Improved modelling of power transformer winding using bacterial swarming algorithm and frequency response analysis

A. Shintemirov, W. J. Tang, W. H. Tang, Q. H. Wu

Research output: Contribution to journalArticle

39 Citations (Scopus)


The paper discusses an improved modelling of transformer windings based on bacterial swarming algorithm (BSA) and frequency response analysis (FRA). With the purpose to accurately identify transformer windings parameters a model-based identification approach is introduced using a well-known lumped parameter model. It includes search space estimation using analytical calculations, which is used for the subsequent model parameters identification with a novel BSA. The newly introduced BSA, being developed upon a bacterial foraging behavior, is described in detail. Simulations and discussions are presented to explore the potential of the proposed approach using simulated and experimentally measured FRA responses taken from two transformers. The BSA identification results are compared with those using genetic algorithm. It is shown that the proposed BSA delivers satisfactory parameter identification and improved modelling can be used for FRA results interpretation.

Original languageEnglish
Pages (from-to)1111-1120
Number of pages10
JournalElectric Power Systems Research
Issue number9
Publication statusPublished - Sep 2010



  • Bacterial swarming algorithm
  • Frequency response analysis
  • Mathematical model
  • Parameter identification
  • Transformer winding

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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