• DocumentCode
    3105105
  • Title

    Electricity load profile classification using Fuzzy C-Means method

  • Author

    Prahastono, Iswan ; King, David J. ; Ozveren, C.S. ; Bradley, D.

  • Author_Institution
    PT. PLN Indonesia, Univ. of Abertay, Dundee
  • fYear
    2008
  • fDate
    1-4 Sept. 2008
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper presents the Fuzzy C-Means (FCM) clustering method. The FCM technique assigns a degree of membership for each data set to several clusters, thus offering the opportunity to deal with load profiles that could belong to more than one group at the same time. The FCM algorithm is based on minimising a c-means objective function to determine an optimal classification. The simulation of FCM was carried out using actual sample data from Indonesia and the results are presented. Some validity index measurements was carried out to estimate the compactness of the resulting clusters or to find the optimal number of clusters for a data set.
  • Keywords
    fuzzy set theory; load forecasting; pattern clustering; Indonesia; data set clusters; electricity load profile classification; fuzzy c-means clustering method; Business; Clustering algorithms; Clustering methods; Databases; Euclidean distance; Flowcharts; Government;
  • 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.2008.4651527
  • Filename
    4651527