Artificial neural network based computational model for the prediction of direct solar radiation in Indian zone

In this paper, a computational model for the prediction of direct solar radiation based on neural network analysis of atmospheric clearness is developed. It considers that the major portion of direct solar radiation reaching the earth's surface is governed by Sun-Earth geometry and atmospheric transmittance factors which are exactly calculable by clear day model. Additional variations are due to climate and weather phenomena characterized by relative humidity, mean duration of sunshine per hour, and rainfall, etc., in the atmosphere. These variations are taken into account with the help of a composite parameter referred to as atmospheric clearness index (CI) which is determined using artificial neural network analysis. The contour maps of CI as a function of latitude, time of the day, and month of the year are then prepared using the meteorological data of eleven stations. Model simulation and test results of the trained network for two typical locations (not used in training the network) are presented an...

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