An efficient method for peak load forecasting

Author

Jin, Liu ; Ziyang, Liu ; Jingbo, Sun ; Xinying, Song

Author_Institution

Dept. of Electr. Eng., Harbin Inst. of Technol.

fYear

2005

fDate

Nov. 29 2005-Dec. 2 2005

Firstpage

1

Lastpage

52

Abstract

This paper describes the peak load characteristics of power systems. A new method for the peak load forecasting (PLF) is proposed by means of an integration technique, which combines fuzzy clustering with feed-forward neural network (FNN) of the Levenberg-Maruardt (LM) training algorithm. Compared with the traditional back propagation (BP) algorithm, the proposed method proves more efficient to the predicted accuracy during the peak load period by using actual data of a power grid in China

Keywords

feedforward neural nets; integration; load forecasting; pattern clustering; power engineering computing; statistical analysis; China; Levenberg-Maruardt training algorithm; feed-forward neural network; fuzzy clustering; integration technique; peak load forecasting; power grid; traditional back propagation algorithm; Accuracy; Clustering algorithms; Computer science; Feedforward neural networks; Feedforward systems; Fuzzy neural networks; Load forecasting; Neural networks; Power systems; Predictive models; Peak load forecasting; fuzzy clustering; neural network; peak load pattern;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Engineering Conference, 2005. IPEC 2005. The 7th International

Conference_Location

Singapore

Print_ISBN

981-05-5702-7

Type

conf

DOI

10.1109/IPEC.2005.206877

Filename

1627166