• DocumentCode
    550599
  • Title

    Operating parameters optimization of thermal power unit based on data mining

  • Author

    Feng Chunhui ; Chen Yanqiao ; Liu Jinkun

  • Author_Institution
    Sch. of Autom. Sci. & Electr. Eng., BeiHang Univ., Beijing, China
  • fYear
    2011
  • fDate
    22-24 July 2011
  • Firstpage
    2119
  • Lastpage
    2123
  • Abstract
    Rationally fixing operation optimization target values of thermal power sets is the premise and foundation of effectuating performance evaluation and operation optimization, which is the key for the power station to save energy and reduce consumption. The paper proposes using data mining to find the optimization target value of controllable parameters. Based on the history data stored in supervisory information system of a 600WM unit, firstly, a clustering method is used to construct fuzzy sets for the steady-state operating data under specific operation condition. Then, fuzzy association rules mining algorithm is used to get the operating target values when the power consumption rate is relatively low. Thus the operation optimization curve can be obtained to guide the practical operation.
  • Keywords
    data mining; fuzzy set theory; information systems; optimisation; pattern clustering; power engineering computing; thermal power stations; clustering method; data mining; fuzzy association rules mining algorithm; fuzzy sets; operating parameters optimization; performance evaluation; power 600 MW; power station; supervisory information system; thermal power sets; thermal power unit; Association rules; Electronic mail; History; Information systems; Optimization; Thermal engineering; Clustering; Fuzzy Association Rules; Operating Optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2011 30th Chinese
  • Conference_Location
    Yantai
  • ISSN
    1934-1768
  • Print_ISBN
    978-1-4577-0677-6
  • Electronic_ISBN
    1934-1768
  • Type

    conf

  • Filename
    6000938