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The most suitable prediction model of the solar intensity, on horizontal plane, at various weather conditions in a specified location in Morocco

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  • El Mghouchi, Y.
  • Ajzoul, T.
  • Taoukil, D.
  • El Bouardi, A.

Abstract

This study aims to examine the performance of few solar radiation models developed in the literature to estimate the amount of solar radiation at a specified position, case study, Tetuan city in northern of Morocco. Ten models have been identified and evaluated on the basis of several statistical indicators by using the MATLAB environment, which are based on recorded data from a local meteorological station implemented in the Faculty of Sciences of Tetuan. The statistical test includes six parameters namely mean bias error, root mean square error, normal root mean square error, mean absolute percentage error, t-statistic and standard deviation. Other analysis is made on the basis of coefficient of determination R² and linear regression coefficients (the slope a and the constant b). The analysis of results revealed that the studied models have not the same accuracy, and it is concluded that there are the models that can be preferred for the estimation of solar radiation in the studied site. The obtained results indicate that model 9 (El Mghouchi model), model 6 (Ghouard model) and model 8 (Campbell model) are performing better than the others for instantaneous, daily and monthly solar estimations, respectively.

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  • El Mghouchi, Y. & Ajzoul, T. & Taoukil, D. & El Bouardi, A., 2016. "The most suitable prediction model of the solar intensity, on horizontal plane, at various weather conditions in a specified location in Morocco," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 84-98.
    • Handle: RePEc:eee:rensus:v:54:y:2016:i:c:p:84-98
    DOI: 10.1016/j.rser.2015.09.089
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    Cited by:

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    3. Sun, Xixi & Bright, Jamie M. & Gueymard, Christian A. & Acord, Brendan & Wang, Peng & Engerer, Nicholas A., 2019. "Worldwide performance assessment of 75 global clear-sky irradiance models using Principal Component Analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 550-570.
    4. Germán Ramos Ruiz & Carlos Fernández Bandera, 2017. "Validation of Calibrated Energy Models: Common Errors," Energies, MDPI, vol. 10(10), pages 1-19, October.

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