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Estimation of hourly direct normal from measured global solar irradiance in Spain

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  • López, Gabriel
  • Rubio, Miguel Angel
  • Batlles, Francisco J.

Abstract

The availability of a good data set, registered in six Spanish locations, including several radiometric variables, has been used to test different approaches for estimating hourly direct normal irradiance by decomposition models. Models proposed by different authors have been tested. Following this preliminary study, to improve the kb–kt correlations, another geometric variable has been used as a predictor of hourly beam transmittance, kb, by means of piecewise correlations. The new beam transmittance correlations, which include additional geometric information, reduce the root mean square deviation. In addition, they show a better performance in terms of the determination coefficient of the regression analysis of measured vs calculated values, providing an improved capture of the real world effects than models that are function of the clearness index only. A new model that uses only two ranges of clearness index is proposed. The proposed model shows seasonal dependence and thus we have developed a seasonal version of it. However, the performance of the seasonal version has proved to be similar to the corresponding annual model.

Suggested Citation

  • López, Gabriel & Rubio, Miguel Angel & Batlles, Francisco J., 2000. "Estimation of hourly direct normal from measured global solar irradiance in Spain," Renewable Energy, Elsevier, vol. 21(2), pages 175-186.
    • Handle: RePEc:eee:renene:v:21:y:2000:i:2:p:175-186
    DOI: 10.1016/S0960-1481(99)00121-4
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    References listed on IDEAS

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    1. Rerhrhaye, A. & Zehaf, M. & Flechon, J., 1995. "Estimation of the direct beam from seasonal correlations," Renewable Energy, Elsevier, vol. 6(7), pages 779-785.
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    Cited by:

    1. Nikitidou, E. & Kazantzidis, A. & Salamalikis, V., 2014. "The aerosol effect on direct normal irradiance in Europe under clear skies," Renewable Energy, Elsevier, vol. 68(C), pages 475-484.
    2. Kambezidis, H.D. & Psiloglou, B.E. & Karagiannis, D. & Dumka, U.C. & Kaskaoutis, D.G., 2017. "Meteorological Radiation Model (MRM v6.1): Improvements in diffuse radiation estimates and a new approach for implementation of cloud products," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 616-637.
    3. Nikitidou, E. & Kazantzidis, A. & Tzoumanikas, P. & Salamalikis, V. & Bais, A.F., 2015. "Retrieval of surface solar irradiance, based on satellite-derived cloud information, in Greece," Energy, Elsevier, vol. 90(P1), pages 776-783.
    4. Chen, Rensheng & Kang, Ersi & Ji, Xibin & Yang, Jianping & Wang, Junhai, 2007. "An hourly solar radiation model under actual weather and terrain conditions: A case study in Heihe river basin," Energy, Elsevier, vol. 32(7), pages 1148-1157.
    5. Dahmani, Kahina & Notton, Gilles & Voyant, Cyril & Dizene, Rabah & Nivet, Marie Laure & Paoli, Christophe & Tamas, Wani, 2016. "Multilayer Perceptron approach for estimating 5-min and hourly horizontal global irradiation from exogenous meteorological data in locations without solar measurements," Renewable Energy, Elsevier, vol. 90(C), pages 267-282.
    6. López, G. & Batlles, F.J. & Tovar-Pescador, J., 2005. "Selection of input parameters to model direct solar irradiance by using artificial neural networks," Energy, Elsevier, vol. 30(9), pages 1675-1684.
    7. Teke, Ahmet & Yıldırım, H. Başak & Çelik, Özgür, 2015. "Evaluation and performance comparison of different models for the estimation of solar radiation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 1097-1107.

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