Aiming at the problem of location and volume of electric vehicle (EV) charging stations, a planning model of EV charging station considering spatial-temporal distribution characteristics of charging load is proposed. Firstly, the spatial-temporal charging load prediction model of EV is established by dynamic Floyd algorithm combined with Latin hypercube sampling (LHS). Afterwards, from the perspective of considering user satisfaction and aiming at the minimum cost of both EV charging stations and users, Voronoi diagram and an adaptive simulated annealing particle swarm optimization algorithm (ASAPSO) are used to determine the service range, optimal number and location of charging stations, as well as the number of fast charging and slow charging pile configurations of each station. The EV charging station location and volume model is established. Finally, the effectiveness of the model is verified by planning some urban areas of a city in north China.
