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Prediction PV Power Based on Artificial Neural Networks

  • Lalia MiloudiEmail author
  • Dalila Acheli
  • Saad Mekhilef
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 62)

Abstract

The goal of this contribution is to estimate the power delivered by a multicrystals solar photovoltaic module based on artificial neural networks. Two structures of ANNs were tested: multiple-layer perceptron and radial basic function. The results obtained gave good coefficients of correlation, the statistical R2-value obtained is about 0.96 to predict this important parameter.

Keywords

Artificial neural network (ANNs) Multiple-layer perceptron (MLP) Radial basic function (RBF) Photovoltaic (PV) power 

Notes

Acknowledgments

The first author would like to thank the System National of Documentation on Line (SNDL) for facilitate download articles as well as Pr S. Mekhilef from PEARL laboratory of University of Malaya, and Dr H. Sarimveis from National Technical University of Athens Greece.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.University of BoumerdèsBoumerdèsAlgeria
  2. 2.University of MalayaKuala LumpurMalaysia

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