This paper evaluates the capacity of electric vehicles(EV) as an important part of distributed energy storage systems to suppress regional load fluctuations in power grid. Firstly, based on cyber-physical-social system (CPSS), an artificial electric vehicle group is constructed in a software-defined manner, combining the private car travel statistics, power battery physical models and users’ response to time-of-use electricity prices or incentives. Then, the Monte Carlo method and central limit theorems are applied to simulate the charging and discharging behavior of the artificial EV group in different scenarios, thus, the mathematical expectation of time-division charge-discharge power is obtained as daily charge-discharge profile. And the simulation experiments are completed interms of the aspects as follows: 1) the differences in charge and discharge behaviors of users with different rational levels under the same price strategy, 2) the effect of charge and discharge behavior of electric vehicles on regional load variance under different price strategies and corresponding costs and benefits of the grid, 3) the changes in regional load variance reduction after the electric vehicle group is connected to the grid under different power battery parameters. Finally, the simulation results provide guidance for the grid to develop a reasonable price strategy, and also show the key factors affecting the electric vehicles as distributed energy storage systems to suppress the load variance. Besides, fundamental technical support for the orderly access of electric vehicles to the grid is provided.