Construction of transformer core model for frequency response analysis with genetic algorithm

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a novel model-based identification approach to determining laminated core parameters of power transformers on the basis of frequency response analysis (FRA) measurements. A genetic algorithm is employed for parameter identification of a transformer core model, established using the duality principle between magnetic and electrical circuits. A well-known lumped parameter model of a 3-phase transformer is used to simulate reference input impedance frequency responses for analyzing the identification accuracy of the proposed approach. It is suggested that the approach can be applied for transformer core modeling and FRA result interpretation at low frequencies.

Original languageEnglish
Title of host publication2009 IEEE Power and Energy Society General Meeting, PES '09
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event2009 IEEE Power and Energy Society General Meeting, PES '09 - Calgary, AB, Canada
Duration: Jul 26 2009Jul 30 2009

Other

Other2009 IEEE Power and Energy Society General Meeting, PES '09
CountryCanada
CityCalgary, AB
Period7/26/097/30/09

Fingerprint

Frequency response
Genetic algorithms
Identification (control systems)
Power transformers
Networks (circuits)

Keywords

  • Frequency response analysis
  • Genetic algorithm
  • Magnetic-electric duality principle
  • Parameter identification
  • Transformer core

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

Cite this

Shintemirov, A., Tang, W. H., & Wu, Q. H. (2009). Construction of transformer core model for frequency response analysis with genetic algorithm. In 2009 IEEE Power and Energy Society General Meeting, PES '09 [5275586] https://doi.org/10.1109/PES.2009.5275586

Construction of transformer core model for frequency response analysis with genetic algorithm. / Shintemirov, A.; Tang, W. H.; Wu, Q. H.

2009 IEEE Power and Energy Society General Meeting, PES '09. 2009. 5275586.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Shintemirov, A, Tang, WH & Wu, QH 2009, Construction of transformer core model for frequency response analysis with genetic algorithm. in 2009 IEEE Power and Energy Society General Meeting, PES '09., 5275586, 2009 IEEE Power and Energy Society General Meeting, PES '09, Calgary, AB, Canada, 7/26/09. https://doi.org/10.1109/PES.2009.5275586
Shintemirov A, Tang WH, Wu QH. Construction of transformer core model for frequency response analysis with genetic algorithm. In 2009 IEEE Power and Energy Society General Meeting, PES '09. 2009. 5275586 https://doi.org/10.1109/PES.2009.5275586
Shintemirov, A. ; Tang, W. H. ; Wu, Q. H. / Construction of transformer core model for frequency response analysis with genetic algorithm. 2009 IEEE Power and Energy Society General Meeting, PES '09. 2009.
@inproceedings{9004cc9fc6974747ba40abe97a2975ce,
title = "Construction of transformer core model for frequency response analysis with genetic algorithm",
abstract = "This paper presents a novel model-based identification approach to determining laminated core parameters of power transformers on the basis of frequency response analysis (FRA) measurements. A genetic algorithm is employed for parameter identification of a transformer core model, established using the duality principle between magnetic and electrical circuits. A well-known lumped parameter model of a 3-phase transformer is used to simulate reference input impedance frequency responses for analyzing the identification accuracy of the proposed approach. It is suggested that the approach can be applied for transformer core modeling and FRA result interpretation at low frequencies.",
keywords = "Frequency response analysis, Genetic algorithm, Magnetic-electric duality principle, Parameter identification, Transformer core",
author = "A. Shintemirov and Tang, {W. H.} and Wu, {Q. H.}",
year = "2009",
doi = "10.1109/PES.2009.5275586",
language = "English",
isbn = "9781424442416",
booktitle = "2009 IEEE Power and Energy Society General Meeting, PES '09",

}

TY - GEN

T1 - Construction of transformer core model for frequency response analysis with genetic algorithm

AU - Shintemirov, A.

AU - Tang, W. H.

AU - Wu, Q. H.

PY - 2009

Y1 - 2009

N2 - This paper presents a novel model-based identification approach to determining laminated core parameters of power transformers on the basis of frequency response analysis (FRA) measurements. A genetic algorithm is employed for parameter identification of a transformer core model, established using the duality principle between magnetic and electrical circuits. A well-known lumped parameter model of a 3-phase transformer is used to simulate reference input impedance frequency responses for analyzing the identification accuracy of the proposed approach. It is suggested that the approach can be applied for transformer core modeling and FRA result interpretation at low frequencies.

AB - This paper presents a novel model-based identification approach to determining laminated core parameters of power transformers on the basis of frequency response analysis (FRA) measurements. A genetic algorithm is employed for parameter identification of a transformer core model, established using the duality principle between magnetic and electrical circuits. A well-known lumped parameter model of a 3-phase transformer is used to simulate reference input impedance frequency responses for analyzing the identification accuracy of the proposed approach. It is suggested that the approach can be applied for transformer core modeling and FRA result interpretation at low frequencies.

KW - Frequency response analysis

KW - Genetic algorithm

KW - Magnetic-electric duality principle

KW - Parameter identification

KW - Transformer core

UR - http://www.scopus.com/inward/record.url?scp=71849107101&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=71849107101&partnerID=8YFLogxK

U2 - 10.1109/PES.2009.5275586

DO - 10.1109/PES.2009.5275586

M3 - Conference contribution

SN - 9781424442416

BT - 2009 IEEE Power and Energy Society General Meeting, PES '09

ER -