peak-valley difference, and avoid the load "new peak", but also improve the revenue of agents and users. Further comparing the influence of the entry on the network of different numbers of electric vehicles on the optimization effect, it is found that the optimization effect is more obvious with the increase in the number of electric vehicles connected to the grid. This work is supported by National Natural Science Foundation of China (No. 51607105).