A new method of short term load forecasting using artificial neural network

被引：0

作者：

Du, XH ^{[1
]}

Zhang, L ^{[1
]}

Xue, ZH ^{[1
]}

Song, JC ^{[1
]}

Du, XP ^{[1
]}

机构：

[1] Tai Yuan Univ Technol, Coll Elect & Power Engn, Taiyuan 030024, Peoples R China

来源：

ISTM/2005: 6th International Symposium on Test and Measurement, Vols 1-9, Conference Proceedings | 2005年

关键词：

D O I：

暂无

中图分类号：

TH7 [仪器、仪表];

学科分类号：

0804 ; 080401 ; 081102 ;

摘要：

Short term load forecasting (STLF) under power market should be fast and accurate. In the article, firstly, after judging the related weather factors that influence load by using scattering figure between load and weather factor, a new idea of selecting input samples of historical day data according to weather factor is presented. Secondly, Levenberg-Marquardt algorithm of feed forward neural network is introduced., Finally, some day STLF results of Taiyuan area in Shan Xi province are given, and it shows that the method is effective.

引用

页码：1700 / 1703

页数：4

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