Title :
The research of local linear model of short term electrical load on multivariate time series
Author :
Lei Shao-lan ; Sun Cai-xin ; Zhou Quan ; Zhang Xiao-xing
Author_Institution :
Chongqing Univ., Chongqing
Abstract :
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.
Keywords :
load forecasting; time series; Euclidean distance; forecasting errors; multivariate time series; phase space reconstruction; scalar time series; short term electrical load; time delay; Delay effects; Economic forecasting; Load forecasting; Power system analysis computing; Power system economics; Power system modeling; Power system reliability; Predictive models; Space technology; Time series analysis; chaotic time series; degree of correlation; multivariate time series; one-rank local linear forecasting model; optimal neighboring points; phase space reconstruction; short-term load forecasting;
Conference_Titel :
Power Tech, 2005 IEEE Russia
Conference_Location :
St. Petersburg
Print_ISBN :
978-5-93208-034-4
Electronic_ISBN :
978-5-93208-034-4
DOI :
10.1109/PTC.2005.4524543
