Hierarchical Optimal Scheduling Strategy for Electric Vehicles with Dynamic Time-of-Use Tariff

The disorderly charging tactics of large-scale electric vehicle (EV) will lead to the increase of peak-valley load difference of the power grid and destroy the stability of the power system. In order to solve this problem, considering the peak adjustment demand of the grid side and the different demands of the users on the charging amount and charging cost, this paper proposes a hierarchical optimization scheduling method based on the dynamic TOU time segment model. This method updates the load curve according to the load information of each EV when it is connected to the grid. Meanwhile, the dynamic time-of-use electricity price model proposed in this paper is used to dynamically update the peak-valley electricity price of the EV. Among them, the upper layer model takes the minimum variance of the total load of the grid as the objective function, and the lower layer model takes the minimum deviation of the agent scheduling plan, the maximum amount of charging and the minimum cost of charging as the objective function, and adopts the improved PSO algorithm to optimize the charging (discharging) tactics of each EV. Finally, the simulation analysis is carried out with a concrete example. The results show that this method can effectively reduce the peak-valley difference of load demand curve on the premise of ensuring the travel demand and economic benefits of EV owners.