Retrofitting the BCTRAN transformer model with nonlinear magnetizing branches for the accurate study of low-frequency deep saturating transients

Ming Yang, Reza Kazemi, Saeed Jazebi, Digvijay Deswal, Francisco De Leon

Research output: Contribution to journalArticle

Abstract

In this paper, an extension to the multiwinding BCTRAN model is proposed for the study of low-frequency saturating transients in single-phase transformers. The conventional experimentally obtained BCTRAN (winding leakage) susceptance matrix is retrofitted with a previously missing experimentally obtained nonlinear (core magnetizing) model. The assembled model gives accurate results for transients in all terminals. The model parameters can be acquired from information available in the nameplate plus terminal tests without the need of detailed transformer design or construction information. Only needed are standard no-load and impedance tests plus a newly introduced saturation test. Very simple formulas are proposed to compute the parameters. Illustrative examples on how the parameters are computed are given for three transformers rated 1.8, 5, and 75 kVA. For model validation, laboratory inrush currents tests are carried out and compared with simulations using the EMTP-RV. The results show that the simulations and experimental results match very closely giving great confidence in the model correctness and parameter estimation method.

Original languageEnglish (US)
Article number8334572
Pages (from-to)2344-2353
Number of pages10
JournalIEEE Transactions on Power Delivery
Volume33
Issue number5
DOIs
StatePublished - Oct 2018

Keywords

  • BCTRAN
  • EMTP
  • electromagnetic transients
  • saturation inductance
  • terminal measurements
  • transformer modeling

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Retrofitting the BCTRAN transformer model with nonlinear magnetizing branches for the accurate study of low-frequency deep saturating transients'. Together they form a unique fingerprint.

  • Cite this