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Variability index of solar resource based on data from surface and satellite

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  • da Rocha, Vinicius Roggério
  • Costa, Rodrigo Santos
  • Martins, Fernando Ramos
  • Gonçalves, André Rodrigues
  • Pereira, Enio Bueno

Abstract

Characterizing solar resource variability is paramount for its thermal and photovoltaic applications. Cloudiness is the main parameter that modulates both the intensity and frequency of variations in solar irradiance on the ground surface. This work introduces an objective index to quantify the temporal variability of the incoming solar irradiance on the surface, defined as Cloudless Percentage Days (CPD). This index accounts for the number of days classified as clear and stable (i.e., high clearness coefficient and decreased frequency of ramps of incoming solar irradiance). Two methods were developed to quantify CPD, the first based on ground measurements and the other based on satellite data. This work compares the results achieved with the two methods to understand their consistency. Monthly and annual maps were drawn for the Brazilian territory characterizing solar resource variability.

Suggested Citation

  • da Rocha, Vinicius Roggério & Costa, Rodrigo Santos & Martins, Fernando Ramos & Gonçalves, André Rodrigues & Pereira, Enio Bueno, 2022. "Variability index of solar resource based on data from surface and satellite," Renewable Energy, Elsevier, vol. 201(P1), pages 354-378.
    • Handle: RePEc:eee:renene:v:201:y:2022:i:p1:p:354-378
    DOI: 10.1016/j.renene.2022.10.093
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    References listed on IDEAS

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    4. Kariuki, Boniface Wainaina & Sato, Tomonori, 2018. "Interannual and spatial variability of solar radiation energy potential in Kenya using Meteosat satellite," Renewable Energy, Elsevier, vol. 116(PA), pages 88-96.
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