Electrical load forecasting formulation by a fast neural network
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Data
2003-03-01
Autores
Lopes, Mara Lúcia M. [UNESP]
Minussi, Carlos R. [UNESP]
Lotufo, Anna Diva P. [UNESP]
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Resumo
The objective of this work is to develop a methodology for electric load forecasting based on a neural network. Here, backpropagation algorithm is used with an adaptive process that based on fuzzy logic and using a decaying exponential function to avoid instability in the convergence process. This methodology results in fast training, when compared to the conventional formulation of backpropagation algorithm. The results are presented using data from a Brazilian Electric Company, and shows a very good performance for the proposal objective.
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Palavras-chave
Backpropagation, Fuzzy logic, Load forecasting, Neural networks, Short term
Como citar
International Journal of Engineering Intelligent Systems for Electrical Engineering and Communications, v. 11, n. 1, p. 51-57, 2003.