• DocumentCode
    254827
  • Title

    Appliance signature: Multi-modes electric appliances

  • Author

    Kwok Tai Chui ; Faan Hei Hung ; Li, B.Y.S. ; Kim Fung Tsang ; Chung, H.S.-H.

  • Author_Institution
    Dept. of Electron. Eng., City Univ. of Hong Kong, Hong Kong, China
  • fYear
    2014
  • fDate
    9-13 April 2014
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    Smart grid has one of the top concerns in recent decade attributable to deteriorating environment. Appliance signatures possessed by electric appliances can be utilized for uniquely classifying between each others. In this paper, a neural network based appliance signature is presented. It presents the performance evaluation with and without separating the operation modes of electric appliance into distinct classes. Neural network has been utilized for the study. Results show that introducing multi-modes electric appliances into multi-class would not affect the performance of appliance signature.
  • Keywords
    neural nets; power apparatus; power engineering computing; smart power grids; multimode electric appliance signature; neural network; smart grid; Accuracy; Data models; Feature extraction; Home appliances; Neural networks; Performance evaluation; Smart grids; Appliance signature; Energy managemnet; Neural network; Smart grid; Smart metering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Consumer Electronics - China, 2014 IEEE International Conference on
  • Conference_Location
    Shenzhen
  • Type

    conf

  • DOI
    10.1109/ICCE-China.2014.7029896
  • Filename
    7029896