A temperature match based optimization method for daily load prediction considering DLC effect

被引：24

作者：

Yu, ZW

机构：

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 1996年 / 11卷 / 02期

关键词：

load forecast; optimal temperature match method; optimal error reduction; neural network forecast; Box-Jenkins forecast; Box-Jenkins transfer function forecast; multi-linear regression forecast; direct load control (DLC);

D O I：

10.1109/59.496146

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：

This paper presents a unique optimization method for short term load forecasting. The new method is based on the optimal template temperature match between the future and past temperatures. The optimal error reduction technique is a new concept introduced in this paper. Two case studies show that for hourly load forecasting, this method can yield results as good as the; rather complicated Box-Jenkins Transfer Function method, and better than the Box-Jenkins method; for peak load prediction, this method is comparable in accuracy to the neural network method with back propagation, and can produce more accurate results than the multi-linear regression method. The DLC effect on system load is also considered in this method.

引用

页码：728 / 733

页数：6