• DocumentCode
    75757
  • Title

    Ladder Network Parameters Determination Considering Nondominant Resonances of the Transformer Winding

  • Author

    Shabestary, Masoud M. ; Ghanizadeh, Ahmad Javid ; Gharehpetian, G.B. ; Agha-Mirsalim, Mojtaba

  • Author_Institution
    Dept. of Electr. Eng., Amirkabir Univ. of Technol., Tehran, Iran
  • Volume
    29
  • Issue
    1
  • fYear
    2014
  • fDate
    Feb. 2014
  • Firstpage
    108
  • Lastpage
    117
  • Abstract
    In order to accurately model the transient behavior of transformer windings, we need models with a large number of nodes and parameters. This paper proposes a model that has fewer nodes and can accurately predict the behavior of a transformer in a wide range of frequencies. In the proposed method, based on the terminal measurements, N dominant resonances are determined, and it is experimentally shown that the winding has N-1 hidden resonances. Using this idea, we suggest the use of a 2N-1 section ladder network, which has a minimum number of nodes and can accurately model the behavior of the transformer winding. The parameters of this model are determined by minimizing the error function by using the genetic algorithm. The close agreement between the simulation and measurement results on the windings of a 20/0.4-kV and 1600-kVA transformer verifies the accuracy of the proposed method.
  • Keywords
    genetic algorithms; power transformers; transformer windings; apparent power 1600 kVA; dominant resonances; error function minimization; genetic algorithm; ladder network parameters determination; nondominant resonances; terminal measurements; transformer windings; transient behavior; voltage 0.4 kV; voltage 20 kV; Accuracy; Capacitance; Genetic algorithms; Impedance; Impedance measurement; Power transformers; Windings; Frequency-response analysis (FRA); genetic algorithm (GA); ladder network; power transformer windings;
  • fLanguage
    English
  • Journal_Title
    Power Delivery, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8977
  • Type

    jour

  • DOI
    10.1109/TPWRD.2013.2278784
  • Filename
    6651674