Abstract

Knowledge of atmospheric turbidity and solar energy resources is essential for optimum planning and operation of solar-powered processes, cleaning of solar devices, energy saving and global warming monitoring. To determine the atmospheric turbidity and solar irradiance, scientists commonly refer to three methods, which are based on ground and/or space instruments. The drawback of these methods is that they do not provide any information about the turbidity of the atmosphere and the intensity of solar irradiance when the instruments are not available. The present study provides an alternative method to quantify the atmospheric turbidity and solar irradiance from measured data of ambient temperature and relative humidity. To overcome the complexity associated with the existing techniques, simple expressions have been proposed to estimate Precipitable Water (PW), Linke's turbidity factor (TL) and aerosols transparency coefficient (k). High quality radiometric databases, recorded at PSDA station, located in the Atacama Desert, Chile, are used to validate the new method. The proposed PW's expression has shown a Mean Bias Error (MBE) of 4.19%, better than the one used in REST2v5 solar radiation code, which has a MBE of 8.06%. Besides, the new method introduced herein, estimates TL with a MBE of 1.31%, which corresponds to a Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) of 7.64% and 10.22% respectively. The method has successively predicted the Direct Normal Irradiance (DNI) with a high accuracy. Indeed, the average deviation (MBE) from the measured DNI is less than 1%, which corresponds to a MAE and RMSE of 3.29% and 5.21% respectively. The careful analysis of the results reveals strong influence of the atmospheric turbidity's uncertainty on the prediction uncertainty of DNI.