Inferential based statistical indicators for the assessment of solar resource data

Abstract

The drive to reduce fossil fuel dependency led to a surge in interest in renewable energy as a replacement fuel source, which provided research opportunities for vastly different domains. Statistical modelling was used extensively to assist in research. This study applied two statistical techniques that can be used in conjunction or independently to existing methods to validate solar resource data simulated from models. The case study, using a database from a Southern African Universities Radiometric Network,  provided illustrative benefits to the methods proposed, while comparing them with some of the validation methods currently used. It was demonstrated that profile analysis plots are easy to interpret, as deviations between modelled and measured data over time are clearly observed, while traditional validation scatter plots are unable to distinguish these deviations.