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Small-scale solar radiation forecasting using ARMA and nonlinear autoregressive neural network models

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Abstract

This paper aims to introduce an approach for multi-hour forecasting (915 h ahead) of hourly global horizontal solar radiation time series and forecasting of a small-scale solar radiation database (30- and 1-s scales) for a period of 1 day (47,000 s ahead) using commonly and available measured meteorological solar radiation. Three methods are considered in this study. First, autoregressive–moving-average (ARMA) model is used to predict future values of the global solar radiation time series. However, because of the non-stationarity of solar radiation time series, a phase of detrending is needed to stationarize the irradiation data; a 6-degree polynomial model is found to be the most stationary one. Secondly, due to the nonlinearity presented in solar radiation time series, a nonlinear autoregressive (NAR) neural network model is used for prediction purposes. Taking into account the advantages of both models, the goodness of ARMA for linear problems and NAR for nonlinear problems, a hybrid method combining ARMA and NAR is introduced to produce better results. The validation process for the site of Ghardaia in Algaria shows that the hybrid model gives a normalized root mean square error (NRMSE) equals to 0.2034 compared to a NRMSE equal to 0.2634 for NAR model and 0.3241 for ARMA model.

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Acknowledgments

The authors would like to thank the University of Laghouat for the financial aspect of the present work. Also, the authors would like to thank Dr. Tamer Khatib and Dr. Hussian Kazem for providing experimental data used for further validation of the proposed model. These data were obtained from an experiment done in the frame of the research project no. ORG SU EI 11 010. Funded by the research council of the Sultanate of Oman.

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Authors and Affiliations

  1. Unité de Recherche des Matériaux et Energies Renouvelables, Department of Physics, Faculty of Science, Abou Bekr Belkaid University, BP 119, Tlemcen, 13000, Algeria

    Khalil Benmouiza

  2. Laboratoire des Semiconducteurs et Matériaux Fonctionnels, Université Amar Telidji de Laghouat, Bd des Martyrs, BP 37G, Laghouat, 03000, Algérie

    Ali Cheknane

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  1. Khalil Benmouiza
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  2. Ali Cheknane
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Correspondence to Ali Cheknane.

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Benmouiza, K., Cheknane, A. Small-scale solar radiation forecasting using ARMA and nonlinear autoregressive neural network models. Theor Appl Climatol 124, 945–958 (2016). https://doi.org/10.1007/s00704-015-1469-z

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  • DOI: https://doi.org/10.1007/s00704-015-1469-z

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