The exploitation of solar energy is becoming cost-effective, and currently is the renewable source showing the higher growth worldwide. The knowledgeof solar energy resources is essential to boost new investments in solar systems for electricity generation. The estimation of site-specific solar irradiation, where ground data are not available, can be accomplished by two approaches: interpolation/extrapolation of surface measurements acquired at neighboring stations or by radiative transfer models based on satellite images. The choice between these two approaches depends on the evaluation of their uncertainties. In this study employed solar radiation data collected by 18 automatic weather stations (AWS) located in the Brazilian southeast region to extrapolate and interpolate solar irradiation at different distances from the AWS. Statistical analysis of the deviations as a function of the distance from the closest measurement site have shown that the root mean square errors (RMSE) increase as the interpolation/extrapolation distances increases. It was found that the greater the distance between AWS's and the reference site, the higher the deviations. Comparing the extrapolation/interpolation RMSE with the RMSE observed for estimates provided by the BRASIL-SR model, it was found that only for distances less than 60 km, the methods of interpolation and extrapolation showed deviations within the range achieved by using the satellite model. Thus, it is possible to conclude that the use of satellite data and radiative transfer models represent the best solution for the assessment of solar energy further from ground radiation measurement sites.
solar radiation; interpolation; extrapolation; remote sensing; numeric modeling; radiative transfer
