This research aims to improve the forecasting precision of electric quantity. It is discovered that the total electricity consumption considerably increased during the Spring Festival by the analysis of the electric q...This research aims to improve the forecasting precision of electric quantity. It is discovered that the total electricity consumption considerably increased during the Spring Festival by the analysis of the electric quantity time series from 2002 to 2007 in Shandong province. The festival factor is ascertained to be one of the important seasonal factors affecting the electric quantity fluctuations, and the multiplication model for forecasting is improved by introducing corresponding variables and parameters. The computational results indicate that the average relative error of the new model decreases from 4.31% to 1.93% and the maximum relative error from 14.05% to 6.52% compared with those of the model when the festival factor is not considered. It shows that introducing the festival factor into the multiplication model for electric quantity forecasting evidently improves the precision.展开更多
基金The Forecasting Research Base of Chinese Academy of Sciences in Xi an Jiaotong University,the National Natural Science Foundation of China (No.70773091)
文摘This research aims to improve the forecasting precision of electric quantity. It is discovered that the total electricity consumption considerably increased during the Spring Festival by the analysis of the electric quantity time series from 2002 to 2007 in Shandong province. The festival factor is ascertained to be one of the important seasonal factors affecting the electric quantity fluctuations, and the multiplication model for forecasting is improved by introducing corresponding variables and parameters. The computational results indicate that the average relative error of the new model decreases from 4.31% to 1.93% and the maximum relative error from 14.05% to 6.52% compared with those of the model when the festival factor is not considered. It shows that introducing the festival factor into the multiplication model for electric quantity forecasting evidently improves the precision.
