Grey Prediction with Rolling Mechanism for Electricity Demand Forecasting of Shanghai
The traditional Grey model has been widely used in various forecasting systems, including electricity demand forecasting. However, it is reported that the accuracy of the model is not satisfactory. In this paper, Grey prediction with rolling mechanism (GPRM) approach is proposed to predict the total and industrial electricity consumption of Shanghai. GPRM is used because of high prediction accuracy, applicability in the case of limited data situations and requirement for little computational effort. Results show that the forecasting precision of GPRM for total and industrial electricity demand is improved. And future projections have also been done for total and industrial sector, respectively.
Xiping Wang
School of Business Administration, North China Electric Power University, Baoding, 071003, P.R. China
国际会议
2007年IEEE灰色系统与智能服务国际会议(2007 IEEE International Conference on Grey Systems and Intelligent Services)
南京
英文
2007-11-18（万方平台首次上网日期，不代表论文的发表时间）