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Experimental and theoretical investigation of diffuse solar radiation: Data and models quality tested for Egyptian sites

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  • Elminir, Hamdy K.

Abstract

In order to obtain reliable irradiation data for the design, operation and economic assessment of solar power stations, eight widely used standard models predicting diffuse irradiation values are tested. A statistical analysis of hourly, daily and monthly correlations is carried out, using a 5yr data archive (1999–2003) of hourly global and diffuse solar irradiances obtained at five selected meteorological stations over greater Egypt area. The accuracy of the candidate correlations are performed in terms of the two widely used statistical indicators, mean bias and root mean square errors; standard deviation, standard error and F-test, were also introduced. The results indicate that the correlations relating the diffuse fraction (KD) with both clearness index (KT) and the sunshine fraction (S/SO) are more reliable for diffuse irradiation predictions in the Egyptian environment than using each variable separately.

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  • Elminir, Hamdy K., 2007. "Experimental and theoretical investigation of diffuse solar radiation: Data and models quality tested for Egyptian sites," Energy, Elsevier, vol. 32(1), pages 73-82.
    • Handle: RePEc:eee:energy:v:32:y:2007:i:1:p:73-82
    DOI: 10.1016/j.energy.2006.01.020
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    1. Gopinathan, K.K. & Soler, Alfonso, 1995. "Diffuse radiation models and monthly-average, daily, diffuse data for a wide latitude range," Energy, Elsevier, vol. 20(7), pages 657-667.
    2. Trabea, A.A, 1999. "Technical note a multiple linear correlation for diffuse radiation from global solar radiation and sunshine data over Egypt," Renewable Energy, Elsevier, vol. 17(3), pages 411-420.
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    Cited by:

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    3. Pillot, Benjamin & de Siqueira, Sandro & Dias, João Batista, 2018. "Grid parity analysis of distributed PV generation using Monte Carlo approach: The Brazilian case," Renewable Energy, Elsevier, vol. 127(C), pages 974-988.
    4. Jiang, Yingni, 2008. "Prediction of monthly mean daily diffuse solar radiation using artificial neural networks and comparison with other empirical models," Energy Policy, Elsevier, vol. 36(10), pages 3833-3837, October.
    5. Koussa, Mustapha & Saheb-Koussa, Djohra & Hadji, Seddik, 2017. "Experimental investigation of simple solar radiation spectral model performances under a Mediterranean Algerian's climate," Energy, Elsevier, vol. 120(C), pages 751-773.
    6. Pandey, Chanchal Kumar & Katiyar, A.K., 2009. "A comparative study to estimate daily diffuse solar radiation over India," Energy, Elsevier, vol. 34(11), pages 1792-1796.
    7. Jiang, Yingni, 2009. "Estimation of monthly mean daily diffuse radiation in China," Applied Energy, Elsevier, vol. 86(9), pages 1458-1464, September.
    8. Elminir, Hamdy K. & Azzam, Yosry A. & Younes, Farag I., 2007. "Prediction of hourly and daily diffuse fraction using neural network, as compared to linear regression models," Energy, Elsevier, vol. 32(8), pages 1513-1523.
    9. Bakirci, Kadir, 2021. "Prediction of diffuse radiation in solar energy applications: Turkey case study and compare with satellite data," Energy, Elsevier, vol. 237(C).
    10. Sabzpooshani, Majid & Mohammadi, Kasra, 2014. "Establishing new empirical models for predicting monthly mean horizontal diffuse solar radiation in city of Isfahan, Iran," Energy, Elsevier, vol. 69(C), pages 571-577.
    11. Khalil, Samy A. & Shaffie, A.M., 2016. "Evaluation of transposition models of solar irradiance over Egypt," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 105-119.
    12. Khalil, Samy A. & Shaffie, A.M., 2013. "A comparative study of total, direct and diffuse solar irradiance by using different models on horizontal and inclined surfaces for Cairo, Egypt," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 853-863.

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