Fault Detection and Diagnosis for Photovoltaic Array Under Grid Connected Using Support Vector Machine

被引:0
|
作者
Badr, Mohamed M. [1 ]
Hamad, Mostafa S. [2 ]
Abdel-Khalik, Ayman S. [1 ]
Hamdy, Ragi A. [1 ]
机构
[1] Alexandria Univ, Dept Elect & Control Engn, Fac Engn, Alexandria, Egypt
[2] Arab Acad Sci Technol & Maritime Transport, Coll Engn & Technol, Alexandria, Egypt
关键词
Photovoltaic (PV) system; PV array fault; fault detection and diagnosis; FDD; SVM; VSI; FLC; MPPT;
D O I
10.1109/cpere45374.2019.8980103
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Abnormal conditions in a solar photovoltaic (PV) array whether permanent or temporary faults lead to lessening the overall PV system efficiency and might lead to a fire hazard. As a result, it is compulsory to detect and diagnose faults in the PV array in order to ameliorate system reliability, safety, and efficiency. This paper proposes an automatic Fault Detection and Diagnosis (FDD) for the PV array under a grid-connected PV system operation based on the Support Vector Machine (SVM). The PV system utilizes two power processing stages consist of a DC-DC boost converter, followed by the three-phase, two-level, Voltage Source Inverter (VSI). The DC-DC boost converter is used to draw out the maximum PV array power and boosting the PV array output voltage. The Fuzzy Logic Control (FLC) based on the Maximum Power Point Tracking (MPPT) is applied to fine-tune the duty cycle for the DC-DC boost converter to realize maximum power. The VSI is used to inject a sinusoidal current into the grid through the LCL filter. The control strategy of the VSI consists of two control loops, the DC-link voltage and the AC-current control loop. The proposed system is simulated using MATLAB/Simulink (R) to investigate system performance.
引用
收藏
页码:546 / 553
页数:8
相关论文
共 50 条
  • [41] Fault diagnosis of gearboxes using wavelet support vector machine, least square support vector machine and wavelet packet transform
    Heidari, Mohammad
    Homaei, Hadi
    Golestanian, Hossein
    Heidari, Ali
    JOURNAL OF VIBROENGINEERING, 2016, 18 (02) : 860 - 875
  • [42] Fault Detection and Diagnosis in Process Data Using Support Vector Machines
    Wu, Fang
    Yin, Shen
    Karimi, Hamid Reza
    JOURNAL OF APPLIED MATHEMATICS, 2014,
  • [43] Support Vector Machine-Based Islanding and Grid Fault Detection in Active Distribution Networks
    Baghaee, Hamid Reza
    Mlakic, Dragan
    Nikolovski, Srete
    Dragicevic, Tomislav
    IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS, 2020, 8 (03) : 2385 - 2403
  • [44] Fault Diagnosis of Control Moment Gyroscope Using Optimized Support Vector Machine
    Farahani, Hossein Varvani
    Rahimi, Afshin
    2020 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2020, : 3111 - 3116
  • [46] Condition Monitoring and Fault Diagnosis of Induction Motor Using Support Vector Machine
    Patel, Rakesh A.
    Bhalja, Bhavesh R.
    ELECTRIC POWER COMPONENTS AND SYSTEMS, 2016, 44 (06) : 683 - 692
  • [47] Multiple Fault Diagnosis in Distillation Column Using Multikernel Support Vector Machine
    Taqvi, Syed A.
    Tufa, Lemma Dendena
    Zabiri, Haslinda
    Maulud, Abdulhalim Shah
    Uddin, Fahim
    INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2018, 57 (43) : 14689 - 14706
  • [48] Hybrid Random Forest and Support Vector Machine Modeling for HVAC Fault Detection and Diagnosis
    Tun, Wunna
    Wong, Johnny Kwok-Wai
    Ling, Sai-Ho
    SENSORS, 2021, 21 (24)
  • [49] Machine learning based islanding detection for grid connected photovoltaic system
    Khan, Mohammed Ali
    Haque, Ahteshamul
    Varaha Satya Bharath, Kurukuru
    2019 INTERNATIONAL CONFERENCE ON POWER ELECTRONICS, CONTROL AND AUTOMATION (ICPECA-2019), 2019, : 231 - 236
  • [50] Fault diagnosis of rotating machine by thermography method on support vector machine
    Gang-Min Lim
    Dong-Myung Bae
    Joo-Hyung Kim
    Journal of Mechanical Science and Technology, 2014, 28 : 2947 - 2952