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Estimation of global solar radiation on horizontal surfaces in Jeddah, Saudi Arabia

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  • El-Sebaii, A.A.
  • Al-Ghamdi, A.A.
  • Al-Hazmi, F.S.
  • Faidah, Adel S.

Abstract

The measured data of global solar radiation on a horizontal surface, as well as the number of sunshine hours, mean daily ambient temperature, maximum and minimum ambient temperatures, relative humidity and amount of cloud cover, for Jeddah (latitude 21° 42'37''N, longitude 39° 11'12''E), Saudi Arabia for the period 1996-2006 are analyzed. The data are divided into two sets. The sub-data set 1 (1996-2004) are employed to develop empirical correlations between the monthly average of daily global solar radiation fraction (H/H0) and various meteorological parameters. The nonlinear Angström type model developed by Sen and the trigonometric function model proposed by Bulut and Büyükalaca are also evaluated. New empirical constants for these two models have been obtained for Jeddah. The sub-data set 2 (2005, 2006) are then used to evaluate the derived correlations. Comparisons between measured and calculated values of H have been performed. It is indicated that, the Sen and Bulut and Büyükalaca models satisfactorily describe the horizontal global solar radiation for Jeddah. All the proposed correlations are found to be able to predict the annual average of daily global solar radiation with excellent accuracy. Therefore, the long term performance of solar energy devices can be estimated.

Suggested Citation

  • El-Sebaii, A.A. & Al-Ghamdi, A.A. & Al-Hazmi, F.S. & Faidah, Adel S., 2009. "Estimation of global solar radiation on horizontal surfaces in Jeddah, Saudi Arabia," Energy Policy, Elsevier, vol. 37(9), pages 3645-3649, September.
    • Handle: RePEc:eee:enepol:v:37:y:2009:i:9:p:3645-3649
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    10. Hepbasli, Arif & Alsuhaibani, Zeyad, 2011. "A key review on present status and future directions of solar energy studies and applications in Saudi Arabia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 5021-5050.
    11. Yacef, R. & Benghanem, M. & Mellit, A., 2012. "Prediction of daily global solar irradiation data using Bayesian neural network: A comparative study," Renewable Energy, Elsevier, vol. 48(C), pages 146-154.
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