• DocumentCode
    134046
  • Title

    Literature review on the applications of data mining in power systems

  • Author

    Kazerooni, M. ; Hao Zhu ; Overbye, Thomas J.

  • Author_Institution
    Dept. of ECE, Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
  • fYear
    2014
  • fDate
    Feb. 28 2014-March 1 2014
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Power system is a highly interconnected network which delivers electric power to the electricity users. Sustaining the secure and reliable delivery of electric power requires continuous monitoring of the system. To process the large volumes of data obtained from the measuring devices, it is essential to investigate effective data enhancement techniques. In this paper, a comprehensive study on the applications of data mining in power systems is presented. Data visualization, clustering, outliers detection and classification are investigated as four major areas of data mining and related works in power systems which utilize each of these methods are presented in an organized and structured fashion.
  • Keywords
    computerised monitoring; data mining; data visualisation; electric power generation; power consumption; power system interconnection; continuous monitoring; data clustering; data enhancement techniques; data mining; data visualization; electric power; electricity users; interconnected network; outliers detection; power systems; Data mining; Data visualization; Layout; Power cables; Power system stability; Substations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Conference at Illinois (PECI), 2014
  • Conference_Location
    Champaign, IL
  • Type

    conf

  • DOI
    10.1109/PECI.2014.6804567
  • Filename
    6804567