• DocumentCode
    1572246
  • Title

    A novel technique to identify inrush current based on adaptive neuro fuzzy

  • Author

    Esmaeilian, A. ; Mohseninezhad, M. ; Khanabadi, M. ; Doostizadeh, M.

  • Author_Institution
    Univ. of Tehran, Tehran, Iran
  • fYear
    2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper, a new method is introduced which is based on the application of adaptive neuro fuzzy method to investigate transformer inrush current. This algorithm uses the second harmonic and the dead angle methods joint to each other utilizes the neuro fuzzy technique. In this method, an inrush detector is defined as an output of neuro fuzzy system. An eligible advantage of this method is evaluation of the inrush detector for three phases; the inrush current conditions can be recognized accurately from internal faults less than one cycle after the occurrence of disturbance. The proposed neuro fuzzy method is trained by the data acquired from a MATLAB-SIMULINK power system model under different conditions.
  • Keywords
    differential transformers; fuzzy neural nets; fuzzy reasoning; harmonic analysis; learning (artificial intelligence); power engineering computing; power transformer protection; MATLAB-SIMULINK power system model; adaptive neurofuzzy method; dead angle method; inrush detector; internal fault; second harmonic method; transformer digital differential protection; transformer inrush current identification; Circuit faults; Detectors; Fault currents; Power system harmonics; Power transformers; Surge protection; Surges; differential protection; inrush current; neuro fuzzy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Environment and Electrical Engineering (EEEIC), 2011 10th International Conference on
  • Conference_Location
    Rome
  • Print_ISBN
    978-1-4244-8779-0
  • Type

    conf

  • DOI
    10.1109/EEEIC.2011.5874743
  • Filename
    5874743