摘要
当前,针对电动汽车充电负荷变化规律的研究大多基于正态分布假定,缺乏对充电行为、时空分布等因素随机性的考虑。以重庆市充电桩监测数据集为研究基础,采用基于时刻充电概率的蒙特卡罗模拟方法,建立充电负荷预测模型,考察不同典型日(工作日、休息日)、车辆类型、充电区域下的充电负荷时空分布规律。研究发现:1)不同类型车辆的充电负荷分布差异较大,私家车和出租车充电负荷占比较高,调节潜力较大,电网在进行调度时,可以设计多种情境下的指导性充电策略;2)相比综合分析,分区域充电负荷预测能够更有效地提升电网负荷预测精确度,使得车辆调度具有更大的时空调节潜力。
At present,the research on the changing rules of the electric vehicle charging load is mostly based on the assumption of normal distribution,and the factors such as randomness of charging behavior,temporal and spatial distribution are not considered.Based on the monitoring data set of charging piles in Chongqing,the Monte Carlo simulation method based on the moment charging probability was adopted to establish the charging load prediction model,and the temporal and spatial distribution rules of the charging load in different typical days(working days and rest days),vehicle types and charging areas were investigated.Findings:1)the distribution of charging loads of different types of vehicles is quite different,and the charging loads of private cars and taxis account for a relatively high proportion,which has great regulating potential,so for the power grid dispatching,guiding charging strategies can be designed in various situations;2)compared with comprehensive analysis,regional charging load predicting method can improve the accuracy of power grid load prediction more effectively,which makes vehicle dispatching have greater potential in the temporal and spatial adjustment.
作者
周珊珊
林永君
ZHOU Shanshan;LIN Yongjun(Department of Automation,North China Electric Power University,Baoding 071003,China)
出处
《工业技术创新》
2022年第3期120-126,共7页
Industrial Technology Innovation
关键词
电动汽车
充电行为
充电负荷预测
时空分布
蒙特卡罗
Electric Vehicle
Charging Behavior
Charging Load Prediction
Temporal and Spatial Distribution
Monte Carlo
