• DocumentCode
    3150621
  • Title

    Signal processing for fault detection in photovoltaic arrays

  • Author

    Braun, H. ; Buddha, S.T. ; Krishnan, V. ; Spanias, A. ; Tepedelenlioglu, C. ; Yeider, T. ; Takehara, T.

  • Author_Institution
    Sch. of ECEE, Arizona State Univ., Tempe, AZ, USA
  • fYear
    2012
  • fDate
    25-30 March 2012
  • Firstpage
    1681
  • Lastpage
    1684
  • Abstract
    Photovoltaics (PV) is an important and rapidly growing area of research. With the advent of power system monitoring and communication technology collectively known as the “smart grid,” an opportunity exists to apply signal processing techniques to monitoring and control of PV arrays. In this paper a monitoring system which provides real-time measurements of each PV module´s voltage and current is considered. A fault detection algorithm formulated as a clustering problem and addressed using the robust minimum covariance determinant (MCD) estimator is described; its performance on simulated instances of arc and ground faults is evaluated. The algorithm is found to perform well on many types of faults commonly occurring in PV arrays.
  • Keywords
    covariance analysis; fault diagnosis; photovoltaic power systems; power system control; signal processing; smart power grids; MCD estimator; PV array control; PV array monitoring; PV module current; PV module voltage; clustering problem; communication technology; fault detection algorithm; monitoring system; photovoltaic arrays; photovoltaics; power system monitoring; real-time measurements; robust minimum covariance determinant estimator; signal processing techniques; smart grid; Array signal processing; Arrays; Circuit faults; Fault detection; Monitoring; Photovoltaic systems; Electrical Fault Detection; Photovoltaic Systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
  • Conference_Location
    Kyoto
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4673-0045-2
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2012.6288220
  • Filename
    6288220