• DocumentCode
    134701
  • Title

    A knowledge-based fault diagnosis platform in smart grid: A conceptual design

  • Author

    Zhao Wang ; Feng Gao ; Xinjie Lv ; Wenjun Yin ; Jin Dong

  • Author_Institution
    IBM Res. - China, Beijing, China
  • fYear
    2014
  • fDate
    27-31 July 2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Ill-treated faults lead to power service interruptions for end customers, or even large scale outages, such as the case of 2003 North America blackout. In a smart grid environment, it is possible to detect and isolate faults in a timely manner. Fault detection and isolation (FDI) techniques based on measurement of traditional system states are well developed after decades of research efforts, mostly formulated as modules. In smart grids, more information sources are available, such as vision, acoustic, weather monitoring, and social media. A knowledge-based FDI platform is proposed to incorporate all these information sources and fault diagnosis modules. The proposed knowledge-based fault diagnosis architecture supplied well-reasoned results to support operator decision making, while expertise from operators help to improve its performance.
  • Keywords
    fault diagnosis; knowledge based systems; power engineering computing; power system faults; power system reliability; smart power grids; FDI technique; North America; blackout; conceptual design; fault detection and isolation technique; fault diagnosis module; information source; knowledge-based fault diagnosis platform; large scale outage; operator decision making; power service interruption; smart grid environment; Expert systems; Fault diagnosis; Sensors; Smart grids; Fault diagnosis; expert system; smart grid;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    PES General Meeting | Conference & Exposition, 2014 IEEE
  • Conference_Location
    National Harbor, MD
  • Type

    conf

  • DOI
    10.1109/PESGM.2014.6938834
  • Filename
    6938834