| Summary: | This paper presents a study on the influence of Sun-Earth geometry and atmospheric variables on the predictions of solar global irradiation (GHI) obtained from the ECMWF model. It was found that the differences between predictions and measurements of GHI are correlated mainly with the clearness index, solar zenith angle, mean air temperature, relative humidity and total water column. An artificial neural network is developed to improve predictions of GHI for four locations being the base for a predicting algorithm that can be used in energy management models of solar systems thus allowing a better management of renewable energy conversion.
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