基于实测数据的多类型电动汽车充电负荷分析

本文基于某电动汽车公司的实测数据,对多类型电动汽车跟踪数据进行统计分析。首先设定条件对数据进行预处理,删除异常数据并采用拉格朗日插值法补充部分数据;然后,文中借助K–S检验和J-B检验等方法,验证电动汽车集群数据是否符合规律分布;再采用蒙特卡洛法对电动汽车充电负荷进行仿真,形成多类型电动汽车充电负荷曲线;最后,结合日用电负荷,分析了无序充电情况下电动汽车负荷对电网的影响。结果表明,电动私家车与电动出租车具有较大的负荷调度潜力,但无序充电下会产生“峰上加峰”现象。

Data-driven Multi-type Electric Vehicle Charging Load Analysis

Based on the measured data, this paper analyzes the tracking data of multi type electric vehicles. Firstly, set conditions to preprocess the data, delete the abnormal data and use Lagrange interpolation to supplement some data; then, with the help of K-S test and J-B test, verify whether the electric vehicle cluster data conform to the regular distribution; then, Monte Carlo simulation is used to predict the charging load of electric vehicles, and the charging load distribution of multiple types of electric vehicles is formed. Finally, the daily electric load was used to analyze the impact of electric vehicle loads on the power grid. The results show that electric private cars and electric taxis have a large load dispatching potential, but the phenomenon of peak plus peak will occur under disorderly charging.