Research on Optimization Control Strategy of Vehicle-Road-Grid Charging and Exchanging Based on User Demand Guidance

Abstract

Considering the time-space uncertainty of electric vehicle charging and changing demand, the uneven distribution and random diversity of charging stations, the big data cloud network is used to realize the real-time information interaction between charging and changing power station and electric vehicle. Based on the user demand orientation, an intelligent charging and changing optimization control strategy of “Vehicle-Road-Grid” integrating cloud vehicle operation data is proposed. Under the discrete electric vehicle charging demand, this strategy quickly organizes the supply information around the discrete point. On the basis of the minimum energy consumption between the electric vehicle charging request point and the supply point, considering the multi-dimensional factors such as the optimal interests of the electric vehicle users, the shortest waiting time for charging and changing, and the shortest driving distance for charging and changing, the multi-objective optimal configuration strategy is realized. The simulation results show that the strategy can stably select the charging and swapping scheme that best meets the actual needs of users, effectively improve the charging and swapping service experience of users, and enhance the adhesion and participation of users.