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

被引：0

作者：

Eskandari, Aref ^{[1
]}

Milimonfared, Jafar ^{[1
]}

Aghaei, Mohammadreza ^{[2
]}

Vidal de Oliveira, Aline Kirsten ^{[3
]}

Ruether, Ricardo ^{[3
]}

机构：

[1] Amirkabir Univ Technol, Tehran 158754413, Iran

[2] Albert Ludwigs Univ Freiburg, D-79110 Freiburg, Germany

[3] Univ Fed Santa Catarina, BR-88040900 Florianopolis, SC, Brazil

来源：

2019 IEEE 46TH PHOTOVOLTAIC SPECIALISTS CONFERENCE (PVSC) | 2019年

关键词：

Fault Detection; Machine Learning Algorithm; Photovoltaic System; Line-Line Fault; Pattern Recognition; MULTIRESOLUTION SIGNAL DECOMPOSITION; DIAGNOSIS; SYSTEMS;

D O I：

10.1109/pvsc40753.2019.8981385

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

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 non-linear 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.

引用

页码：503 / 507

页数：5

共 50 条

[21] Design of a Portable Photovoltaic I-V Curve Tracer Based on the DC-DC Converter Method
Pereira, Thiago A.
Schmitz, Lenon
dos Santos, Walbermark M.
Martins, Denizar C.
Coelho, Roberto F.
IEEE JOURNAL OF PHOTOVOLTAICS, 2021, 11 (02): : 552 - 560
[22] A Wireless Self-Powered I-V Curve Tracer for On-Line Characterization of Individual PV Panels
De Riso, Monica
Matacena, Ilaria
Guerriero, Pierluigi
Daliento, Santolo
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2024, 71 (09) : 11508 - 11518
[23] A new offline method for extracting I-V characteristic curve for photovoltaic modules using artificial neural networks
Khatib, Tamer
Ghareeb, Ahmed
Tamimi, Maan
Jaber, Mahmoud
Jaradat, Saif
SOLAR ENERGY, 2018, 173 : 462 - 469
[24] An Improved Method for Extracting Photovoltaic Module I-V Characteristic Curve Using Hybrid Learning Machine System
Khatib, Tamer
Direya, Rezeq
Said, Asmaa
JOURNAL OF SOLAR ENERGY ENGINEERING-TRANSACTIONS OF THE ASME, 2021, 143 (05):
[25] A New Application of Duty Cycle Sweep Based on Microcontroller to Obtain the I-V Characteristic Curve of Photovoltaic Modules
Duran, E.
Galan, J.
Sidrach-de-Cardona, M.
Ferrera, M. B.
Andujar, J. M.
2008 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY, VOLS 1-5, 2008, : 2032 - +
[26] Yield Prediction of Photovoltaic Power Station Based on the Data of Real-Time I-V Curve Measurement
Xing, Chaolu
Zhang, Bo
Cong, Weilun
Dai, Xiaolin
2016 IEEE INTERNATIONAL CONFERENCE ON POWER AND RENEWABLE ENERGY (ICPRE), 2016, : 602 - 605
[27] A data-driven photovoltaic string current mismatch fault diagnosis method based on I-V curve
Zhang, Zhixiang
Ma, Mingyao
Ma, Wenting
Zhang, Rui
Wang, Jun
MICROELECTRONICS RELIABILITY, 2022, 138
[28] Intelligent fault diagnosis of photovoltaic arrays based on optimized kernel extreme learning machine and I-V characteristics
Chen, Zhicong
Wu, Lijun
Cheng, Shuying
Lin, Peijie
Wu, Yue
Lin, Wencheng
APPLIED ENERGY, 2017, 204 : 912 - 931
[29] Design of a Portable Low-Cost I-V Curve Tracer for On-Line and In Situ Inspection of PV Modules
De Riso, Monica
Dhimish, Mahmoud
Guerriero, Pierluigi
Daliento, Santolo
MICROMACHINES, 2024, 15 (07)
[30] Method for the diagnostic evaluation of thin-film solar modules based on I-V measurement using a line light source
Yanagisawa, T
Kojima, T
SOLAR ENERGY MATERIALS AND SOLAR CELLS, 2005, 85 (02) : 285 - 291

← 1 2 3 4 5 →