Line-to-Line Faults Detection for Photovoltaic Arrays Based on I-V Curve Using Pattern Recognition

Aref Eskandari; Jafar Milimonfared; Mohammadreza Aghaei; Aline Kirsten Vidal De Oliveira; Ricardo Ruther

doi:10.1109/PVSC40753.2019.8981385

Line-to-Line Faults Detection for Photovoltaic Arrays Based on I-V Curve Using Pattern Recognition

Aref Eskandari, Jafar Milimonfared, Mohammadreza Aghaei, Aline Kirsten Vidal De Oliveira, Ricardo Ruther

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

7 Citaten (Scopus)

Samenvatting

Fault detection plays a crucial role in reliability and safety of photovoltaic systems. However, the fault detection by the conventional protection devices is always difficult due to nonlinear characteristics of PV systems, Maximum Power Point Tracking (MPPT), low irradiation, and high fault impedance. In addition, it may lead to the power losses, efficiency reduction and even fire hazard. This paper proposes an innovative fault detection method based on the pattern recognition techniques and extraction of the essential features from the current-voltage (I-V) characteristics. The main benefit of this method is using less data to detect faults while improving accuracy. The primary results demonstrate that the proposed method is accurate, effective and reliable for detecting line-line faults in PV systems.

Originele taal-2	Engels
Titel	2019 IEEE 46th Photovoltaic Specialists Conference, PVSC 2019
Uitgeverij	Institute of Electrical and Electronics Engineers
Pagina's	503-507
Aantal pagina's	5
ISBN van elektronische versie	9781728104942
DOI's	https://doi.org/10.1109/PVSC40753.2019.8981385
Status	Gepubliceerd - jun. 2019
Extern gepubliceerd	Ja
Evenement	46th IEEE Photovoltaic Specialists Conference, PVSC 2019 - Chicago, Verenigde Staten van Amerika Duur: 16 jun. 2019 → 21 jun. 2019

Congres

Congres	46th IEEE Photovoltaic Specialists Conference, PVSC 2019
Land/Regio	Verenigde Staten van Amerika
Stad	Chicago
Periode	16/06/19 → 21/06/19

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10.1109/PVSC40753.2019.8981385

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Eskandari, A., Milimonfared, J., Aghaei, M., Vidal De Oliveira, A. K., & Ruther, R. (2019). Line-to-Line Faults Detection for Photovoltaic Arrays Based on I-V Curve Using Pattern Recognition. In 2019 IEEE 46th Photovoltaic Specialists Conference, PVSC 2019 (blz. 503-507). Artikel 8981385 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/PVSC40753.2019.8981385

@inproceedings{4356c367a74344e5a343d188b7f9695f,

title = "Line-to-Line Faults Detection for Photovoltaic Arrays Based on I-V Curve Using Pattern Recognition",

abstract = "Fault detection plays a crucial role in reliability and safety of photovoltaic systems. However, the fault detection by the conventional protection devices is always difficult due to nonlinear characteristics of PV systems, Maximum Power Point Tracking (MPPT), low irradiation, and high fault impedance. In addition, it may lead to the power losses, efficiency reduction and even fire hazard. This paper proposes an innovative fault detection method based on the pattern recognition techniques and extraction of the essential features from the current-voltage (I-V) characteristics. The main benefit of this method is using less data to detect faults while improving accuracy. The primary results demonstrate that the proposed method is accurate, effective and reliable for detecting line-line faults in PV systems.",

keywords = "Fault Detection, Line-Line Fault, Machine Learning Algorithm, Pattern Recognition, Photovoltaic System",

author = "Aref Eskandari and Jafar Milimonfared and Mohammadreza Aghaei and {Vidal De Oliveira}, {Aline Kirsten} and Ricardo Ruther",

year = "2019",

month = jun,

doi = "10.1109/PVSC40753.2019.8981385",

language = "English",

pages = "503--507",

booktitle = "2019 IEEE 46th Photovoltaic Specialists Conference, PVSC 2019",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "46th IEEE Photovoltaic Specialists Conference, PVSC 2019 ; Conference date: 16-06-2019 Through 21-06-2019",

}

Eskandari, A, Milimonfared, J, Aghaei, M, Vidal De Oliveira, AK & Ruther, R 2019, Line-to-Line Faults Detection for Photovoltaic Arrays Based on I-V Curve Using Pattern Recognition. in 2019 IEEE 46th Photovoltaic Specialists Conference, PVSC 2019., 8981385, Institute of Electrical and Electronics Engineers, blz. 503-507, 46th IEEE Photovoltaic Specialists Conference, PVSC 2019, Chicago, Verenigde Staten van Amerika, 16/06/19. https://doi.org/10.1109/PVSC40753.2019.8981385

Line-to-Line Faults Detection for Photovoltaic Arrays Based on I-V Curve Using Pattern Recognition. / Eskandari, Aref; Milimonfared, Jafar; Aghaei, Mohammadreza et al.
2019 IEEE 46th Photovoltaic Specialists Conference, PVSC 2019. Institute of Electrical and Electronics Engineers, 2019. blz. 503-507 8981385.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

TY - GEN

T1 - Line-to-Line Faults Detection for Photovoltaic Arrays Based on I-V Curve Using Pattern Recognition

AU - Eskandari, Aref

AU - Milimonfared, Jafar

AU - Aghaei, Mohammadreza

AU - Vidal De Oliveira, Aline Kirsten

AU - Ruther, Ricardo

PY - 2019/6

Y1 - 2019/6

N2 - Fault detection plays a crucial role in reliability and safety of photovoltaic systems. However, the fault detection by the conventional protection devices is always difficult due to nonlinear characteristics of PV systems, Maximum Power Point Tracking (MPPT), low irradiation, and high fault impedance. In addition, it may lead to the power losses, efficiency reduction and even fire hazard. This paper proposes an innovative fault detection method based on the pattern recognition techniques and extraction of the essential features from the current-voltage (I-V) characteristics. The main benefit of this method is using less data to detect faults while improving accuracy. The primary results demonstrate that the proposed method is accurate, effective and reliable for detecting line-line faults in PV systems.

AB - Fault detection plays a crucial role in reliability and safety of photovoltaic systems. However, the fault detection by the conventional protection devices is always difficult due to nonlinear characteristics of PV systems, Maximum Power Point Tracking (MPPT), low irradiation, and high fault impedance. In addition, it may lead to the power losses, efficiency reduction and even fire hazard. This paper proposes an innovative fault detection method based on the pattern recognition techniques and extraction of the essential features from the current-voltage (I-V) characteristics. The main benefit of this method is using less data to detect faults while improving accuracy. The primary results demonstrate that the proposed method is accurate, effective and reliable for detecting line-line faults in PV systems.

KW - Fault Detection

KW - Line-Line Fault

KW - Machine Learning Algorithm

KW - Pattern Recognition

KW - Photovoltaic System

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U2 - 10.1109/PVSC40753.2019.8981385

DO - 10.1109/PVSC40753.2019.8981385

M3 - Conference contribution

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BT - 2019 IEEE 46th Photovoltaic Specialists Conference, PVSC 2019

PB - Institute of Electrical and Electronics Engineers

T2 - 46th IEEE Photovoltaic Specialists Conference, PVSC 2019

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ER -

Line-to-Line Faults Detection for Photovoltaic Arrays Based on I-V Curve Using Pattern Recognition

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