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A multiple correlation between different solar parameters in Medina, Saudi Arabia

Author

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  • Benghanem, M.
  • Joraid, A.A.

Abstract

The purpose of this work is to give the potential of solar energy in Medina (Kingdom of Saudi Arabia). We develop a correlation between the different parameters of solar energy. We have used a database available at the National Renewable Energy Laboratory (NREL) website for five years since 1998 until 2002. Also, a typical meteorological year (TMY) has been built from this database. By using the correlations model obtained from these database, we can estimate the global and diffuse irradiation with good agreement in Medina. The correlation connecting diffuse irradiation with both clearness index and sunshine (SS) duration is found to be applicable in Medina site. A linear correlation between ambient temperature and global irradiation data is found from sunrise until midday with a good agreement. A polynomial correlation is given between temperature and global irradiation data from midday until sunset.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:32:y:2007:i:14:p:2424-2435
    DOI: 10.1016/j.renene.2006.12.017
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    Citations

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    Cited by:

    1. Fei Wang & Zengqiang Mi & Shi Su & Hongshan Zhao, 2012. "Short-Term Solar Irradiance Forecasting Model Based on Artificial Neural Network Using Statistical Feature Parameters," Energies, MDPI, vol. 5(5), pages 1-16, May.
    2. Ngoc-Lan Huynh, Anh & Deo, Ravinesh C. & Ali, Mumtaz & Abdulla, Shahab & Raj, Nawin, 2021. "Novel short-term solar radiation hybrid model: Long short-term memory network integrated with robust local mean decomposition," Applied Energy, Elsevier, vol. 298(C).
    3. El-Sebaii, A.A. & Al-Hazmi, F.S. & Al-Ghamdi, A.A. & Yaghmour, S.J., 2010. "Global, direct and diffuse solar radiation on horizontal and tilted surfaces in Jeddah, Saudi Arabia," Applied Energy, Elsevier, vol. 87(2), pages 568-576, February.
    4. 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.
    5. 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.
    6. Alamdari, Pouria & Nematollahi, Omid & Alemrajabi, Ali Akbar, 2013. "Solar energy potentials in Iran: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 778-788.
    7. 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.
    8. Benghanem, M., 2011. "Optimization of tilt angle for solar panel: Case study for Madinah, Saudi Arabia," Applied Energy, Elsevier, vol. 88(4), pages 1427-1433, April.
    9. Kebir, Nisrine & Maaroufi, Mohamed, 2017. "Technical losses computation for short-term predictive management enhancement of grid-connected distributed generations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 1011-1021.
    10. 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.
    11. Hassan, Muhammed A. & Bailek, Nadjem & Bouchouicha, Kada & Nwokolo, Samuel Chukwujindu, 2021. "Ultra-short-term exogenous forecasting of photovoltaic power production using genetically optimized non-linear auto-regressive recurrent neural networks," Renewable Energy, Elsevier, vol. 171(C), pages 191-209.

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