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
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;
Conference_Titel :
Circuits and Systems, 2000. Proceedings of the 43rd IEEE Midwest Symposium on
Conference_Location :
Lansing, MI
Print_ISBN :
0-7803-6475-9
DOI :
10.1109/MWSCAS.2000.952840
