• DocumentCode
    3404992
  • Title

    Locality sensitive hashing of customer load profiles

  • Author

    Beretka, Sandor F. ; Varga, Ervin D.

  • Author_Institution
    Fac. of Tech. Sci., Univ. of Novi Sad, Novi Sad, Serbia
  • fYear
    2013
  • fDate
    20-23 Oct. 2013
  • Firstpage
    353
  • Lastpage
    356
  • Abstract
    Precise determination of load profiles is a key process in optimal control of power distribution systems. The emerging need for electricity, the penetration of distributed local generation and the rising power quality requirements imposes more advanced algorithms to be used. In this paper locality sensitive hashing is presented, which uses feature sets extracted from load data by autoencoders.
  • Keywords
    customer profiles; load distribution; power distribution planning; power distribution reliability; power engineering computing; customer load profiles; distributed local generation; load data; locality sensitive hashing; power distribution systems; power quality; Feature extraction; Home appliances; Load modeling; Neural networks; Neurons; Training; Water heating; autoencoder; feature set; load profile; locality sensitive hashing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Renewable Energy Research and Applications (ICRERA), 2013 International Conference on
  • Conference_Location
    Madrid
  • Type

    conf

  • DOI
    10.1109/ICRERA.2013.6749779
  • Filename
    6749779