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    Master Thesis
    Short-Term Solar Irradiance Forecasting With Deep Neural Networks
    (Kadir Has Üniversitesi, 2019) Vatansever, Caner; Ceylan, O?uzhan
    Usage of solar energy has increased through the last decades, and they are being integrated into main grid systems since the recent years. In order to fully bene t from solar panels, predicting irradiance is essential. By knowing 15-minute ahead values of solar irradiance, resistance of the cells inside the solar panels can be measured to analyze production output. This study focuses on 15-minute ahead forecasting of irradiance by using sliding windows method on the feature set. ANN, K-NN, SVM and RF models are optimized in this study. As the result of the study, around 6% MAPE is achieved