Integrating satellite imagery-derived data and GIS-based solar radiation algorithms to map solar radiation in high temporal and spatial resolutions for the province of Salta, Argentina

Abstract

An accurate estimation of solar radiation availability is vital for planning solar energy generation systems. Classically, this type of estimation is made by cumulating data for periods of one year and serves to determine locations with the highest solar radiation availability. However, the integration of high shares of technologies such as photovoltaics in the energy matrix and the evaluation of the economic viability of these systems under time-dependent promotion mechanisms, also requires estimations in a high temporal resolution. When looking at the yearly solar resource availability, the north-west of Argentina is one of the regions of the world with the highest solar radiation potential. Yet estimations are available mainly in low spatial resolutions and there are only few studies that try to characterize the temporal variability of the solar resource in this part of the world. This paper presents a methodology to integrate satellite imagery derived data and a GIS-based solar radiation algorithm in order to generate a high resolution solar irradiance spatiotemporal data set for the province of Salta, north-west Argentina. This data set describes in a better way the differences in solar resource availability between flat and mountainous regions in the province, serves to accurately identify locations with the highest global solar radiation and to characterize its variability on time. Furthermore, the presented methodology can be easily replicated for the rest of South America that is covered by Down-welling Surface Shortwave Flux (DSSF) product provided by the Land Surface Analysis Satellite Applications Facility.