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

机译:电动汽车充电负荷需求的时空分布研究-以中国为例

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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.
机译:近年来,电动汽车用户数量的激增带来了大量的电动汽车充电需求,使中国建造了数以万计的充电桩。但是,城市充电基础设施的盲目建设带来了土地和资金浪费,电网不规则波动等问题。只有知道电动汽车充电负荷需求的时空分布,才能解决这些问题,并科学地安排充电基础设施。因此,本文主要讨论了不同城市功能区和温度下电动汽车充电负荷需求的时空分布。首先,将个体差异纳入理性人的假设中,并考虑时间,位置,温度和道路条件等多个随机因素,建立了充电负荷需求的时空分布模型,并应用蒙特卡洛模拟求解它。然后,进行案例研究。结果表明,不同功能区的充电负荷需求具有明显的时空分布特征,并且相互之间存在差异。温度变化会显着影响快速和慢速充电负载需求的比率。最后,本文建议在住宅区中将慢速充电桩的比例设置为50:1,在工作区中将充电桩的比例设置为85:1,在其他功能区中将其设置为3:1,在购物娱乐区和社交场所中的比例可以设置为3:1休息区可设置为4:1至5:1。这些比例与充电桩的额定功率有关。 (C)2019 Elsevier Ltd.保留所有权利。

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