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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

7 Citations (Scopus)

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.

Original language	English
Title of host publication	2019 IEEE 46th Photovoltaic Specialists Conference, PVSC 2019
Publisher	Institute of Electrical and Electronics Engineers
Pages	503-507
Number of pages	5
ISBN (Electronic)	9781728104942
DOIs	https://doi.org/10.1109/PVSC40753.2019.8981385
Publication status	Published - Jun 2019
Externally published	Yes
Event	46th IEEE Photovoltaic Specialists Conference, PVSC 2019 - Chicago, United States Duration: 16 Jun 2019 → 21 Jun 2019

Conference

Conference	46th IEEE Photovoltaic Specialists Conference, PVSC 2019
Country/Territory	United States
City	Chicago
Period	16/06/19 → 21/06/19

Keywords

Fault Detection
Line-Line Fault
Machine Learning Algorithm
Pattern Recognition
Photovoltaic System

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/PVSC40753.2019.8981385

Cite this

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 (pp. 503-507). Article 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, pp. 503-507, 46th IEEE Photovoltaic Specialists Conference, PVSC 2019, Chicago, United States, 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. p. 503-507 8981385.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › 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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M3 - Conference contribution

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

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Y2 - 16 June 2019 through 21 June 2019

ER -

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

Abstract

Conference

Keywords

UN SDGs

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