Solar radiation prediction using Artificial Neural Network techniques: A review
Yadav, A. K. and Chandel, S. S.
2014 Renewable and Sustainable Energy Reviews, Volume 33, May 2014, Pages 772-781
Solar energy; Solar radiation models; Artificial Neural Network; Solar radiation prediction; Meteorological data
Yadav, A. K. and Chandel, S. S., (2014), "Solar radiation prediction using Artificial Neural Network techniques: A review", Renewable and Sustainable Energy Reviews, Volume 33, May 2014, Pages 772-781.
Abstract:
Solar radiation data plays an important role in solar energy research. These data are not available for location of interest due to absence of a meteorological station. Therefore, the solar radiation has to be predicted accurately for these locations using various solar radiation estimation models. The main objective of this study is to review Artificial Neural Network (ANN) based techniques in order to identify suitable methods available in the literature for solar radiation prediction and to identify research gaps. The study shows that Artificial Neural Network techniques predict solar radiation more accurately in comparison to conventional methods. The prediction accuracy of ANN models is found to be dependent on input parameter combinations, training algorithm and architecture configurations. Further research areas in ANN technique based methodologies are also identified in the present study.
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