ARTIFICIAL NEURAL NETWORK AND WAVELET DECOMPOSITION IN THE FORECAST OF GLOBAL HORIZONTAL SOLAR RADIATION

This paper proposes a method (denoted by WD-ANN) that combines the Artificial Neural Networks (ANN) and the Wavelet Decomposition (WD) to generate short-term global horizontal solar radiation forecasting, which is an essential information for evaluating the electrical power generated from the conversion of solar energy into electrical energy. The WD-ANN method consists of two basic steps: firstly, it is performed the decomposition of level p of the time series of interest, generating p + 1 wavelet orthonormal components; secondly, the p + 1 wavelet orthonormal components (generated in the step 1) are inserted simultaneously into an ANN in order to generate short-term forecasting. The results showed that the proposed method (WD-ANN) improved substantially the performance over the (traditional) ANN method.

Bibliographic Details

Main Authors:	Teixeira Júnior,Luiz Albino, Souza,Rafael Morais de, Menezes,Moisés Lima de, Cassiano,Keila Mara, Pessanha,José Francisco Moreira, Souza,Reinaldo Castro
Format:	Digital revista
Language:	English
Published:	Sociedade Brasileira de Pesquisa Operacional 2015
Online Access:	http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382015000100073
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