基于蒙特卡洛算法的大规模电动汽车充电负荷预测

Monte-Carlo-algorithm-based Load Prediction of Electric Vehicles Large-scale Charging

电动汽车充电负荷的有效预测对配电网的安全稳定运行有重大意义。以某地区不同类型电动汽车的保有量预测结果为基础,将用户出行习惯、电动汽车的充电功率、充电时长等因素作为模型参数,利用蒙特卡洛模拟算法建立了考虑电动汽车类型的充电负荷预测模型,对该地区电动汽车的充电负荷进行预测。结果表明,未来电动汽车充电负荷增长较快,2025年较2022年充电负荷增长近70%,且不同类型充电负荷有不同的特征。该方法能提升电网负荷预测精确度,为配电网的调度与规划提供技术支撑。

The effective prediction of EV charging load is of great significance to safe and stable operation of distribution network.Based on the prediction results of various types of EVs in a certain region and by using Monte Carlo algorithm,this work established a charging load prediction model considering EV types in which user travel behaviors,EV charging power and charging time and other factors were selected as model parameters.A simulative prediction of EV charging load demand in that region was carried out,indicating a rapid growth of charging load in 2025 by nearly 70%from 2022 and obvious characteristic differences among various types of charging loads.The proposed method may help in improving accuracy of load prediction and providing technical support for distribution network scheduling and planning.