• DocumentCode
    3399179
  • Title

    Data mining techniques application in power distribution utilities

  • Author

    Ramos, Sérgio ; Vale, Zita

  • Author_Institution
    Polytech. Inst. of Porto, Lisbon
  • fYear
    2008
  • fDate
    21-24 April 2008
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    This paper presents an electricity medium voltage (MV) consumer characterization framework supported on the data base knowledge discovery process (KDD). Data Mining (DM) techniques are used to discover a set of a MV consumer typical load profile and, therefore, to extract knowledge concerning to the electric energy consumption patterns. In order to form the different customers´ classes a hierarchical clustering algorithm is used. The framework includes several steps, starting from the pre-processing data, application of DM algorithms, classification model, and finally, the interpretation of the discovered knowledge. To validate the proposed framework, a case study which includes real databases of MV consumers is used.
  • Keywords
    data mining; power distribution economics; power system analysis computing; data base knowledge discovery process; data mining techniques; electric energy consumption; hierarchical clustering algorithm; medium voltage consumer; power distribution utilities; Classification algorithms; Clustering algorithms; Contracts; Data mining; Databases; Delta modulation; Electricity supply industry; Energy consumption; Medium voltage; Power distribution; Classification; clustering; data mining; electricity markets; load profiles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Transmission and Distribution Conference and Exposition, 2008. T&D. IEEE/PES
  • Conference_Location
    Chicago, IL
  • Print_ISBN
    978-1-4244-1903-6
  • Electronic_ISBN
    978-1-4244-1904-3
  • Type

    conf

  • DOI
    10.1109/TDC.2008.4517229
  • Filename
    4517229