基于充电行为分析的电动汽车充电负荷预测

本文基于南方某市的电动汽车充电数据，得出各类型电动汽车在不同日期类型的充电开始时间、充电电量、充电功率的分布规律，采用蒙特卡洛算法模拟计算了该市2021年各类型电动汽车工作日与休息日的充电负荷情况，结果表明，电动私家车在休息日的午间和凌晨充电负荷要高于工作日；该市电动出租车在工作日与休息日的充电负荷占比分别为60.42%，58.55%，在三类型车中始终最大。电动私家车工作日与休息日充电负荷曲线有较大差异。电网总负荷会在19点达到最高峰，本文验证了电动汽车的大规模引入会增加电网的峰值和峰谷差，同时将充电行为数据拟合为公式，旨在为未来的电网扩容建设和对电动汽车的有序充电控制提供帮助。

Electric Vehicle Charging Load Forecast Based on Analysis of Charging Behavior

According to the charging data of electric vehicles in a southern city, this paper derives the distribution patterns of charging start time, electric quantity and charging power of each type of electric vehicle on different date types, and uses Monte Carlo algorithm to calculate the charging load of each type of electric vehicle on weekdays and rest days in the city in 2021.The results show that the charging load of electric private cars is higher on rest days than on weekdays during lunchtime and early morning; the charging load of electric taxis in the city is 60.42% and 58.55% on weekdays and rest days respectively, which is always the largest among the three types of vehicles. There is a large difference between the charging load curve for electric private cars on weekdays and rest days. The total grid load peaks at 19:00. This paper verifies that the large-scale introduction of electric vehicles increases the peak and peak-valley differences on the grid, and at the same time fits the charging behavior data into formulas, with the aim of providing assistance in the construction of future grid expansions and the control of orderly charging of electric vehicles.