Predicting daily distribution of solar irradiation by neural networks

This work focuses on prediction of solar irradiation during the day. In order to predict half hourly solar irradiation during the day an artificial neural network is applied. The artificial neural network was trained using error backpropagation learning rule. Meteorological data measured during three years were used to form learning patterns. The trained artificial neural network was tested with different patterns. Some of them were new while the others were used in the training procedure. The comparison of measured and by the artificial neural network predicted daily distribution of solar irradiation shows a very good agreement for the clear days.