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Application of artificial neural networks for forecasting photovoltaic system parameters

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Abstract

The main element which justifies the installation of a photovoltaic system is the solar energy potential. Various structures of artificial neural networks (ANNs) are used for predicting the sun location, the global solar radiation (GSR) at horizontal and inclined plans. Real meteorological data have been exploited in order to validate the computation results. The ANNs are also carried out to predict the current-voltage characteristics of the photovoltaic module. It can be concluded that the ANNs effectively predict the behavior of photovoltaic system parameters with good a coefficient of determination.

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Authors and Affiliations

  1. University M’HamedBougara of Boumerdès, Boumerdès, Algeria

    Lalia Miloudi, Dalila Acheli & Mohamed Kesraoui

Authors
  1. Lalia Miloudi
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  2. Dalila Acheli
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  3. Mohamed Kesraoui
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Correspondence to Lalia Miloudi.

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Miloudi, L., Acheli, D. & Kesraoui, M. Application of artificial neural networks for forecasting photovoltaic system parameters. Appl. Sol. Energy 53, 85–91 (2017). https://doi.org/10.3103/S0003701X17020104

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  • DOI: https://doi.org/10.3103/S0003701X17020104

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