COMPOSITE MODELING FOR ADAPTIVE SHORT-TERM LOAD FORECASTING

被引:119
作者
PARK, JH
PARK, YM
LEE, KY
机构
[1] SEOUL NATL UNIV,DEPT ELECT ENGN,SEOUL 151742,SOUTH KOREA
[2] PENN STATE UNIV,DEPT ELECT ENGN,UNIVERSITY PK,PA 16802
关键词
LOAD FORECASTING; ADAPTIVE FILTERS;
D O I
10.1109/59.76686
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Composite load model is developed for 1-24 hours ahead prediction of hourly electric loads. The load model is composed of three components: the nominal load, the type load and the residual load. The nominal load is modeled such that the Kalman filter can be used and the parameters of the model are adapted by the exponentially weighted recursive least squares method. The type load component is extracted for weekend load prediction and updated by an exponential smoothing method. The residual load is predicted by the autoregressive model and the parameters of the model are estimated using the recursive least squares method. Test results are shown using a utility data for two different years.
引用
收藏
页码:450 / 457
页数:8
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