SHORT-TERM POWER-SYSTEM LOAD FORECASTING USING THE ITERATIVELY REWEIGHTED LEAST-SQUARES ALGORITHM

被引：10

作者：

ELHAWARY, ME

MBAMALU, GAN

机构：

[1] Technical University of Nova Scotia, Halifax, NS

来源：

ELECTRIC POWER SYSTEMS RESEARCH | 1990年 / 19卷 / 01期

关键词：

D O I：

10.1016/0378-7796(90)90003-L

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：

A robust model for forecasting power system hourly load is developed. The method exploits the convenience of the autocorrelation function (ACF), and the partial autocorrelation function (PACF) of the resulting differenced previous load data in identifying a suboptimal model. The identified model parameters are estimated using the iteratively reweighted least squares procedure. The weighting functions, the tuning constants, and the weighted sum of the squared residuals form a three-way decision variable in identifying an optimal model and the subsequent parameter estimates. The final model is applied to predict the Nova Scotia Power Corporation's 24 hours ahead hourly load. The results obtained are documented and compared with results based on the ordinary least squares procedure in order to demonstrate the superior performance of this approach. © 1990.

引用

页码：11 / 22

页数：12

共 17 条

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