Study of Charging Station Short-Term Load Forecast Based on Wavelet Neural Networks for Electric Buses
With the large-scale use of electric vehicles (EVs),a short-term load forecast method based on wavelet neural network (WNN) for electric buses is proposed to analyze load characteristics in order to better arrange transmission and distribution planning and regulate EVs charging or discharging,which comes from the current measured data related the charging station,Guangdong.This method is used to predicting EVs’ load data of two test day selected randomly,compared with the effect of the single BP network model.The statistical results show that the prediction method has higher accuracy to meet certain application requirements than BP network applying to short-term load forecast of charging station for electric buses.
Electric buses wavelet neural network short-term load forecast BP network charging station
Lei Zhang Chun Huang Haoming Yu
College of Electrical and Information Engineering,Hunan University,Changsha,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
555-564
2014-11-01（万方平台首次上网日期，不代表论文的发表时间）