PV shading fault detection and classification based on I-V curve using principal component analysis: Application to isolated PV system

S. Fadhel 1 Claude Delpha 2 Demba Diallo 1 I. Bahri 1 A. Migan 1 M. Trabelsi M.F. Mimouni
1 GeePs - Laboratoire Génie électrique et électronique de Paris
2 L2S - Laboratoire des signaux et systèmes
Abstract : Health monitoring and diagnosis of photovoltaic (PV) systems is becoming crucial to maximise the power production, increase the reliability and life service of PV power plants. Operating under faulty conditions, in particular under shading, PV plants have remarkable shape of current-voltage (I-V) characteristics in comparison to reference condition (healthy operation). Based on real electrical measurements (I-V), the present work aims to provide a very simple, robust and low cost Fault Detection and Classification (FDC) method for PV shading faults. At first, we extract the features for different experimental tests under healthy and shading conditions to build the database. The features are then analysed using Principal Component Analysis (PCA). The accuracy of the data classification into the PCA space is evaluated using the confusion matrix as a metric of class separability. The results using experimental data of a 250 Wp PV module are very promising with a successful classification rate higher than 97% with four different configurations. The method is also cost effective as it uses only electrical measurements that are already available. No additional sensors are required.
Keywords : PV shading faults I-V curves Principal component analysis Fault detection Fault classification
Type de document :
Article dans une revue
Solar Energy, Elsevier, 2019, 179, pp.1-10. 〈10.1016/j.solener.2018.12.048〉
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https://hal-centralesupelec.archives-ouvertes.fr/hal-01970593
Contributeur : Claude Delpha <>
Soumis le : samedi 5 janvier 2019 - 16:38:47
Dernière modification le : samedi 23 mars 2019 - 01:40:13

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CENTRALESUPELEC | UNIV-PARIS-SACLAY | SORBONNE-UNIVERSITE | SUP_SIGNAUX | SUP_LSS | ECO2 | L2S | PHEMADIC | GEEPS | SU-SCIENCES

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S. Fadhel, Claude Delpha, Demba Diallo, I. Bahri, A. Migan, et al.. PV shading fault detection and classification based on I-V curve using principal component analysis: Application to isolated PV system. Solar Energy, Elsevier, 2019, 179, pp.1-10. 〈10.1016/j.solener.2018.12.048〉. 〈hal-01970593〉

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