Abstract
The construction of electric vehicle charging stations plays a very important role in the process of promoting the electrification of urban traffic, among which the prediction of electric vehicle charging demand is the premise and foundation of the planning and construction of charging stations. This paper first predicts the development of electric vehicles in Beijing; Based on the travel data of users in Beijing, the data are mined and analyzed, and the rules are reached by electric vehicles. Based on the parking data of EV users, the SOC distribution of users' parking was obtained. Monte Carlo method was used to simulate the arrival time and arrival condition of users, and then the charging process was simulated. After that, the charging decision model was established to obtain the spatial-temporal distribution curve of EV charging load. Finally, the charging pile and charging power capacity of the charging station are configured based on the regional charging demand and the spatial and temporal distribution curve of charging load.
Published Version
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