光伏阵列故障检测方法综述

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Abstract The fault diagnosis method based on condition monitoring is an effective way to improve the reliability and safety of photovoltaic systems. The output of the photovoltaic array has non-linear characteristics and is easily affected by external environmental interference. These reasons make it difficult for traditional protection devices to detect its DC side faults. The failure of the photovoltaic array will not only reduce the power generation and damage the photovoltaic modules, but also cause large-scale fires in severe cases. In order to deal with this problem, the methods of photovoltaic array fault detection are constantly being proposed by experts and scholars. This research summarizes the common fault detection methods. In this paper, the common fault types and characteristics of photovoltaic arrays are introduced, and the advantages and disadvantages of common detection methods are summarized at the end.

Key words： photovoltaic array fault diagnosis photovoltaic module status detection

Received: 08 October 2020

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	Articles by authors
	IAO Supeng
	YANG Yan
	CHEN Shiqun
	GAO Wei
	YANG Gengjie

Cite this article:

IAO Supeng,YANG Yan,CHEN Shiqun等. Review on photovoltaic array diagnosis methods[J]. Electrical Engineering, 2021, 22(7): 1-6.

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http://dqjs.cesmedia.cn/EN/Y2021/V22/I7/1

[1] 韩付昌, 陈志聪, 吴丽君, 等. 一种光伏阵列实时状态监测与故障定位系统[J]. 福州大学学报(自然科学版), 2018, 46(6): 799-807.
[2] 王尧, 张彦风, 牛峰, 等. 光伏直流电弧电磁辐射特性分析与测量方法[J]. 电工技术学报, 2019, 34(14): 2913-2921.
[3] PILLAI D S, NATARAJAN R.A compatibility analysis on NEC, IEC, and UL standards for protection against line-line and line-ground faults in PV arrays[J]. IEEE Journal of Photovoltaics, 2019, 9(3): 864-871.
[4] ZHAO Ye, DE PALMA J F, MOSESIAN J, et al. Line-line fault analysis and protection challenges in solar photovoltaic arrays[J]. IEEE Transactions on Industrial Electronics, 2013, 60(9): 3784-3795.
[5] 彭雅兰, 李志刚. 太阳能光伏阵列在线故障诊断方法综述[J]. 电器与能效管理技术, 2019(11): 1-7.
[6] PILLAI D S, BLAABJERG F, RAJASEKAR N.A comparative evaluation of advanced fault detection approaches for PV systems[J]. IEEE Journal of Photo-voltaics, 2019, 9(2): 513-527.
[7] 毛峡, 李亚豪. 光伏阵列故障检测中的无人机红外图像拼接[J]. 太阳能学报, 2020, 41(3): 262-269.
[8] CUBUKCU M, AKANALCI A.Real-time inspection and determination methods of faults on photovoltaic power systems by thermal imaging in Turkey[J]. Renewable Energy, 2020, 147: 1231-1238.
[9] KAPLANI E.Detection of degradation effects in field-aged c-Si solar cells through IR thermography and digital image processing[J]. International Journal of Photoenergy, 2012, 2012: 1-11.
[10] BENATTO G A D R, MANTEL C, SPATARU S, et al. Drone-based daylight electroluminescence imaging of PV modules[J]. IEEE Journal of Photovoltaics, 2020, 10(3): 872-877.
[11] BREITENSTEIN O, BAUER J, TRUPKE T, et al.On the detection of shunts in silicon solar cells by photo and electroluminescence imaging[J]. Progress in Photovoltaics: Research and Applications, 2008, 16(4): 325-330.
[12] HAUNSCHILD J, REIS I E, GEILKER J, et al.Detecting efficiency-limiting defects in Czochralski-grown silicon wafers in solar cell production using photoluminescence imaging[J]. Physica Status Solidi-Rapid Research Letters, 2011, 5: 199-201.
[13] CHAKRAPANI S K, PADIYAR M J, BALASUBRAMANIAM K.Crack detection in full size CZ-silicon wafers using lamb wave air coupled ultrasonic testing (LAC-UT)[J]. Journal of Nondestructive Evaluation, 2012, 31(1): 46-55.
[14] 孟佳彬, 李智华, 吴春华, 等. 基于SSTDR的光伏系统对地故障检测方法[J]. 太阳能学报, 2020, 41(10): 109-118.
[15] HARROU F, TAGHEZOUIT B, SUN Ying.Improved KNN-based monitoring schemes for detecting faults in PV systems[J]. IEEE Journal of Photovoltaics, 2019, 9(3): 811-821.
[16] DHIMISH M, HOLMES V, MEHRDADI B, et al.Simultaneous fault detection algorithm for grid-connected photovoltaic plants[J]. IET Renewable Power Generation, 2017, 11(12): 1565-1575.
[17] HARIHARAN R, CHAKKARAPANI M, SARAVANA ILANGO G, et al.A method to detect photovoltaic array faults and partial shading in PV systems[J]. IEEE Journal of Photovoltaics, 2016, 6(5): 1278-1285.
[18] DHIMISH M, HOLMES V, MEHRDADI B, et al.Photovoltaic fault detection algorithm based on theoretical curves modelling and fuzzy classification system[J]. Energy, 2017, 140: 276-290.
[19] CHOUDER A, SILVESTRE S.Automatic supervision and fault detection of PV systems based on power losses analysis[J]. Energy Conversion and Management, 2010, 51(10): 1929-1937.
[20] DAVARIFAR M, RABHI A, EL-HAJJAJI A, et al.Real-time model base fault diagnosis of PV panels using statistical signal processing[C]//2013 Inter-national Conference on Renewable Energy Research and Applications (ICRERA), 2013: 599-604.
[21] 张明锐, 陈喆旸, 韦莉. 免疫萤火虫算法在光伏阵列最大功率点跟踪中的应用[J]. 电工技术学报, 2020, 35(7): 1553-1562.
[22] HUANG Junming, WAI Rongjong, GAO Wei.Newly-designed fault diagnostic method for solar photovoltaic generation system based on IV-curve measurement[J]. IEEE Access, 2019, 7: 70919-70932.
[23] CHEN Zhicong, CHEN Yixiang, WU Lijun, et al.Deep residual network based fault detection and diagnosis of photovoltaic arrays using current-voltage curves and ambient conditions[J]. Energy Conversion and Management, 2019, 198: 111793.
[24] 甘雨涛, 吴振辉, 陈志聪, 等. 基于LoRa和自适应神经网络模糊推理系统的光伏阵列故障诊断系统[J]. 电气技术, 2020, 21(8): 80-86.
[25] SPATARU S, SERA D, KEREKES T, et al.Diagnostic method for photovoltaic systems based on light I-V measurements[J]. Solar Energy, 2015, 119: 29-44.
[26] 王元章, 吴春华, 周笛青, 等. 基于BP神经网络的光伏阵列故障诊断研究[J]. 电力系统保护与控制, 2013, 41(16): 108-114.
[27] 蔡雨桥, 林培杰, 林耀海, 等. 基于动态时间规整的光伏阵列在线故障检测方法[J]. 电气技术, 2020, 21(7): 42-47.
[28] 杨佳葳, 闫正兵, 李剑锋, 等. 基于序差和的光伏阵列故障分类方法[J]. 控制工程, 2020, 27(8): 1425-1428.
[29] 李光辉, 段晨东, 武珊. 基于半监督机器学习法的光伏阵列故障诊断[J]. 电网技术, 2020, 44(5): 1908-1913.
[30] KUMAR B P, ILANGO G S, REDDY M J B, et al. Online fault detection and diagnosis in photovoltaic systems using wavelet packets[J]. IEEE Journal of Photovoltaics, 2018, 8(1): 257-265.
[31] YI Z, ETEMADI A H.Line-to-line fault detection for photovoltaic arrays based on multi-resolution signal decomposition and two-stage support vector machine[J]. IEEE Transactions on Industrial Electronics, 2017, 64(11): 8546-8556.
[32] YI Zhehan, ETEMADI A H.Fault detection for photovoltaic systems based on multi-resolution signal decomposition and fuzzy inference systems[J]. IEEE Transactions on Smart Grid, 2017, 8(3): 1274-1283.