Modelling of diffuse solar fraction with multiple predictors

• Published in: Renewable energy 2010-02, Vol.35 (2), p.478-483
• Main Authors: Ridley, Barbara, Boland, John, Lauret, Philippe
• Format: Article
• Language: English
• Subjects: Applied sciences; Diffuse radiation; Energy; Energy meterology; Engineering Sciences; Exact sciences and technology; Mathematical modelling; Mechanics; Multiple regression; Natural energy; Physics; Solar energy; Solar radiation; Thermics
• ISSN: 0960-1481; 1879-0682
• DOI: 10.1016/j.renene.2009.07.018

For some locations both global and diffuse solar radiation are measured. However, for many locations, only global radiation is measured, or inferred from satellite data. For modelling solar energy applications, the amount of radiation on a tilted surface is needed. Since only the direct component on a tilted surface can be calculated from direct on some other plane using trigonometry, we need to have diffuse radiation on the horizontal plane available. There are regression relationships for estimating the diffuse on a tilted surface from diffuse on the horizontal. Models for estimating the diffuse on the horizontal from horizontal global that have been developed in Europe or North America have proved to be inadequate for Australia [13]. Boland et al. [2] developed a validated model for Australian conditions. Boland et al. [3] detailed our recent advances in developing the theoretical framework for the use of the logistic function instead of piecewise linear or simple nonlinear functions and was the first step in identifying the means for developing a generic model for estimating diffuse from global and other predictors. We have developed a multiple predictor model, which is much simpler than previous models, and uses hourly clearness index, daily clearness index, solar altitude, apparent solar time and a measure of persistence of global radiation level as predictors. This model performs marginally better than currently used models for locations in the Northern Hemisphere and substantially better for Southern Hemisphere locations. We suggest it can be used as a universal model.