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Evaluation and performance comparison of different models for global solar radiation forecasting: a case study on five cities

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  • Mohamed A. Ali

    (City of Scientific Research and Technological Applications (SRTA-City)
    Alexandria University
    Borg Al Arab Technological University)

  • Ashraf Elsayed

    (Alexandria University
    Al Alamein International University)

  • Islam Elkabani

    (Alexandria University
    Al Alamein International University)

  • M. Elsayed Youssef

    (City of Scientific Research and Technological Applications (SRTA-City))

  • Gasser E. Hassan

    (City of Scientific Research and Technological Applications (SRTA-City)
    Borg Al Arab Technological University)

Abstract

Recently, solar energy has emerged as the most promising renewable energy source to meet the world’s energy demands. However, to harness the potential of solar energy, accurate data on solar radiation are crucial. It is considered the first step in assessing solar resources for various applications and achieving energy sustainability goals. Due to the unavailability of solar radiation measurements in many parts of the world, several models have been developed to predict global solar radiation (GSR) at these locations. Thus, this study aims to evaluate the proficiency of several GSR models at five new locations and determine the most suitable one for GSR prediction. The study has further developed solar radiation models for these new locations, as well as general ones for the entire region, which does not have any GSR models despite the existence of many planned solar energy facilities in this area. Additionally, the study investigates the effect of changing the length of the validation dataset on models’ performance and accuracy, as well as assesses the introduced models’ generalization capability. To achieve these objectives, the observed data of GSR for approximately 37 years at studied locations are used to develop and validate the proposed models. The study’s findings reveal that Model 1 provides the best performance at all locations, with accuracy, coefficient of determination ( $$R^{2}$$ R 2 ), ranging from 95 to 98%, except for the coastal location, where it is from 91 to 95%. The remaining performance indicators of the best models, such as RMSE, MABE, MAPE, and $$r$$ r , are good, and their values range from 0.7863 to 1.9097 (MJ m−2 day−1), from 0.6430 to 1.7060 (MJ m−2 day−1), from 3.4319 to 10.0890 (%), and from 0.9914 to 0.9981, respectively. The length of the validation dataset has a slight effect on the models’ performance, ranging from about 1% to 2%. Therefore, Model 1 is the recommended solar radiation model, which can provide precise and rapid estimates of global solar radiation. This approach could be used in the design and performance evaluation of many solar applications. The primary benefit of this approach in the current investigation is that temperature data are continuously and effortlessly recorded for various purposes.

Suggested Citation

  • Mohamed A. Ali & Ashraf Elsayed & Islam Elkabani & M. Elsayed Youssef & Gasser E. Hassan, 2025. "Evaluation and performance comparison of different models for global solar radiation forecasting: a case study on five cities," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(5), pages 10159-10201, May.
  • Handle: RePEc:spr:endesu:v:27:y:2025:i:5:d:10.1007_s10668-023-04307-5
    DOI: 10.1007/s10668-023-04307-5
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    References listed on IDEAS

    as
    1. Karakoti, Indira & Das, Prasun Kumar & Singh, S.K., 2012. "Predicting monthly mean daily diffuse radiation for India," Applied Energy, Elsevier, vol. 91(1), pages 412-425.
    2. Agarwal, Vernika & Malhotra, Snigdha & Dagar, Vishal & M. R, Pavithra, 2023. "Coping with public-private partnership issues: A path forward to sustainable agriculture," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    3. Almorox, J. & Hontoria, C. & Benito, M., 2011. "Models for obtaining daily global solar radiation with measured air temperature data in Madrid (Spain)," Applied Energy, Elsevier, vol. 88(5), pages 1703-1709, May.
    4. Almorox, J. & Benito, M. & Hontoria, C., 2005. "Estimation of monthly Angström–Prescott equation coefficients from measured daily data in Toledo, Spain," Renewable Energy, Elsevier, vol. 30(6), pages 931-936.
    5. Dongwei Su & Shulin Xu & Zefeng Tong, 2023. "Credit availability and corporate risk-taking: evidence from China’s green credit policy," Post-Communist Economies, Taylor & Francis Journals, vol. 35(3), pages 236-270, April.
    6. Doorga, Jay R.S. & Rughooputh, Soonil D.D.V. & Boojhawon, Ravindra, 2019. "Modelling the global solar radiation climate of Mauritius using regression techniques," Renewable Energy, Elsevier, vol. 131(C), pages 861-878.
    7. Dagher, Leila & Yacoubian, Talar, 2012. "The causal relationship between energy consumption and economic growth in Lebanon," Energy Policy, Elsevier, vol. 50(C), pages 795-801.
    8. Ertekin, Can & Yaldız, Osman, 1999. "Estimation of monthly average daily global radiation on horizontal surface for Antalya (Turkey)," Renewable Energy, Elsevier, vol. 17(1), pages 95-102.
    9. Zulfiqar Ali Baloch & Qingmei Tan & Hafiz Waqas Kamran & Muhammad Atif Nawaz & Gadah Albashar & Javaria Hameed, 2022. "A multi-perspective assessment approach of renewable energy production: policy perspective analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(2), pages 2164-2192, February.
    10. Abd Alwahed Dagestani & Lingli Qing & Mohamad Abou Houran, 2022. "What Remains Unsolved in Sub-African Environmental Exposure Information Disclosure: A Review," JRFM, MDPI, vol. 15(10), pages 1-11, October.
    11. Dagher, Leila & Ruble, Isabella, 2010. "Challenges for CO2 mitigation in the Lebanese electric-power sector," Energy Policy, Elsevier, vol. 38(2), pages 912-918, February.
    12. Dagher, Leila & El Hariri, Sadika, 2013. "The impact of global oil price shocks on the Lebanese stock market," Energy, Elsevier, vol. 63(C), pages 366-374.
    13. Charles Eesley & Jian Bai Li & Delin Yang, 2016. "Does Institutional Change in Universities Influence High-Tech Entrepreneurship? Evidence from China’s Project 985," Organization Science, INFORMS, vol. 27(2), pages 446-461, April.
    14. Dagestani, Abd Alwahed & Shang, Yuping & Schneider, Nicolas & Cifuentes-Faura, Javier & Zhao, Xin, 2023. "Porter in China: A quasi-experimental view of market-based environmental regulation effects on firm performance," Energy Economics, Elsevier, vol. 126(C).
    15. Dagher, Leila, 2012. "Natural gas demand at the utility level: An application of dynamic elasticities," Energy Economics, Elsevier, vol. 34(4), pages 961-969.
    16. Zhang, Shaohe & Shinwari, Riazullah & Zhao, Shikuan & Dagestani, Abd Alwahed, 2023. "Energy transition, geopolitical risk, and natural resources extraction: A novel perspective of energy transition and resources extraction," Resources Policy, Elsevier, vol. 83(C).
    17. Chen, Pengyu & Dagestani, Abd Alwahed, 2023. "Urban planning policy and clean energy development Harmony- evidence from smart city pilot policy in China," Renewable Energy, Elsevier, vol. 210(C), pages 251-257.
    18. Iskander Tlili, 2015. "Renewable energy in Saudi Arabia: current status and future potentials," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 17(4), pages 859-886, August.
    19. Ayodele, T.R. & Ogunjuyigbe, A.S.O., 2015. "Prediction of monthly average global solar radiation based on statistical distribution of clearness index," Energy, Elsevier, vol. 90(P2), pages 1733-1742.
    20. Dagher, Leila & Ruble, Isabella, 2011. "Modeling Lebanon’s electricity sector: Alternative scenarios and their implications," Energy, Elsevier, vol. 36(7), pages 4315-4326.
    21. Hassan, Gasser E. & Youssef, M. Elsayed & Mohamed, Zahraa E. & Ali, Mohamed A. & Hanafy, Ahmed A., 2016. "New Temperature-based Models for Predicting Global Solar Radiation," Applied Energy, Elsevier, vol. 179(C), pages 437-450.
    22. Khorasanizadeh, H. & Mohammadi, K., 2013. "Introducing the best model for predicting the monthly mean global solar radiation over six major cities of Iran," Energy, Elsevier, vol. 51(C), pages 257-266.
    23. Fadare, D.A., 2009. "Modelling of solar energy potential in Nigeria using an artificial neural network model," Applied Energy, Elsevier, vol. 86(9), pages 1410-1422, September.
    24. Li, Huashan & Ma, Weibin & Lian, Yongwang & Wang, Xianlong, 2010. "Estimating daily global solar radiation by day of year in China," Applied Energy, Elsevier, vol. 87(10), pages 3011-3017, October.
    25. Rao, Amar & Dagar, Vishal & Sohag, Kazi & Dagher, Leila & Tanin, Tauhidul Islam, 2023. "Good for the planet, good for the wallet: The ESG impact on financial performance in India," Finance Research Letters, Elsevier, vol. 56(C).
    26. Jiang, Yingni, 2009. "Estimation of monthly mean daily diffuse radiation in China," Applied Energy, Elsevier, vol. 86(9), pages 1458-1464, September.
    27. Zaaoumi, Anass & Bah, Abdellah & Ciocan, Mihaela & Sebastian, Patrick & Balan, Mugur C. & Mechaqrane, Abdellah & Alaoui, Mohammed, 2021. "Estimation of the energy production of a parabolic trough solar thermal power plant using analytical and artificial neural networks models," Renewable Energy, Elsevier, vol. 170(C), pages 620-638.
    28. Ashmore Mawire & Sibongiseni M. Simelane & Patrick O. Abedigamba, 2021. "Energetic and exergetic performance comparison of three solar cookers for developing countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(10), pages 14528-14555, October.
    29. Zhou, Hui & Awosusi, Abraham Ayobamiji & Dagar, Vishal & Zhu, Guohua & Abbas, Shujaat, 2023. "Unleashing the asymmetric effect of natural resources abundance on carbon emissions in regional comprehensive economic partnership: What role do economic globalization and disaggregating energy play?," Resources Policy, Elsevier, vol. 85(PA).
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