Forecasting Solar Radiation Based on Meteorological Data Using Machine Learning Techniques: A Case Study of Isparta

Authors : Buğra GÜZEL, Onur SEVLİ, Ersan OKATAN

Pages : 704-713

Doi:10.29137/umagd.1268055

View : 140 | Download : 137

Publication Date : 2023-07-14

Article Type : Research Paper

Abstract :Solar energy systems which is one of renewable energy sources takes more interest and gains prevalence day by day. As in other many renewable energy sources, a significant problem in solar energy systems is the unstability of the energy that the system will provide. Prediction of the energy to be obtained is very important in this respect. In this study, solar radiation is predicted using meteorological data taken from the General Directorate of Meteorology for Isparta. For predictions, the random forest insert ignore into journalissuearticles values(RF);, KNN insert ignore into journalissuearticles values(k-Nearest Neighbor);, ANN insert ignore into journalissuearticles values(Artificial Neural Networks); and Deep Learning insert ignore into journalissuearticles values(DL); methods are used. In addition, the results of dummy variable usage for time data are examined with these different methods. According to the findings obtained, it is seen that the dummy variable usage increases performance for ANN and DL methods but decreases performance for random forest and KNN methods. Best results are obtained for the prediction of the solar radiation with ANN and DL.
Keywords : derin öğrenme, kukla değişken, rastgele orman, güneş ışınımı tahmini, yapay sinir ağları