• DocumentCode
    892850
  • Title

    Enhancement of anomalous data mining in power system predicting-aided state estimation

  • Author

    Huang, Shyh-Jier ; Lin, Jeu-Min

  • Author_Institution
    Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
  • Volume
    19
  • Issue
    1
  • fYear
    2004
  • Firstpage
    610
  • Lastpage
    619
  • Abstract
    An approach for predicting-aided state estimation including bad data mining in a power system is proposed in this paper. In the method, the sliding surface-enhanced fuzzy control and optimal cluster numbers estimation techniques are both employed for the enhancement of state estimation. This proposed approach has been applied to test systems. Test results reveal the feasibility of the method for the applications considered.
  • Keywords
    data mining; fuzzy control; power system control; power system state estimation; anomalous data mining; optimal cluster number estimation techniques; power system predicting-aided state estimation; sliding surface-enhanced fuzzy control; Data mining; Economic forecasting; Filtering; Fuzzy control; Load management; Neural networks; Power system dynamics; Power system modeling; Power systems; State estimation;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2003.818726
  • Filename
    1266620
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=892850