• DocumentCode
    3498266
  • Title

    Embedded power quality monitoring system based on Independent Component Analysis and SVMs

  • Author

    Ruiz-Llata, Marta ; Guarnizo, Guillermo ; Boya, Carlos

  • Author_Institution
    Dept. of Electron. Technol., Univ. Carlos III de Madrid, Leganés, Spain
  • fYear
    2011
  • fDate
    July 31 2011-Aug. 5 2011
  • Firstpage
    2229
  • Lastpage
    2234
  • Abstract
    On-line identification and classification of voltage and current disturbances in power systems are important tasks in the power quality monitoring and protection of power systems. Some power quality disturbances are non-stationary and transitory while other are steady-state variations that distort the voltage signal. One, two or more different power quality disturbances may appear at the same time. In this paper we propose a power quality monitoring system that employs Independent Component Analysis algorithm that is able to decouple multiple simultaneous power quality disturbances, and Support Vector Machines for identification the occurrence of a disturbance. We also show the first steps towards embedding the proposed system on an FPGA for online power quality monitoring.
  • Keywords
    field programmable gate arrays; independent component analysis; power engineering computing; power supply quality; power system faults; power system identification; power system measurement; power system protection; support vector machines; SVM; current disturbance; embedded power quality monitoring system; independent component analysis algorithm; power quality disturbance; power system protection; support vector machine; voltage disturbance; voltage signal distortion; Harmonic analysis; Kernel; Monitoring; Power harmonic filters; Power quality; Support vector machines; Transient analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2011 International Joint Conference on
  • Conference_Location
    San Jose, CA
  • ISSN
    2161-4393
  • Print_ISBN
    978-1-4244-9635-8
  • Type

    conf

  • DOI
    10.1109/IJCNN.2011.6033506
  • Filename
    6033506