A geographic information system method to generate long term regional solar radiation resource maps: enhancing decision-making

Abstract

A long-term regional solar energy assessment improves decision-making processes for the selection of the best solar energy technology and helps understand how to define focused policies and investments. This study presents long-term solar resource monthly maps for Qatar. The availability of solar radiation throughout the country has been mapped here using ground-based measurements and satellite data. The regression-kriging algorithm and its variants are used to calibrate satellite data, through interpolation of ground solar radiation data. Digital surface model data is used as an auxiliary variable to further scale down to 30 m resolution. Long-term monthly maps of daily total solar radiation have been produced which consist of 12 monthly maps for global horizontal irradiance (GHI) and 12 monthly maps for direct normal irradiance (DNI) for each month of the year. A significant improvement of 9.15% and 9.32% in GHI and DNI estimation has been observed after calibration, which brings down the Normalized Root Mean Square Error (NRMSE) to 4% and 11.70% for GHI and DNI respectively as compared to the non-calibrated satellite data estimation.