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On a universal model for the prediction of the daily global solar radiation

Author

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  • Kaplanis, S.
  • Kumar, Jatin
  • Kaplani, E.

Abstract

A model to predict the mean expected daily global solar radiation, H(n) on a day n, at a site with latitude φ is proposed. The model is based on two cosine functions. A regression analysis taking into account the mean measured values Hm.meas(n) obtained from SoDa database for 42 sites in the Northern Hemisphere resulted in a set of mathematical expressions of split form to predict H(n). The parameters of the two cosine model for 0°<φ < 23° are obtained by regression analysis using a sum of 3–8 Gaussian functions, while for 23°<φ < 71° the two cosine model parameters are expressed by a sum of exponential functions or the product of an exponential and a cosine function. The main equation of the model and the set of parametric expressions provide H(n) for any φ on Earth. Validation results of this model are provided along with the statistical estimators NMBE, NRMSE and t-statistic in comparison to the corresponding values from three databases of NASA, SoDa and the measured values from ground stations provided in Meteonorm.

Suggested Citation

  • Kaplanis, S. & Kumar, Jatin & Kaplani, E., 2016. "On a universal model for the prediction of the daily global solar radiation," Renewable Energy, Elsevier, vol. 91(C), pages 178-188.
    • Handle: RePEc:eee:renene:v:91:y:2016:i:c:p:178-188
    DOI: 10.1016/j.renene.2016.01.037
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    Citations

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    Cited by:

    1. Akarslan, Emre & Hocaoglu, Fatih Onur, 2017. "A novel method based on similarity for hourly solar irradiance forecasting," Renewable Energy, Elsevier, vol. 112(C), pages 337-346.
    2. Mohammadi, Kasra & Shamshirband, Shahaboddin & Kamsin, Amirrudin & Lai, P.C. & Mansor, Zulkefli, 2016. "Identifying the most significant input parameters for predicting global solar radiation using an ANFIS selection procedure," Renewable and Sustainable Energy Reviews, Elsevier, vol. 63(C), pages 423-434.
    3. 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).
    4. Rao K, D.V. Siva Krishna & Premalatha, M. & Naveen, C., 2018. "Analysis of different combinations of meteorological parameters in predicting the horizontal global solar radiation with ANN approach: A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 248-258.
    5. Kaplani, E. & Kaplanis, S. & Mondal, S., 2018. "A spatiotemporal universal model for the prediction of the global solar radiation based on Fourier series and the site altitude," Renewable Energy, Elsevier, vol. 126(C), pages 933-942.

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