• DocumentCode
    2017916
  • Title

    Research and Application of Data Mining Technique in Power Plant

  • Author

    Li, Jian-qiang ; Wang, Song-Ling ; Niu, Cheng-Lin ; Liu, Ji-zhen

  • Author_Institution
    North China Electr. Power Univ., Beijing
  • Volume
    2
  • fYear
    2008
  • fDate
    17-18 Oct. 2008
  • Firstpage
    250
  • Lastpage
    253
  • Abstract
    As the development of electric industry, more and more real-time data is sent to databases by data acquisition system and large amounts of data are accumulated. Abundant knowledge exists in those historical data. It is meaning to analyze those historical data in electric industry and find useful knowledge and rules from the mass of data to provide better decision support and better adjustment guidance. The concept and steps of data mining is introduced in particular. Based on the characteristic of electric data, the data mining technique is introduced into the electric industry and the feasibility and necessity are discussed. The application of data mining in electric power industrial is discussed. The fault diagnosis and operation optimization based on data mining is researched in detail. The application of data mining in electric industry can guide the optimal operation based on historical data and improve the economic efficient in power plant.
  • Keywords
    data acquisition; data mining; electricity supply industry; power plants; power system analysis computing; power system economics; data acquisition system; data mining technique; electric industry; electric power industrial; fault diagnosis; operation optimization; power plant; Data acquisition; Data analysis; Data mining; Databases; Fault diagnosis; Industrial economics; Mining industry; Power generation; Power generation economics; Real time systems; Data mining; electric power industry; fault diagnosis; operation optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Design, 2008. ISCID '08. International Symposium on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3311-7
  • Type

    conf

  • DOI
    10.1109/ISCID.2008.191
  • Filename
    4725501