Research on the spatial-temporal distribution of electric vehicle charging load demand: A case study in China

The surge in the number of electric vehicle (EV) users has brought a large amount of EV charging demands in recent years, making China construct tens of thousands of charging piles. However, the blind construction of charging infrastructures in cities brings about problems such as waste of land and funds, as well as irregular fluctuations in power grids. Only knowing the spatial-temporal distribution of EV charging load demands can these problems be solved and charging infrastructures be scientifically arranged. Therefore, this paper mainly discusses the spatial-temporal distribution of EV charging load demands in different urban functional areas and temperatures. First, involving individual differences into the hypothesis of rational people and taking multiple random factors such as time, location, temperature and road conditions into account, this paper establishes a spatial-temporal distribution model of charging load demands and applies the Monte Carlo simulation to solve it. Then, a case study is conducted. The results show that charging load demands of different functional areas have obvious spatial-temporal distribution characteristics and vary from each other. The temperature changes significantly affect the ratio of fast and slow charging load demands. Finally, this paper suggests that the proportion of slow and fast charging piles can be set to 50:1 in residential areas, 85:1 in working areas, while 3:1 in other functional areas, and the proportion in shopping entertainment areas and social rest areas can be set from 4:1 to 5:1. These proportions are related to the rated power of the charging pile. (C) 2019 Elsevier Ltd. All rights reserved.