A Recent Invasion Wave Of Deep Learning In Solar Power Forecasting Techniques Using Ann

Analysis of variables to determine their influence on renewable energy forecasting using ensemble methods

“… Jain, Rathee, Kumar, Sambasivam, Boadh, Choudhary, Kumar & Kumar Singh [ 7 ]; Inman, Pedro, Coimbra[ 8 ] Artificial Intelligence (AI) methods, especially Artificial Neural Networks (ANNs) AI methods, notably ANNs, have shown superior effectiveness over primitive models. Sfetsos & Coonick [ 9 ]; Nguyen, Pham, Duong & Vu [ 10 ]; Malik, Gehlot, Singh, Gupta & Thakur [ 11 ] Multilayer Perceptron (MLP) and Feed-Forward Back-Propagation Networks Used to predict solar irradiance on horizontal surfaces with a net error significantly lower than some linear methods. Gardner & Dorling [ 12 ]; Paoli, Voyant, Muselli, & Nivet [ 13 ]; Achite, Banadkooki, Ehteram, Bouharira, Ahmed & Elshafie [ 14 ] Precision evaluation using RMSE, nRMSE, and MAPE Mixed results in predictions, hovering around 20–30 % accuracy in some cases.…”