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Validation of direct normal irradiance predictions under arid conditions: A review of radiative models and their turbidity-dependent performance

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  • Gueymard, Christian A.
  • Ruiz-Arias, José Antonio

Abstract

In this study, a detailed review of the performance of 24 radiative models from the literature is presented. These models are used to predict the clear-sky surface direct normal irradiance (DNI) at a 1-min time resolution. Coincident radiometric and sunphotometric databases of the highest possible quality, and recorded at seven stations located in arid environments, are used for this analysis. At most sites, an extremely large range of aerosol loading conditions and high variability in their characteristics are noticed. At one site (Solar Village), DNI was measured routinely with an active cavity radiometer with very low uncertainty compared to field pyrheliometers, which makes its dataset exceptional.

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  • Gueymard, Christian A. & Ruiz-Arias, José Antonio, 2015. "Validation of direct normal irradiance predictions under arid conditions: A review of radiative models and their turbidity-dependent performance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 379-396.
  • Handle: RePEc:eee:rensus:v:45:y:2015:i:c:p:379-396
    DOI: 10.1016/j.rser.2015.01.065
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    1. Janjai, S. & Sricharoen, K. & Pattarapanitchai, S., 2011. "Semi-empirical models for the estimation of clear sky solar global and direct normal irradiances in the tropics," Applied Energy, Elsevier, vol. 88(12), pages 4749-4755.
    2. 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.
    3. Gueymard, Christian A., 2005. "Importance of atmospheric turbidity and associated uncertainties in solar radiation and luminous efficacy modelling," Energy, Elsevier, vol. 30(9), pages 1603-1621.
    4. 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.
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    10. Benkaciali, Saïd & Haddadi, Mourad & Khellaf, Abdellah, 2018. "Evaluation of direct solar irradiance from 18 broadband parametric models: Case of Algeria," Renewable Energy, Elsevier, vol. 125(C), pages 694-711.
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    12. Sun, Xixi & Bright, Jamie M. & Gueymard, Christian A. & Acord, Brendan & Wang, Peng & Engerer, Nicholas A., 2019. "Worldwide performance assessment of 75 global clear-sky irradiance models using Principal Component Analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 550-570.
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