Research On Coordination Strategy Of Electric Vehicle Charging And Feeding Scheduling With Path Planning

As a green transportation tool,electric vehicles can alleviate the serious consumption of non-renewable energy by traditional fuel vehicles and the increasingly serious environmental pollution problems.At present,China has also introduced a number of policies to promote the promotion and use of electric vehicles.With the application of large-scale electric vehicles,in order to improve the travel and charging experience of electric vehicle users in the driving mode,and to alleviate the impact of the collective charging behavior of electric vehicles on the grid load.In this thesis,the electric vehicle charging scheduling strategy and the feeding scheduling strategy in the driving mode are studied respectively,and the charging schedule is combined to plan the shortest time driving route for the electric vehicle users.In order to manage the charging behavior of electric vehicles that initiates the path planning request in the driving mode,this thesis firstly uses Monte Carlo method to simulate the charging load of charging stations to estimate the queuing time of electric vehicles in charging stations.Then this thesis proposes a single electric vehicle charging scheduling strategy based on driving plan and solves the model.The simulation results show that this strategy can effectively reduce the charging queue time of electric vehicles when the number of electric vehicles is small.However,as the number of electric vehicles increases,this strategy does not consider the impact of electric vehicle charging on each other and the impact on grid load.Therefore,the average travel time of electric vehicles in the system continues to increase,and serious charging imbalance occurs in each charging station.Aiming at this phenomenon,this thesis proposes an electric vehicle charging scheduling strategy based on charging station load balancing,and uses genetic algorithm to solve it.The simulation results show that even if the number of electric vehicles is large,the strategy can effectively balance the load of each charging station.And effectively reduce the average travel and charging time of electric vehicles in the system.During the peak load period of the grid,for an electric vehicle that is emergency in the travel mode and needs to be charged,it is often desirable to supplement the electric energy by feeding to reduce the charging time.This thesis first analyzes the feasibility of electric power exchange technology between electric vehicles in driving mode.Then,based on how to preferentially match the charging electric vehicles and feeder electric vehicles with similar driving route,this thesis proposes an electric vehicle power discharging matching strategy based on driving plan.The strategy is solved using the improved GS algorithm.The simulation results show that the electric vehicle power discharging matching strategy based on the driving plan proposed in this thesis can effectively reduce the waiting time of the charging electric vehicle and the additional power consumption of the feeding electric vehicle.In addition,the proposed strategy is to maximize the system feed volume as the objective function,which can alleviate the peak load pressure of the grid to some extent.