The Prediction of Electric Vehicle Charging Load

被引：0
|
作者：
Song, Teng [1 ]
机构：
[1] Jiang Su Xuzhou Elect Power Co, Xuzhou 221000, Jiangsu, Peoples R China
来源：
PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON MANAGEMENT AND COMPUTER SCIENCE (ICMCS 2018) | 2018年 / 77卷
关键词：
Electric Vehicle; Load Forecasting; Optimization Algorithm; Driving Rule; Charging Mode;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Because electric vehicle charging has the characteristics of strong randomness and unpredictability, it will inevitably have a certain impact on the power system. To effectively predict the charging load of electric vehicles can effectively alleviate the impact of electric vehicle charging on the distribution network to a certain extent. An electric vehicle charging load forecasting method using neural network and genetic algorithm is proposed in this paper. This method fully considers the influence of driving rule, charging characteristics, seasonal change, road condition and other factors. Relevant experimental data show that the prediction method has good prediction accuracy.
引用
收藏
页码：565 / 568
页数：4
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