Abstract：A method is put forward in this paper to analyze the demand of EV charging piles based on stochastic simulation. Six charging areas are built by correlation analysis of parking time in different places, drivers’ acceptance range of battery state of charge are considered, and EV’ s traveling and charging model is established, where Monte Carlo method is used to stimulate EVs’ daily trip chain and charging demand in each destination. Meanwhile, the variation of parking number and the simultaneity of charging number are recorded. The proportion of total charging piles with parking space and the proportion of fast and slow piles are available in each area when entering the scale and proportion of EVs. It is proved that, the proportion of charging piles is not that high in working area, while the one is higher in three or more trip destinations. The proportion of fast and slow piles is higher in the areas with short parking time and urgent charging demand, while there exist fast charging demand in residential area. With constant EV scale and the increase of maximum driving range, there is no obvious change in the proportion of total charging piles, but the proportion of fast and slow piles goes down.
麻秀范, 李颖, 王皓, 王超, 洪潇. 基于电动汽车出行随机模拟的充电桩需求研究[J]. 电工技术学报, 2017, 32(增刊2): 190-202.
Ma Xiufan, Li Ying, Wang Hao, Wang Chao, Hong Xiao. Research on Demand of Charging Piles Based on Stochastic Simulation of EV Trip Chain. Transactions of China Electrotechnical Society, 2017, 32(增刊2): 190-202.
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