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Diffuse radiation models and monthly-average, daily, diffuse data for a wide latitude range

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  • Gopinathan, K.K.
  • Soler, Alfonso

Abstract

Several years of measured data on global and diffuse radiation and sunshine duration for 40 widely spread locations in the latitude range 36° S to 60° N are used to develop and test models for estimating monthly-mean, daily, diffuse radiation on horizontal surfaces. Applicability of the clearness-index (K) and sunshine fraction (SSO) models for diffuse estimation and the effect of combining several variables into a single multilinear equation are tested. Correlations connecting the diffuse to global fraction (HdH) with K and SSO predict Hd values more accurately than their separate use. Among clearness-index and sunshine-fraction models, SSO models are found to have better accuracy if correlations are developed for wide latitude ranges. By including a term for declinations in the correlation, the accuracy of the estimated data can be marginally improved. The addition of latitude to the equation does not help to improve the accuracy further.

Suggested Citation

  • Gopinathan, K.K. & Soler, Alfonso, 1995. "Diffuse radiation models and monthly-average, daily, diffuse data for a wide latitude range," Energy, Elsevier, vol. 20(7), pages 657-667.
    • Handle: RePEc:eee:energy:v:20:y:1995:i:7:p:657-667
    DOI: 10.1016/0360-5442(95)00004-Z
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    1. Soler, A. & Oteiza, P., 1994. "A search for the best relation to be used to estimate monthly mean daily diffuse solar radiation on a horizontal surface for Europe," Renewable Energy, Elsevier, vol. 5(5), pages 1517-1519.
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    Cited by:

    1. Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
    2. Li, Huashan & Bu, Xianbiao & Lian, Yongwang & Zhao, Liang & Ma, Weibin, 2012. "Further investigation of empirically derived models with multiple predictors in estimating monthly average daily diffuse solar radiation over China," Renewable Energy, Elsevier, vol. 44(C), pages 469-473.
    3. Elminir, Hamdy K., 2007. "Experimental and theoretical investigation of diffuse solar radiation: Data and models quality tested for Egyptian sites," Energy, Elsevier, vol. 32(1), pages 73-82.
    4. Francesco Pasanisi & Gaia Righini & Massimo D’Isidoro & Lina Vitali & Gino Briganti & Sergio Grauso & Lorenzo Moretti & Carlo Tebano & Gabriele Zanini & Mabafokeng Mahahabisa & Mosuoe Letuma & Muso Ra, 2021. "A Cooperation Project in Lesotho: Renewable Energy Potential Maps Embedded in a WebGIS Tool," Sustainability, MDPI, vol. 13(18), pages 1-26, September.
    5. Pandey, Chanchal Kumar & Katiyar, A.K., 2009. "A comparative study to estimate daily diffuse solar radiation over India," Energy, Elsevier, vol. 34(11), pages 1792-1796.
    6. Khorasanizadeh, Hossein & Mohammadi, Kasra, 2016. "Diffuse solar radiation on a horizontal surface: Reviewing and categorizing the empirical models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 338-362.
    7. Li, Huashan & Bu, Xianbiao & Long, Zhen & Zhao, Liang & Ma, Weibin, 2012. "Calculating the diffuse solar radiation in regions without solar radiation measurements," Energy, Elsevier, vol. 44(1), pages 611-615.
    8. Jamil, Basharat & Akhtar, Naiem, 2017. "Comparison of empirical models to estimate monthly mean diffuse solar radiation from measured data: Case study for humid-subtropical climatic region of India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1326-1342.
    9. Wang, Lunche & Lu, Yunbo & Zou, Ling & Feng, Lan & Wei, Jing & Qin, Wenmin & Niu, Zigeng, 2019. "Prediction of diffuse solar radiation based on multiple variables in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 151-216.
    10. Yang, Liu & Cao, Qimeng & Yu, Ying & Liu, Yan, 2020. "Comparison of daily diffuse radiation models in regions of China without solar radiation measurement," Energy, Elsevier, vol. 191(C).
    11. Despotovic, Milan & Nedic, Vladimir & Despotovic, Danijela & Cvetanovic, Slobodan, 2016. "Evaluation of empirical models for predicting monthly mean horizontal diffuse solar radiation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 246-260.
    12. Elminir, Hamdy K. & Azzam, Yosry A. & Younes, Farag I., 2007. "Prediction of hourly and daily diffuse fraction using neural network, as compared to linear regression models," Energy, Elsevier, vol. 32(8), pages 1513-1523.
    13. Mohammadi, Kasra & Shamshirband, Shahaboddin & Petković, Dalibor & Khorasanizadeh, Hossein, 2016. "Determining the most important variables for diffuse solar radiation prediction using adaptive neuro-fuzzy methodology; case study: City of Kerman, Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1570-1579.
    14. Sabzpooshani, Majid & Mohammadi, Kasra, 2014. "Establishing new empirical models for predicting monthly mean horizontal diffuse solar radiation in city of Isfahan, Iran," Energy, Elsevier, vol. 69(C), pages 571-577.
    15. 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.
    16. Notton, Gilles & Paoli, Christophe & Vasileva, Siyana & Nivet, Marie Laure & Canaletti, Jean-Louis & Cristofari, Christian, 2012. "Estimation of hourly global solar irradiation on tilted planes from horizontal one using artificial neural networks," Energy, Elsevier, vol. 39(1), pages 166-179.
    17. Bakirci, Kadir, 2015. "Models for the estimation of diffuse solar radiation for typical cities in Turkey," Energy, Elsevier, vol. 82(C), pages 827-838.
    18. Jin, Zhou & Yezheng, Wu & Gang, Yan, 2004. "Estimation of daily diffuse solar radiation in China," Renewable Energy, Elsevier, vol. 29(9), pages 1537-1548.

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