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Prediction of Time Series of Photovoltaic Energy Production Using Artificial Neural Networks

  • A. ElamimEmail author
  • B. Hartiti
  • A. Barhdadi
  • A. Haibaoui
  • A. Lfakir
  • P. Thevenin
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 912)

Abstract

An artificial neural network (ANN) model is used for forecasting the power provided by photovoltaic solar panels using feed forward neural network (FFNN) of a photovoltaic installation located in the city of Mohammedia (Morocco). One year of hourly data on solar irradiance, ambient temperature and output PV power were available for this study. For this, different combinations of inputs with different numbers of hidden neurons were considered. To evaluate this model several statistic parameters were used such, as the coefficient of determination (R2), the Root Mean Squared Error (RMSE) and the Mean Absolute Error (MAE). The results of this model, tested on unknown data, showed that the model works well, with determination coefficients lying between 0.98 and 0.998 for sunny days and between 0.82 and 0.96 for cloudy days.

Keywords

Photovoltaic installation Feed forward neural network Artificial neural network 

Notes

Acknowledgements

The authors would like to thank “Institute for Research in Solar Energy and New Energies (IRESEN)” for the financing of the project PROPRE.MA.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • A. Elamim
    • 1
    Email author
  • B. Hartiti
    • 1
    • 2
  • A. Barhdadi
    • 3
  • A. Haibaoui
    • 1
    • 4
  • A. Lfakir
    • 5
  • P. Thevenin
    • 6
  1. 1.ERDYS Laboratory, MEEM & DD GroupHassan II University of CasablancaMohammediaMorocco
  2. 2.ICTP, UNESCOTriesteItaly
  3. 3.Energy Research CentreEcole Normale Supérieure (ENS) Mohammed V UniversityRabatMorocco
  4. 4.LIMAT Laboratory, Department of PhysicsUniversity Hassan II FSBCasablancaMorocco
  5. 5.University Sultan Moulay Slimane FSTBBeni MelallMorocco
  6. 6.LMOPS Laboratory, Department of PhysicsUniversity of Lorraine MetzLorraineFrance

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