Monthly load forecasting Based on Optimum Grey Model

摘要：

　　Due to the variety and the randomicity of its influencing factors,the monthly load forecasting is a difficult problem for a long time.In order to improve the forecast accuracy,the paper proposes a new load forecast model based on improved GM (1,1).First,the GM (1,1) is used to forecast the load data,which takes the longitude historical data as original series,the increment trend of load was forecasted and takes the crosswise historical data as original series,the fluctuation trend of load was forecasted.On this basis the optimum method is led in.An optimal integrated forecasting model is built up.The case calculation results show that the proposed method can remarkably improve the accuracy of monthly load forecasting,and decrease the error.The integrated model this paper describes for short-term load forecasting is available and accurate.

关键词： Monthly load forecast Trend and fluctuations GM (1, 1) Optimum method

作者: Ting Wang Ximiao Jia

作者单位: 689 Room, Huadian Road North China Electric Power University, Baoding, China

会议类型: 国际会议

会议名称: the 2011 International Conference on Frontiers of Manufacturing Science and Measuring Technology (第一届制造科学与检测技术国际会议(ICFMM2011))

会议地点: 重庆

会议语种:英文

页码: 1226-1230

在线出版日期: 2011-06-23（万方平台首次上网日期，不代表论文的发表时间）