DocumentCode
375483
Title
A fast electric load forecasting using neural networks
Author
Lopes, Mara M. ; Minussi, Carlos R. ; Lotufo, Anna P.
Author_Institution
Departamento de Engenharia Eletrica, Univ. Estadual Paulista, Sao Paulo, Brazil
Volume
2
fYear
2000
fDate
2000
Firstpage
646
Abstract
The objective of this work is the development of a methodology for electric load forecasting based on a neural network. Here, the backpropagation algorithm with an adaptive process based on fuzzy logic is used. This methodology results in fast training, when compared to the conventional formulation of the backpropagation algorithm. Results are presented using data from a Brazilian electric company and the performance is very good for the proposal objective
Keywords
backpropagation; load forecasting; neural nets; power system analysis computing; Brazil; adaptive process; backpropagation algorithm; computer simulation; fast electric load forecasting; fuzzy logic; neural networks; training; Artificial neural networks; Backpropagation algorithms; Control systems; Economic forecasting; Load forecasting; Load modeling; Neural networks; Neurons; Proposals; Relays;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2000. Proceedings of the 43rd IEEE Midwest Symposium on
Conference_Location
Lansing, MI
Print_ISBN
0-7803-6475-9
Type
conf
DOI
10.1109/MWSCAS.2000.952840
Filename
952840
Link To Document