Electric Vehicle Charging Load Modeling Based on Influence Factor Analysis

Abstract

Abstract:The spatial-temporal distribution of charging loads for electric vehicles is influenced by multiple factors, Nowadays, the accuracy of the forecasts needs to be improved and the completeness of the modeling is relatively lacking. Therefore, this paper proposes a method for modeling the charging load of electric vehicles based on the influence of multiple factors. First, an in-depth analysis of the factors affecting the charging load of electric vehicles was conducted. Then, a model of electric vehicle electricity consumption per unit kilometer was constructed based on the influencing factors. Next, the electric vehicle, the charging station, the traffic network and the grid are modeled separately. In addition, a unified model of vehicle-station-road-network was constructed through the interaction and coupling of information between the models. Finally, the spatial-temporal distribution of electric vehicle charging loads was simulated using real data from a region. The study shows that the model is able to simulate the charging load of electric vehicles more accurately. Different traffic flows and areas have a significant impact on the charging load distribution.

Key words:electric vehicle, influencing factors, vehicle-station-road-network, load forecasting

摘要：电动汽车的充电负荷时空分布受到多种因素影响，预测的准确性还有待提高，建模的完备性比较缺乏。为此，提出了基于多种因素影响的电动汽车充电负荷建模方法。首先深入地分析了影响电动汽车充电负荷的因素，基于影响因素构建了电动汽车单位里程耗电量模型，然后分别建立了电动汽车、充电站、交通网、配电网模型，利用各模型之间的信息交互和耦合关系构建了车-站-路-网统一模型，最后以采集的某区域真实数据为例模拟了电动汽车充电负荷时空分布。结果表明：所构建的模型能够较为准确的模拟电动汽车不同时空分布的充电需求；不同车流量以及不同区域对充电负荷分布具有明显的影响。

关键词:电动汽车，影响因素，车-站-路-网，负荷预测

CLC Number:

TM73
U49

WANG Guojun, WANG Liye, WANG Lifang, LIAO Chenglin. Electric Vehicle Charging Load Modeling Based on Influence Factor Analysis[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(6): 1232-1241.

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