Faults diagnosis in a photovoltaic system based on multivariate statistical analysis

Improving the efficiency of photovoltaic (PV) systems has gained priority in current research due to the large volumes of PV panels installed. Moreover, the remarkable efforts made to investigate d...

[1]  Aissa Chouder,et al.  Automatic fault detection in grid connected PV systems , 2013 .

[2]  Si-Zhao Joe Qin,et al.  Reconstruction-based contribution for process monitoring , 2009, Autom..

[3]  Mahmoud Dhimish,et al.  A Comprehensive Review on Bypass Diode Application on Photovoltaic Modules , 2020, Energies.

[4]  Evan J. Benoit,et al.  Detection and Localization of Damaged Photovoltaic Cells and Modules Using Spread Spectrum Time Domain Reflectometry , 2021, IEEE Journal of Photovoltaics.

[5]  Siva Ramakrishna Madeti,et al.  A comprehensive study on different types of faults and detection techniques for solar photovoltaic system , 2017 .

[6]  Xiu Yao,et al.  Characteristic Study and Time-Domain Discrete- Wavelet-Transform Based Hybrid Detection of Series DC Arc Faults , 2014, IEEE Transactions on Power Electronics.

[7]  Douglas L. Maskell,et al.  Automatic fault detection and diagnosis for photovoltaic systems using combined artificial neural network and analytical based methods , 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

[8]  Demba Diallo,et al.  Data-driven approach for isolated PV shading fault diagnosis based on experimental I-V curves analysis , 2018, 2018 IEEE International Conference on Industrial Technology (ICIT).

[9]  Mousumi Basu,et al.  Metaheuristic optimization based fault diagnosis strategy for solar photovoltaic systems under non-uniform irradiance , 2018 .

[10]  A Self-adaptive Algorithm with Newton Raphson Method for Parameters Identification of Photovoltaic Modules and Array , 2021, Transactions on Electrical and Electronic Materials.

[11]  W. Shen,et al.  Deep learning‐based automatic detection of multitype defects in photovoltaic modules and application in real production line , 2021, Progress in Photovoltaics: Research and Applications.

[12]  Heng Tao Shen,et al.  Principal Component Analysis , 2009, Encyclopedia of Biometrics.

[13]  Hyung-Keun Ahn,et al.  Fault Detection for Photovoltaic Systems Using Multivariate Analysis With Electrical and Environmental Variables , 2021, IEEE Journal of Photovoltaics.

[14]  Kelaiaia Mounia Samira,et al.  Automatic detection of faults in a photovoltaic power plant based on the observation of degradation indicators , 2021 .

[15]  Imen Bahri,et al.  PV shading fault detection and classification based on I-V curve using principal component analysis: Application to isolated PV system , 2019, Solar Energy.

[16]  Marko V. Jankovic,et al.  The Detection of Series Arc Fault in Photovoltaic Systems Based on the Arc Current Entropy , 2016, IEEE Transactions on Power Electronics.

[17]  Zahoor Uddin,et al.  ICA ‐based solar photovoltaic fault diagnosis , 2020 .

[18]  Djordje Stojic,et al.  Series arc fault detection in photovoltaic system by small‐signal impedance and noise monitoring , 2020, International Transactions on Electrical Energy Systems.

[19]  Juvenal Rodríguez-Reséndiz,et al.  Photovoltaic Failure Detection Based on String-Inverter Voltage and Current Signals , 2021, IEEE Access.

[20]  Pierre Ele,et al.  Enhanced Vibrating Particles System Algorithm for Parameters Estimation of Photovoltaic System , 2019, Journal of Power and Energy Engineering.

[21]  Mustapha Raoufi,et al.  Characteristic curve diagnosis based on fuzzy classification for a reliable photovoltaic fault monitoring , 2021 .

[22]  Eluri N.V.D.V. Prasad,et al.  Fault analysis in photovoltaic generation based DC microgrid using multifractal detrended fluctuation analysis , 2020 .

[23]  Radu Platon,et al.  Online Fault Detection in PV Systems , 2015, IEEE Transactions on Sustainable Energy.

[24]  Junjie Wang,et al.  Fault diagnosis method of photovoltaic array based on support vector machine , 2019 .

[25]  Saad Mekhilef,et al.  Real-time fault detection in PV systems under MPPT using PMU and high-frequency multi-sensor data through online PCA-KDE-based multivariate KL divergence , 2021 .

[26]  Pierre Ele,et al.  Important notes on parameter estimation of solar photovoltaic cell , 2019, Energy Conversion and Management.

[27]  Gi-Hwan Kang,et al.  Analysis of electrical and thermal characteristics of PV array under mismatching conditions caused by partial shading and short circuit failure of bypass diodes , 2021 .

[28]  Saad Mekhilef,et al.  Shading fault detection in a grid-connected PV system using vertices principal component analysis , 2021 .

[29]  Zhehan Yi,et al.  Line-to-Line Fault Detection for Photovoltaic Arrays Based on Multiresolution Signal Decomposition and Two-Stage Support Vector Machine , 2017, IEEE Transactions on Industrial Electronics.

[30]  Honglu Zhu,et al.  Deep‐learning–based method for faults classification of PV system , 2021, IET Renewable Power Generation.

[31]  G. Saravana Ilango,et al.  Online Fault Detection and Diagnosis in Photovoltaic Systems Using Wavelet Packets , 2018, IEEE Journal of Photovoltaics.

[32]  Elyes Garoudja,et al.  An enhanced machine learning based approach for failures detection and diagnosis of PV systems , 2017 .

[33]  Her-Terng Yau,et al.  Photovoltaic Energy Conversion System Fault Detection Using Fractional-Order Color Relation Classifier in Microdistribution Systems , 2017, IEEE Transactions on Smart Grid.

[34]  Sofiane Kichou,et al.  Efficient fault detection and diagnosis procedure for photovoltaic systems , 2016, 2016 8th International Conference on Modelling, Identification and Control (ICMIC).

[35]  Jin Hyun Park,et al.  Fault detection and identification of nonlinear processes based on kernel PCA , 2005 .

[36]  Patrick Juvet Gnetchejo,et al.  Reply to comment on “Important notes on parameter estimation of solar photovoltaic cell”, by Gnetchejo et al. [Energy Conversion and Management, https://doi.org/10.1016/j.enconman.2019.111870.] , 2019, Energy Conversion and Management.

[37]  M. Nounou,et al.  Kernel PCA- and Kernel PLS-based generalized likelihood ratio tests for fault detection , 2020 .

[38]  Teymoor Ghanbari,et al.  A current based approach for hotspot detection in photovoltaic strings , 2019, International Transactions on Electrical Energy Systems.

[39]  Patrick Juvet Gnetchejo,et al.  A combination of Newton-Raphson method and heuristics algorithms for parameter estimation in photovoltaic modules , 2021, Heliyon.

[40]  Tarek A. Mahmoud,et al.  Fault diagnosis of time-varying processes using modified reconstruction-based contributions , 2018, Journal of Process Control.

[41]  Hazem Nounou,et al.  Reduced Kernel Random Forest Technique for Fault Detection and Classification in Grid-Tied PV Systems , 2020, IEEE Journal of Photovoltaics.

[42]  T. Hiyama,et al.  Controlling of artificial neural network for fault diagnosis of photovoltaic array , 2011, 2011 16th International Conference on Intelligent System Applications to Power Systems.

[43]  B. Lehman,et al.  Decision tree-based fault detection and classification in solar photovoltaic arrays , 2012, 2012 Twenty-Seventh Annual IEEE Applied Power Electronics Conference and Exposition (APEC).

[44]  Arnulf Jäger-Waldau,et al.  Snapshot of Photovoltaics—February 2020 , 2020, Energies.

[45]  H. Mekki,et al.  Artificial neural network-based modelling and fault detection of partial shaded photovoltaic modules , 2016, Simul. Model. Pract. Theory.

[46]  Xinghua Zhang,et al.  Review and Performance Evaluation of Photovoltaic Array Fault Detection and Diagnosis Techniques , 2019, International Journal of Photoenergy.

[47]  Peijie Lin,et al.  Online Fault Diagnosis for Photovoltaic Arrays Based on Fisher Discrimination Dictionary Learning for Sparse Representation , 2021, IEEE Access.

[48]  Lijun Wu,et al.  Intelligent fault diagnosis of photovoltaic arrays based on optimized kernel extreme learning machine and I-V characteristics , 2017 .