• DocumentCode
    783575
  • Title

    Participatory Learning in Power Transformers Thermal Modeling

  • Author

    Hell, Michel ; Costa, Pyramo, Jr. ; Gomide, Fernando

  • Author_Institution
    Dept. of Comput. Eng. & Autom. (DCA), State Univ. of Campinas (UNICAMP), Campinas
  • Volume
    23
  • Issue
    4
  • fYear
    2008
  • Firstpage
    2058
  • Lastpage
    2067
  • Abstract
    In this paper, we introduce a new approach based on the participatory learning paradigm to train a class of hybrid neurofuzzy networks whose aim is to model the thermal behavior of power transformers. The participatory learning paradigm is a training procedure that tends to emulate the human learning mechanism. An acceptance mechanism determines which observation is used for learning based upon their compatibility with the current beliefs. The proposed model is compared with actual data obtained from an experimental power transformer equipped with fiber-optic probes. Comparisons with alternative approaches suggested in the literature are included to show the effectiveness of participatory learning to model the thermal behavior of power transformers.
  • Keywords
    fuzzy neural nets; learning (artificial intelligence); power engineering computing; power transformers; hybrid neurofuzzy networks; participatory learning paradigm; power transformers; thermal modeling; Nonlinear modeling; participatory learning; power transformers; thermal modeling;
  • fLanguage
    English
  • Journal_Title
    Power Delivery, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8977
  • Type

    jour

  • DOI
    10.1109/TPWRD.2008.923994
  • Filename
    4558847