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Prediction of daily global solar irradiation data using Bayesian neural network: A comparative study

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  • Yacef, R.
  • Benghanem, M.
  • Mellit, A.

Abstract

This paper presents a comparative study between Bayesian Neural Network (BNN), classical Neural Network (NN) and empirical models for estimating the daily global solar irradiation (DGSR). An experimental meteorological database from 1998 to 2002 at Al-Madinah (Saudi Arabia) has been used. Four input parameters have been employed: air temperature, relative humidity, sunshine duration and extraterrestrial irradiation. Automatic relevance determination (ARD) method has investigated in order to select the optimum input parameters of the NN. Results show that the BNN performs better that other NN structures and empirical models.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:renene:v:48:y:2012:i:c:p:146-154
    DOI: 10.1016/j.renene.2012.04.036
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    References listed on IDEAS

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    1. 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.
    2. Siqueira, Adalberto N. & Tiba, Chigueru & Fraidenraich, Naum, 2010. "Generation of daily solar irradiation by means of artificial neural net works," Renewable Energy, Elsevier, vol. 35(11), pages 2406-2414.
    3. López, G. & Batlles, F.J. & Tovar-Pescador, J., 2005. "Selection of input parameters to model direct solar irradiance by using artificial neural networks," Energy, Elsevier, vol. 30(9), pages 1675-1684.
    4. Rahimikhoob, Ali, 2010. "Estimating global solar radiation using artificial neural network and air temperature data in a semi-arid environment," Renewable Energy, Elsevier, vol. 35(9), pages 2131-2135.
    5. Rehman, Shafiqur & Mohandes, Mohamed, 2008. "Artificial neural network estimation of global solar radiation using air temperature and relative humidity," Energy Policy, Elsevier, vol. 36(2), pages 571-576, February.
    6. Benghanem, M. & Joraid, A.A., 2007. "A multiple correlation between different solar parameters in Medina, Saudi Arabia," Renewable Energy, Elsevier, vol. 32(14), pages 2424-2435.
    7. Benghanem, Mohamed & Mellit, Adel, 2010. "Radial Basis Function Network-based prediction of global solar radiation data: Application for sizing of a stand-alone photovoltaic system at Al-Madinah, Saudi Arabia," Energy, Elsevier, vol. 35(9), pages 3751-3762.
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