• DocumentCode
    3262223
  • Title

    Identification and feature selection of non-technical losses for industrial consumers using the software WEKA

  • Author

    Ramos, C.C.O. ; de Souza, Andre N. ; Gastaldello, Danilo S. ; Papa, Joao Paulo

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Sao Paulo - USP, Sao Paulo, Brazil
  • fYear
    2012
  • fDate
    5-7 Nov. 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This work has as objectives the implementation of a intelligent computational tool to identify the non-technical losses and to select its most relevant features, considering information from the database with industrial consumers profiles of a power company. The solution to this problem is not trivial and not of regional character, the minimization of non-technical loss represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. This work presents using the WEKA software to the proposed objective, comparing various classification techniques and optimization through intelligent algorithms, this way, can be possible to automate applications on Smart Grids.
  • Keywords
    maintenance engineering; optimisation; power engineering computing; power systems; smart power grids; WEKA software; feature selection; industrial consumers; industrial consumers profiles; intelligent algorithms; intelligent computational tool; nontechnical losses; optimization; power company; power systems maintenance; product quality; smart grids; Artificial neural networks; Lead;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industry Applications (INDUSCON), 2012 10th IEEE/IAS International Conference on
  • Conference_Location
    Fortaleza
  • Print_ISBN
    978-1-4673-2412-0
  • Type

    conf

  • DOI
    10.1109/INDUSCON.2012.6451485
  • Filename
    6451485