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

2015; Sociedade Brasileira de Pesquisa Operacional; Volume: 35; Issue: 1 Linguagem: Inglês

10.1590/0101-7438.2015.035.01.0073

1678-5142

Luíz Albino Teixeira Júnior, Rafael Morais de Souza, Moisés Lima de Menezes, Keila Mara Cassiano, José Francisco Moreira Pessanha, Reinaldo Castro Souza,

Grey System Theory Applications

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.