• DocumentCode
    3105411
  • Title

    Automated recognition of irregularities in substation load profiles due to abnormal feeding arrangements

  • Author

    Leaman, A.J. ; Nouri, H. ; Polycarpou, A. ; der Linde, F.V. ; Ciric, R.M.

  • Author_Institution
    UWE Bristol, Bristol, UK
  • fYear
    2008
  • fDate
    1-4 Sept. 2008
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Detection of abnormal feeding through the concept of data mining is studied. The presented results are in the form of case studies for various abnormalities. The developed detection algorithm is based on feeding patterns that compare the load profile against a reference waveform in conjunction with a threshold to denote abnormality.
  • Keywords
    data mining; power engineering computing; substation automation; abnormal feeding arrangements; data mining; feeding patterns; irregularities automated recognition; substation load profiles; Circuit breakers; Circuit faults; Costs; Data mining; Frequency; Power demand; Power generation; Substations; Transformers; Weather forecasting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Universities Power Engineering Conference, 2008. UPEC 2008. 43rd International
  • Conference_Location
    Padova
  • Print_ISBN
    978-1-4244-3294-3
  • Electronic_ISBN
    978-88-89884-09-6
  • Type

    conf

  • DOI
    10.1109/UPEC.2008.4651542
  • Filename
    4651542