Abstract

CLOHESSY, Chantelle May; SHARP, Gary; HUGO, Johan  and  VAN DYK, E.. Inferential based statistical indicators for the assessment of solar resource data. J. energy South. Afr. [online]. 2019, vol.30, n.1, pp.21-33. ISSN 2413-3051.  http://dx.doi.org/10.17159/2413-3051/2019/v30i1a5430.

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. Highlights 1. Identified new statistical techniques to compare measured and modelled solar radiation data. 2. Multivariate technique used to assess the shape and trend of solar radiation data. 3. Developed a method to calculate interval estimate plots for the assessment of modelled data. 4. Both proposed methods provide adequate support for solar resource reliability.

Keywords : solar resource assessment; statistical comparison techniques; multivariate profile analysis; interval estimate plots.

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