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Solar radiation over Saudi Arabia and comparisons with empirical models

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  • Rehman, Shafiqur

Abstract

We present a comparison between models developed by the present authors and 16 other models for different geographical and varied meteorological conditions. The comparisons are made using the mean bias error (MBE), root mean square error (RMSE), mean percentage error (MPE), and mean absolute bias error (MABE). These errors are calculated using monthly-mean, measured daily and estimated values of total solar radiation for 41 locations in Saudi Arabia. We find that our latitude, longitude, altitude, and sunshine-duration-dependent model given in Eq. (1)produced the best estimates for global solar radiation. The second- and third-best estimates were obtained from our linear model and other models given in Eq. (2)and Eq. (11), respectively.

Suggested Citation

  • Rehman, Shafiqur, 1998. "Solar radiation over Saudi Arabia and comparisons with empirical models," Energy, Elsevier, vol. 23(12), pages 1077-1082.
    • Handle: RePEc:eee:energy:v:23:y:1998:i:12:p:1077-1082
    DOI: 10.1016/S0360-5442(98)00057-7
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    Cited by:

    1. Jamil, Basharat & Akhtar, Naiem, 2017. "Estimation of diffuse solar radiation in humid-subtropical climatic region of India: Comparison of diffuse fraction and diffusion coefficient models," Energy, Elsevier, vol. 131(C), pages 149-164.
    2. 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.
    3. Rehman, Shafiqur & Bader, Maher A. & Al-Moallem, Said A., 2007. "Cost of solar energy generated using PV panels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 11(8), pages 1843-1857, October.
    4. Despotovic, Milan & Nedic, Vladimir & Despotovic, Danijela & Cvetanovic, Slobodan, 2015. "Review and statistical analysis of different global solar radiation sunshine models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1869-1880.
    5. Jamal AlFaraj & Emanuel Popovici & Paul Leahy, 2024. "Solar Irradiance Database Comparison for PV System Design: A Case Study," Sustainability, MDPI, vol. 16(15), pages 1-26, July.
    6. Sabziparvar, Ali A., 2008. "A simple formula for estimating global solar radiation in central arid deserts of Iran," Renewable Energy, Elsevier, vol. 33(5), pages 1002-1010.
    7. Jawed Mustafa & Shahid Husain & Saeed Alqaed & Uzair Ali Khan & Basharat Jamil, 2022. "Performance of Two Variable Machine Learning Models to Forecast Monthly Mean Diffuse Solar Radiation across India under Various Climate Zones," Energies, MDPI, vol. 15(21), pages 1-32, October.
    8. Chen, Ji-Long & He, Lei & Yang, Hong & Ma, Maohua & Chen, Qiao & Wu, Sheng-Jun & Xiao, Zuo-lin, 2019. "Empirical models for estimating monthly global solar radiation: A most comprehensive review and comparative case study in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 91-111.
    9. 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.
    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. Bakirci, Kadir, 2009. "Correlations for estimation of daily global solar radiation with hours of bright sunshine in Turkey," Energy, Elsevier, vol. 34(4), pages 485-501.
    12. Muzathik, A.M. & Ibrahim, M.Z. & Samo, K.B. & Wan Nik, W.B., 2011. "Estimation of global solar irradiation on horizontal and inclined surfaces based on the horizontal measurements," Energy, Elsevier, vol. 36(2), pages 812-818.
    13. Halawa, Edward & GhaffarianHoseini, AmirHosein & Hin Wa Li, Danny, 2014. "Empirical correlations as a means for estimating monthly average daily global radiation: A critical overview," Renewable Energy, Elsevier, vol. 72(C), pages 149-153.
    14. Ağbulut, Ümit & Gürel, Ali Etem & Biçen, Yunus, 2021. "Prediction of daily global solar radiation using different machine learning algorithms: Evaluation and comparison," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    15. Ashraf Farahat & Abdulhaleem H. Labban & Abdul-Wahab S. Mashat & Hosny M. Hasanean & Harry D. Kambezidis, 2024. "Status of Solar-Energy Adoption in GCC, Yemen, Iraq, and Jordan: Challenges and Carbon-Footprint Analysis," Clean Technol., MDPI, vol. 6(2), pages 1-32, June.
    16. 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.
    17. Makade, Rahul G. & Jamil, Basharat, 2018. "Statistical analysis of sunshine based global solar radiation (GSR) models for tropical wet and dry climatic Region in Nagpur, India: A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 87(C), pages 22-43.
    18. 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.
    19. Bakirci, Kadir, 2015. "Models for the estimation of diffuse solar radiation for typical cities in Turkey," Energy, Elsevier, vol. 82(C), pages 827-838.

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