• DocumentCode
    2710043
  • Title

    Load characteristics clustering based on an improved FCM method

  • Author

    Wang, Jin ; Li, Xinran ; Li, Cailing

  • Author_Institution
    Coll. of Electr. & Inf. Eng., Univ. of Sci. & Technol., Changsha
  • fYear
    2008
  • fDate
    21-24 April 2008
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    It is well-known that load modeling is one of the most difficult problems in the power system of the world. It is necessary to carry out further research on the load characteristics analysis and the practical load model is constructed using clustering method to increase the precision and credibility of the power system simulation analysis. Since the output using traditional Hard C-Means (HCM) is sensitive to random selections about C initial cluster centers, this paper presents an improved Fuzzy C-Means (FCM) method on searching optimal initial cluster centers for the static load characteristics clustering of 36 220 KV substations in Hunan province power grid. The results verify the feasibility and validity of the improved FCM method for load clustering.
  • Keywords
    fuzzy set theory; power grids; power system simulation; substations; Hunan province; clustering method; fuzzy C-means method; load characteristics clustering; power grid; power system simulation analysis; substations; Clustering methods; Educational institutions; Load modeling; Measurement units; Power system analysis computing; Power system measurements; Power system modeling; Power system simulation; Shape measurement; Substations; clustering analysis; fuzzy sets; improved FCM method; load characteristics; load modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Technology, 2008. ICIT 2008. IEEE International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-1705-6
  • Electronic_ISBN
    978-1-4244-1706-3
  • Type

    conf

  • DOI
    10.1109/ICIT.2008.4608686
  • Filename
    4608686