• DocumentCode
    578376
  • Title

    FRS-based decision table reduction for the operation optimization of large coal-fired power units

  • Author

    Ang, Ning-ling W. ; Chen, De-gang ; Yang, Yong-ping ; Zhang, Ting

  • Author_Institution
    Key Lab. of Condition Monitoring & Control for Power Plant Equip., North China Electr. Power Univ., Beijing, China
  • Volume
    3
  • fYear
    2012
  • fDate
    15-17 July 2012
  • Firstpage
    1007
  • Lastpage
    1013
  • Abstract
    Large coal-fired power unit is a complex nonlinear system with more uncertainties to describe, evaluate and optimize. It is essential and difficult to determine the optimal targets in operation optimization of power units, especially considering the boundary constraints, operation conditions and system features. Fuzzy rough set (FRS)-based decision table reduction was introduced to clean the historian operation data efficiently without information losses. The result shows that the derived energy consumption decision rules can be used to determine the optimal targets quickly and dynamically for different boundary and operation conditions. It makes significant reference and promising prospects in energy-consumption diagnosis and operation optimization of power units.
  • Keywords
    decision tables; fuzzy set theory; optimisation; rough set theory; steam power stations; FRS-based decision table reduction; boundary constraints; complex nonlinear system; energy consumption decision rules; energy-consumption diagnosis; fuzzy rough set-based decision table reduction; historian operation data; information losses; large coal-fired power units; operation optimization; optimal targets; power unit operation optimization; system features; Abstracts; Approximation methods; Training; Decision table reduction; Energy-consumption decision rule; FRS; Large coal-fired power units; Operation optimization; Optimal target;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2012 International Conference on
  • Conference_Location
    Xian
  • ISSN
    2160-133X
  • Print_ISBN
    978-1-4673-1484-8
  • Type

    conf

  • DOI
    10.1109/ICMLC.2012.6359492
  • Filename
    6359492