• DocumentCode
    976374
  • Title

    Load pattern-based classification of electricity customers

  • Author

    Chicco, Gianfranco ; Napoli, Roberto ; Piglione, Federico ; Postolache, Petru ; Scutariu, Mircea ; Toader, Cornel

  • Author_Institution
    Dipt. di Ingegneria Elettrica Industriale, Politecnico di Torino, Italy
  • Volume
    19
  • Issue
    2
  • fYear
    2004
  • fDate
    5/1/2004 12:00:00 AM
  • Firstpage
    1232
  • Lastpage
    1239
  • Abstract
    Accurate knowledge of the customers´ consumption patterns represents a worthwhile asset for electricity providers in competitive electricity markets. Various approaches can be used for grouping customers that exhibit similar electrical behavior into customer classes. In this paper, we focus on two approaches for customer classification-a modified follow-the-leader algorithm and the self-organizing maps. We include an overview of basic theory for these methods and discuss the performance of the customer classification on the real case of a set of customers supplied by a distribution company. We compare the results obtained from the two approaches by means of two suitably defined adequacy indicators and discuss the potential applications of the surveyed approaches.
  • Keywords
    customer services; load distribution; power consumption; power distribution economics; power markets; self-organising feature maps; adequacy indicator; clustering algorithm; customer consumption pattern; distribution company; electricity customers; electricity market; electricity provider; load pattern; load pattern-based classification; self-organizing map; Classification algorithms; Costs; Data mining; Electricity supply industry; Energy consumption; Monitoring; Neural networks; Pattern analysis; Power engineering; Self organizing feature maps;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2004.826810
  • Filename
    1295037