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Parameterization of daily solar irradiance variability

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  • Czekalski, D.
  • Chochowski, A.
  • Obstawski, P.

Abstract

The effects of solar systems operation can be compared only under very similar weather conditions. Diagnostics of the solar systems requires unequivocal determination of solar irradiation. Development of a method for precise identification of solar radiation day time profile is needed, as the methods used so far in the cloud cover determination are not satisfactory. The paper presents two optional methods, developed by the authors, for identification of the solar radiation profile. Advantages and disadvantages of the methods are also specified.

Suggested Citation

  • Czekalski, D. & Chochowski, A. & Obstawski, P., 2012. "Parameterization of daily solar irradiance variability," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 2461-2467.
    • Handle: RePEc:eee:rensus:v:16:y:2012:i:5:p:2461-2467
    DOI: 10.1016/j.rser.2012.01.069
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    References listed on IDEAS

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    1. Bakirci, Kadir, 2009. "Models of solar radiation with hours of bright sunshine: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(9), pages 2580-2588, December.
    2. Muneer, T. & Younes, S. & Munawwar, S., 2007. "Discourses on solar radiation modeling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 11(4), pages 551-602, May.
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    Cited by:

    1. Gianfranco Chicco & Valeria Cocina & Paolo Di Leo & Filippo Spertino & Alessandro Massi Pavan, 2015. "Error Assessment of Solar Irradiance Forecasts and AC Power from Energy Conversion Model in Grid-Connected Photovoltaic Systems," Energies, MDPI, vol. 9(1), pages 1-27, December.
    2. Avila, Alberto & Vizcaya, Pedro R. & Diez, Rafael, 2019. "Daily irradiance test signal for photovoltaic systems by selection from long-term data," Renewable Energy, Elsevier, vol. 131(C), pages 755-762.
    3. 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.
    4. Castillejo-Cuberos, Armando & Escobar, Rodrigo, 2020. "Understanding solar resource variability: An in-depth analysis, using Chile as a case of study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    5. Hernández-Escobedo, Q. & Rodríguez-García, E. & Saldaña-Flores, R. & Fernández-García, A. & Manzano-Agugliaro, F., 2015. "Solar energy resource assessment in Mexican states along the Gulf of Mexico," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 216-238.
    6. Chochowski, Andrzej & Obstawski, Paweł, 2017. "The use of thermal-electric analogy in solar collector thermal state analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 397-409.
    7. Grossmann, Wolf D. & Grossmann, Iris & Steininger, Karl W., 2013. "Distributed solar electricity generation across large geographic areas, Part I: A method to optimize site selection, generation and storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 831-843.

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