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基于充电概率的区域电动汽车充电负荷预测

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在"双碳"战略的引导下,我国电动汽车行业发展迅猛,但同时也给区域内电网的配置以及充电站的运营带来了挑战.为更准确地预测区域内电动汽车在不同时刻的充电负荷,提高现有研究的精细度,首先分析了上海市某一区域内电动汽车用户的出行行为和充电行为数据,考虑用户在一天内不同时段的充电概率,然后基于蒙特卡洛方法建立了区域电动汽车充电负荷预测模型.结果显示,该区域的电动汽车日均行驶里程高出私人乘用车37.5 km;不同电池型号的电动汽车百公里耗电量差异较大;该区域内充电负荷存在明显的"三峰"现象,分别出现在7:00、14:00和22:00.最后,针对区域内公共充电站的供需情况,以实现资源最大化利用为目标,提出了优化区域电网配置、提高充电站利用率的针对性建议.基于蒙特卡洛方法提出的电动汽车充电负荷预测模型能丰富区域充电负荷预测方法,研究结果对电动汽车基础设施规划建设提供了参考.
Prediction of Regional Electric Vehicle Charging Load by Charging Probability
Under the Carbon Peaking and Carbon Neutrality("double carbon")strategy,electric vehicle(EV)in-dustry has developed rapidly in China.But it also brings challenges to the configuration of regional power grids and the operation of charging stations.In order to more accurately predict the charging load of EV in the region at differ-ent times and improve the precision of existing research,the travel behavior and charging behavior data of EV users were firstly analyzed in a region of Shanghai.Considering the charging probability in different periods of a day,the regional EV charging load prediction model was established by Monte Carlo method.The results show that the aver-age daily mileage of EV in this region is 37.5 km higher than that of private passenger vehicles;The power con-sumption per 100 km of EV with different battery models varies greatly;There are obvious"three peaks"of charging load in this area,which occur at 7:00,14:00 and 22:00 respectively.Finally,according to the supply and demand situation of public charging stations,targeted suggestions are put forward to optimize the regional power grid configu-ration and improve the utilization rate of charging stations in order to achieve the maximum utilization of resources.The EV charging load forecasting model by Monte Carlo method can enrich the regional charging load forecasting method.The research results provide a reference for the planning and construction of EV infrastructure.

electric vehicle(EV)travel behaviorcharging behaviorcharging loadMonte Carlo method

叶湘、罗瑛、李洁

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湖南大学土木工程学院,湖南长沙 410000

电动汽车 出行行为 充电行为 充电负荷 蒙特卡洛方法

2024

市政技术
中国市政工程协会 北京市政路桥股份有限公司 北京市政建设集团有限责任公司 北京市市政工程研究院

市政技术

影响因子:0.385
ISSN:1009-7767
年,卷(期):2024.42(2)
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