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Effect of sunshine and solar declination on the computation of monthly mean daily diffuse solar radiation

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  • Gopinathan, K.K.
  • Soler, Alfonso

Abstract

Several years of measured data for 17 European locations have been used to develop models for estimating monthly mean daily values of diffuse radiation (Hd) from combinations of the following: clearness index, sunshine fraction, and solar declination. Two models giving the highest correlation coefficients and the lowest standard errors of estimation are tested with data for 10 European locations not used in their development. From consideration of the MBE and RMSE values, a model which estimates Hd values from clearness index, relative sunshine duration and solar declination is found to be the most accurate. Comparison with Hd values predicted with the European Community solar radiation model (ECM) confirms this conclusion.

Suggested Citation

  • Gopinathan, K.K. & Soler, Alfonso, 1996. "Effect of sunshine and solar declination on the computation of monthly mean daily diffuse solar radiation," Renewable Energy, Elsevier, vol. 7(1), pages 89-93.
    • Handle: RePEc:eee:renene:v:7:y:1996:i:1:p:89-93
    DOI: 10.1016/0960-1481(95)00108-5
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    Cited by:

    1. Shamshirband, Shahaboddin & Mohammadi, Kasra & Khorasanizadeh, Hossein & Yee, Por Lip & Lee, Malrey & Petković, Dalibor & Zalnezhad, Erfan, 2016. "Estimating the diffuse solar radiation using a coupled support vector machine–wavelet transform model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 428-435.
    2. Khorasanizadeh, Hossein & Mohammadi, Kasra, 2016. "Diffuse solar radiation on a horizontal surface: Reviewing and categorizing the empirical models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 338-362.
    3. Jamil, Basharat & Akhtar, Naiem, 2017. "Comparison of empirical models to estimate monthly mean diffuse solar radiation from measured data: Case study for humid-subtropical climatic region of India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1326-1342.
    4. Mohammadi, Kasra & Shamshirband, Shahaboddin & Petković, Dalibor & Khorasanizadeh, Hossein, 2016. "Determining the most important variables for diffuse solar radiation prediction using adaptive neuro-fuzzy methodology; case study: City of Kerman, Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1570-1579.
    5. Sözen, Adnan & Arcakliog[caron]lu, Erol, 2005. "Effect of relative humidity on solar potential," Applied Energy, Elsevier, vol. 82(4), pages 345-367, December.
    6. Sözen, Adnan & Arcaklioglu, Erol, 2005. "Solar potential in Turkey," Applied Energy, Elsevier, vol. 80(1), pages 35-45, January.
    7. Miroslav Rimar & Marcel Fedak & Andrii Kulikov & Olha Kulikova & Martin Lopusniak, 2022. "Analysis and CFD Modeling of Thermal Collectors with a Tracker System," Energies, MDPI, vol. 15(18), pages 1-28, September.
    8. Sözen, Adnan & Arcaklıoğlu, Erol & Özalp, Mehmet & Çağlar, Naci, 2005. "Forecasting based on neural network approach of solar potential in Turkey," Renewable Energy, Elsevier, vol. 30(7), pages 1075-1090.
    9. Chen, Ji-Long & He, Lei & Chen, Qiao & Lv, Ming-Quan & Zhu, Hong-Lin & Wen, Zhao-Fei & Wu, Sheng-Jun, 2019. "Study of monthly mean daily diffuse and direct beam radiation estimation with MODIS atmospheric product," Renewable Energy, Elsevier, vol. 132(C), pages 221-232.
    10. Sözen, Adnan & Arcaklioglu, Erol & Özalp, Mehmet & Kanit, E. Galip, 2004. "Use of artificial neural networks for mapping of solar potential in Turkey," Applied Energy, Elsevier, vol. 77(3), pages 273-286, March.
    11. Sözen, Adnan & Arcaklioglu, Erol & Özalp, Mehmet & Kanit, E. Galip, 2005. "Solar-energy potential in Turkey," Applied Energy, Elsevier, vol. 80(4), pages 367-381, April.

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