scholarly journals Overview of Solar Radiation Estimation Techniques with Development of Solar Radiation Model Using Artificial Neural Network

2020 ◽  
Vol 5 (4) ◽  
pp. 589-593
Author(s):  
Amar Choudhary ◽  
Deependra Pandey ◽  
Saurabh Bhardwaj
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Solar Radiation ◽  
Radiation Model ◽  
Estimation Techniques ◽  
Solar Radiation Model ◽  
Artificial Neural

Daily Surface Solar Radiation Prediction Mapping Using Artificial Neural Network: The Case Study of Reunion Island

2019 ◽  
Vol 142 (2) ◽  
Author(s):  
Peng Li ◽  
Miloud Bessafi ◽  
Beatrice Morel ◽  
Jean-Pierre Chabriat ◽  
Mathieu Delsaut ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Wavelet Transform ◽  
Solar Radiation ◽  
Computational Time ◽  
Reunion Island ◽  
Surface Solar Radiation ◽  
Clear Sky ◽  
Réunion Island ◽  
Artificial Neural

Abstract This paper focuses on the prediction of daily surface solar radiation maps for Reunion Island by a hybrid approach that combines principal component analysis (PCA), wavelet transform analysis, and artificial neural network (ANN). The daily surface solar radiation over 18 years (1999–2016) from CM SAF (SARAH-E with 0.05 deg × 0.05 deg spatial resolution) is first detrended using the clear sky index. Dimensionality reduction of the detrended dataset is secondly performed through PCA, which results in saving computational time by a factor of eight in comparison to not using PCA. A wavelet transform is thirdly applied onto each of the first 28 principal components (PCs) explaining 95% of the variance. The decomposed nine-wavelet components for each PC are fourthly used as input to an ANN model to perform the prediction of day-ahead surface solar radiation. The predicted decomposed components are finally returned to PCs and clear sky indices, irradiation in the end for re-mapping the surface solar radiation's distribution. It is found that the prediction accuracy is quite satisfying: root mean square error (RMSE) is 30.98 W/m2 and the (1 − RMSE_prediction/RMSE_persistence) is 0.409.

Supervised artificial neural network-based method for conversion of solar radiation data (case study: Algeria)

2016 ◽  
Vol 128 (1-2) ◽  
pp. 439-451 ◽  
Author(s):  
Maamar Laidi ◽  
Salah Hanini ◽  
Ahmed Rezrazi ◽  
Mohamed Redha Yaiche ◽  
Abdallah Abdallah El Hadj ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Solar Radiation ◽  
Radiation Data ◽  
Artificial Neural
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