Neural network based integration of MPPT and diagnosis of degradation for photovoltaic module

The artificial neural network was used in this paper as a model for monitoring the degradation of solar cells of a photovoltaic module. Two dependent models based neural networks have been used, the first one ensures identification of series and parallel resistance characterizing the intrinsic struc...

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Bibliographic Details
Published in:Optical and quantum electronics 2016-02, Vol.48 (2), Article 105
Main Authors: Dkhichi, Fayrouz, Oukarfi, Benyounes, El Kouari, Youssef, Ouoba, David, Fakkar, Abderrahim
Format: Article
Language:English
Subjects:
Advanced Materials for photonics and electronics
Characterization and Evaluation of Materials
Computer Communication Networks
Electrical Engineering
Lasers
Optical Devices
Optics
Photonics
Physics
Physics and Astronomy
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Summary:The artificial neural network was used in this paper as a model for monitoring the degradation of solar cells of a photovoltaic module. Two dependent models based neural networks have been used, the first one ensures identification of series and parallel resistance characterizing the intrinsic structure of solar cells, while the second one allows the prediction of the normalized value of degradation in terms of maximum power and also provides intelligent control of a photovoltaic system. During the latter, the model provides the duty cycle value that corresponds to the deterioration in photovoltaic module.
ISSN:0306-8919
1572-817X
DOI:10.1007/s11082-015-0355-3