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

Pesquisa Operacional

Luiz Albino Teixeira Júnior¹  Rafael Morais De Souza¹  Moisés Lima De Menezes¹  Keila Mara Cassiano¹  José Francisco Moreira Pessanha¹  Reinaldo Castro Souza¹ 

关键词: wavelet decomposition;    artificial neural networks;    forecasts;   

DOI  :  10.1590/0101-7438.2015.035.01.0073

来源: SciELO

【 摘 要 】

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.

【 授权许可】

CC BY   
 All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License