Charging Load Forecasting for Electric Vehicles Based on Fuzzy Inference
Large scale of electric vehicles (EVS) integration will pose great impacts on the power system,due to their disorderly charging.Electric cars’ charging load cannot be forecasted as the traditional power load,which is usually forecasted based on historical data.There need to be some other methods to predict electric vehicles charging load,in order to improve the reliability and security of the grid.This paper analyze the travel characteristics of electric vehicles,then use the fuzzy inference system to emulate the process of drivers’ decision to charge their cars,the charging probability is attained in the given location.Finally,the daily profile of charging load can be predicted according to the numbers of electric vehicles forecasted in Beijing.
electric vehicle travel characteristics charging load,fuzzy inference
Jingwei Yang Diansheng Luo Shuang Yang Shiyu Hu
The College of Electric and Information Engineering,Hunan University,Changsha 410082,China
国际会议
Chinese Conference on Pattern Recognition, CCPR(2014年全国模式识别学术会议)
长沙
英文
585-594
2014-11-01（万方平台首次上网日期，不代表论文的发表时间）