Solar radiation forecasting by using deep neural networks in Eski̇şehi̇r

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Sigma Mühendislik ve Fen Bilimleri Dergisi
Volume:39 Issue:2
Solar radiation forecasting by using deep neural networks in Eski̇şehi̇r

Solar radiation forecasting by using deep neural networks in Eski̇şehi̇r

Authors : Mohammed QADEM, Ümmühan BAŞARAN FİLİK

Pages : 159-169

View : 33 | Download : 8

Publication Date : 2021-06-02

Article Type : Research Paper

Abstract :According to the World Economic Outlook insert ignore into journalissuearticles values(WEO);, the global demand for energy is presumably going to be increased due to growing the world’s population up during the upcoming two decades. As a result of that, apprehensions about environmental effects, which appear as a result of greenhouse gases are grown and cleaner energy technologies are developed. This clearly shows that extended growth of the worldwide market share of clean energy. Solar energy is considered as one of the fundamental types of renewable energy. For this reason, the need for a predictive model that effectively observes solar energy conversion with high performance becomes urgent. In this paper, classic empirical, artificial neural network insert ignore into journalissuearticles values(ANN);, deep neural network insert ignore into journalissuearticles values(DNN);, and time series models are applied, and their results are compared to each other to find the most accurate model for daily global solar radiation insert ignore into journalissuearticles values(DGSR); estimation. In addition, four regression models have been developed and applied for DGSR estimation. The obtained results are evaluated and compared by the root mean square error insert ignore into journalissuearticles values(RMSE);, relative root mean square error insert ignore into journalissuearticles values(rRMSE);, mean absolute error insert ignore into journalissuearticles values(MAE);, mean bias error insert ignore into journalissuearticles values(MBE);, t-statistic, and coefficient of determination insert ignore into journalissuearticles values(R2);. Finally, simulation results provided that the best result is found by the DNN model.
Keywords : Daily global solar radiation forecasting, artificial neural network, deep neural network, renewable energy

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