The research of local linear model of short term electrical load on multivariate time series

According to the idea of phase space reconstruction of scalar time series, phase space reconstruction of multivariate time series based on the short-term electric load is presented. The good time delay is chosen for each scalar time series by mutual information. The method to get the minimum embedding dimension is based on minimum forecasting errors. The choice of optimal neighbor points is presented in this paper according to Euclidean distance and degree of correlation between forecast point and its nearest neighboring points. Then one-rank local linear model based on multivariate time series is proposed. The daily load forecasting for a certain district in Chongqing is respectively carried out by the method presented in this paper. Through the analysis of the obtained forecasting results it is shown that the method presented in this paper is more accurate than that of scalar time series.