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

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