• DocumentCode
    581401
  • Title

    Smart meter systems detection & classification using artificial neural networks

  • Author

    Bier, Thomas ; Abdeslam, Djaffar Quid ; Merckle, Jean ; Benyoucef, Dirk

  • Author_Institution
    Univ. Furtwangen, Furtwangen, Germany
  • fYear
    2012
  • fDate
    25-28 Oct. 2012
  • Firstpage
    3324
  • Lastpage
    3329
  • Abstract
    The goal of that paper is to show a possibility for the disaggregation of electrical appliances in the power profile of residential buildings. The advantage is that the measurement system is at a central point in the household. So the installation effort decrease. For the disaggregation of the appliances out of the load curve, an approach for the development of a system based on pattern recognition is presented. One method for the classification of appliances is to use Artificial Neural Network. This idea is the main part of that paper. It is shown a method, to classify one kind of appliances. At the end, the first results and a comparison with the famous approach, for the disaggregation of electrical appliances, from Hart is presented.
  • Keywords
    building management systems; domestic appliances; electrical products; intelligent sensors; neural nets; pattern recognition; power engineering computing; smart meters; artificial neural network; electrical appliance; load curve; pattern recognition; residential building; smart classification system; smart detection system; smart meter system; Artificial neural networks; Manuals; Monitoring; Refrigerators; Switches; Weight measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society
  • Conference_Location
    Montreal, QC
  • ISSN
    1553-572X
  • Print_ISBN
    978-1-4673-2419-9
  • Electronic_ISBN
    1553-572X
  • Type

    conf

  • DOI
    10.1109/IECON.2012.6389365
  • Filename
    6389365