Detection and Classification of Faults in Solar PV Array Using Thevenin Equivalent Resistance

被引:40
|
作者
Karmakar, Binoy Kumar [1 ]
Pradhan, Ashok Kumar [1 ]
机构
[1] Indian Inst Technol Kharagpur, Dept Elect Engn, Kharagpur 721302, W Bengal, India
来源
IEEE JOURNAL OF PHOTOVOLTAICS | 2020年 / 10卷 / 02期
关键词
Fault; fault classification; partial shading; photovoltaic (PV) array; Thevenin's equivalent; PHOTOVOLTAIC SYSTEMS;
D O I
10.1109/JPHOTOV.2019.2959951
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
Detecting fault in a solar photovoltaic (PV) array in the presence of protection diodes (bypass and reverse blocking) is complex. This is because variations in the electrical parameters (due to a fault) are often not distinguishable from one type of fault to another or from fault to partial shading. Depending on the fault condition, an open fault may appear like a short-circuit fault and a severe partial shading occasionally may be detected as a short-circuit fault. Identifying a short-circuit fault and separating it from an open fault or partial shading are important as the former demands immediate attention to avoid damage to the PV modules and fire hazard. It is observed that the available techniques, based on transient changes in array parameters and model comparison, cannot identify faults under all practical scenarios. In this article, a fault detection and classification technique using array voltage, current, irradiance, and temperature measurements is proposed. The technique computes Thevenin equivalent resistance of the PV array for accurate fault identification. The simulation results demonstrate that the proposed technique can detect and classify faults correctly and differentiate them from partial shading. The comparative results show its superior performance compared with available techniques. The proposed technique is also validated by the results of hardware experiments.
引用
收藏
页码:644 / 654
页数:11
相关论文
共 50 条
  • [21] Classification and Early Detection of Solar Panel Faults with Deep Neural Network Using Aerial and Electroluminescence Images
    Jaybhaye, Sangita
    Sirvi, Vishal
    Srivastava, Shreyansh
    Loya, Vaishnav
    Gujarathi, Varun
    Jaybhaye, M. D.
    JOURNAL OF FAILURE ANALYSIS AND PREVENTION, 2024, 24 (04) : 1746 - 1758
  • [22] Binary Classification of Defective Solar PV Modules Using Thermography
    Niazi, K.
    Akhtar, W.
    Khan, H. A.
    Sohaib, S.
    Nasir, A. K.
    2018 IEEE 7TH WORLD CONFERENCE ON PHOTOVOLTAIC ENERGY CONVERSION (WCPEC) (A JOINT CONFERENCE OF 45TH IEEE PVSC, 28TH PVSEC & 34TH EU PVSEC), 2018, : 0753 - 0757
  • [23] Fault Detection and Classification Scheme for PV System Using Array Power and Cross-Strings Differential Currents
    Aboshady, F. M.
    Taha, Ibrahim B. M.
    IEEE ACCESS, 2021, 9 : 112655 - 112669
  • [24] PV Array Fault Detection using Radial Basis Networks
    Pedersen, Emma
    Rao, Sunil
    Katoch, Sameeksha
    Jaskie, Kristen
    Spanias, Andreas
    Tepedelenlioglu, Cihan
    Kyriakides, Elias
    2019 10TH INTERNATIONAL CONFERENCE ON INFORMATION, INTELLIGENCE, SYSTEMS AND APPLICATIONS (IISA), 2019, : 306 - 309
  • [25] An effective method for detection and location estimation of faults in large-scale solar PV arrays
    Kumar, Shubham
    Nayak, Paresh Kumar
    SOLAR ENERGY, 2024, 277
  • [26] Sensor Faults Detection and Classification using SVM with Diverse Features
    Jan, Sana Ullah
    Koo, In Soo
    2017 INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY CONVERGENCE (ICTC), 2017, : 576 - 578
  • [27] Photovoltaic array fault detection based on a new model of series equivalent resistance
    Pei, Tingting
    Wang, Hao
    Chen, Wei
    Wang, Shuo
    Pan, Duoyi
    PHYSICA SCRIPTA, 2024, 99 (09)
  • [28] Detection and classification of intrusions and faults using sequences of system calls
    Cabrera, JBD
    Lewis, L
    Mehra, RK
    SIGMOD RECORD, 2001, 30 (04) : 25 - 34
  • [29] Detection, Classification and Localization of Faults in LVDC Microgrid Using ANN
    Bhalla, Anu
    Bhalja, Bhavesh R.
    Purwar, Ekta
    Sosic, Darko
    Stojanovic, Zoran
    2023 IEEE BELGRADE POWERTECH, 2023,
  • [30] Detection and Classification of Photovoltaic System Faults using Neural Network
    Moulay, Aicha
    Benslimane, Tarak
    Abdelkhalek, Othmane
    Koussa, Khaled
    PRZEGLAD ELEKTROTECHNICZNY, 2023, 99 (11): : 157 - 162