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Empirical sunshine-based models vs online estimators for solar resources

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  • Paulescu, Marius
  • Badescu, Viorel
  • Budea, Sanda
  • Dumitrescu, Alexandru

Abstract

Monthly averaged daily global solar irradiation data collected from four online platforms (NASA POWER, MERRA2, ERA5 and CAMS) are compared with ground measured data retrieved from World Radiation Data Center and Baseline Surface Radiation Network. Similarly, monthly averaged daily global solar irradiation estimated by five different Ångström-Prescott-type equations have been compared with the same ground measured data. The accuracy of the online platforms and Ångström – Prescott equations, respectively, is largely comparable, although some differences are noticed. Both the platforms and the Ångström-Prescott equations are sensitive to climates. A tendency of the Ångström-Prescott equations to exceed the platforms performance in the tropical and continental climates was noticed. Without exception the platforms and models perform better in summer than in winter. No Ångström – Prescott equation outperforms the platforms during all seasons, and, mutually, no platform outperforms the Ångström – Prescott equations during all seasons.

Suggested Citation

  • Paulescu, Marius & Badescu, Viorel & Budea, Sanda & Dumitrescu, Alexandru, 2022. "Empirical sunshine-based models vs online estimators for solar resources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    • Handle: RePEc:eee:rensus:v:168:y:2022:i:c:s136403212200750x
    DOI: 10.1016/j.rser.2022.112868
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    References listed on IDEAS

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    1. Song, Zhe & Cao, Sunliang & Yang, Hongxing, 2024. "An interpretable framework for modeling global solar radiation using tree-based ensemble machine learning and Shapley additive explanations methods," Applied Energy, Elsevier, vol. 364(C).

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