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A review of validation methodologies and statistical performance indicators for modeled solar radiation data: Towards a better bankability of solar projects

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  • Gueymard, Christian A.

Abstract

In the context of the current rapid development of large-scale solar power projects, the accuracy of the modeled radiation datasets regularly used by many different interest groups is of the utmost importance. This process requires careful validation, normally against high-quality measurements. Some guidelines for a successful validation are reviewed here, not just from the standpoint of solar scientists but also of non-experts with limited knowledge of radiometry or solar radiation modeling. Hence, validation results and performance metrics are reported as comprehensively as possible. The relationship between a desirable lower uncertainty in solar radiation data, lower financial risks, and ultimately better bankability of large-scale solar projects is discussed.

Suggested Citation

  • Gueymard, Christian A., 2014. "A review of validation methodologies and statistical performance indicators for modeled solar radiation data: Towards a better bankability of solar projects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 1024-1034.
    • Handle: RePEc:eee:rensus:v:39:y:2014:i:c:p:1024-1034
    DOI: 10.1016/j.rser.2014.07.117
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    References listed on IDEAS

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    1. Badescu, Viorel & Gueymard, Christian A. & Cheval, Sorin & Oprea, Cristian & Baciu, Madalina & Dumitrescu, Alexandru & Iacobescu, Flavius & Milos, Ioan & Rada, Costel, 2012. "Computing global and diffuse solar hourly irradiation on clear sky. Review and testing of 54 models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1636-1656.
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    5. Marsaglia, George & Tsang, Wai Wan & Wang, Jingbo, 2003. "Evaluating Kolmogorov's Distribution," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 8(i18).
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