基于时间充电概率的电动汽车负荷预测方法

Haolin Wang, Yongjun Zhang, Haipeng Mao
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引用次数: 6

摘要

电动汽车负荷预测是制定电动汽车充电策略和充电桩选址规划的技术基础。这对智慧城市和智能交通的发展具有重要意义。提出了一种基于时间充电概率的电动汽车负荷预测方法。首先,分析了影响负荷预测的主要因素。其次,根据电动汽车的典型出行特征将其分为四类,并建立了相应影响因素的数学模型;然后,推导出电动汽车每次充电的概率,并通过蒙特卡罗仿真计算电动汽车的充电负荷。最后,以深圳市电动汽车负荷预测为例,验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Load Forecasting Method of EVs Based on Time Charging Probability
Electric vehicle load forecasting is the technical basis for the development of electric vehicle charging strategies and the location planning of charging piles. It is of great significance for the development of smart cities and intelligent transportation. This paper proposes a load forecasting method for electric vehicles based on the time charging probability. Firstly, the main factors affecting load forecasting are described. Secondly, the electric cars are divided into four categories according to typical travel characteristics, and a mathematical model of the corresponding influence factors is established. Then, the charging probability of the electric vehicle at each time is derived, and the charging load of the electric vehicle is calculated by the Monte Carlo simulation. Finally, the validity of the method is verified by using the electric vehicle load forecast in Shenzhen city as an example.
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