Nonlinear estimation of synchronous machine parameters using operating data

Gustavo Valverde, Elias Kyriakides, Gerald T. Heydt, Vladimir Terzija

Research output: Contribution to journalArticle

27 Citations (Scopus)

Abstract

This paper presents a nonlinear parameter estimator for synchronous machines based on the unscented Kalman filter. The proposed methodology uses voltages and current signals recorded from the stator and the field winding to update the parameters of the classical model of the synchronous machine for stability studies. The methodology can be applied without interrupting the normal operation of the generator. Parks Transformation is included in the estimation process to relate the stator measurements (in abc components) to the nonlinear voltage equations in the qd0 reference frame. The proposed robust methodology has been validated using real and simulated data to estimate the model parameters of a 483-MVA round rotor machine.

Original languageEnglish (US)
Article number5937045
Pages (from-to)831-839
Number of pages9
JournalIEEE Transactions on Energy Conversion
Volume26
Issue number3
DOIs
StatePublished - Sep 2011

Fingerprint

Stators
Electric potential
Kalman filters
Rotors

Keywords

  • Generator modeling
  • parameter estimation
  • synchronous machines
  • unscented Kalman filter (UKF)

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Energy Engineering and Power Technology

Cite this

Nonlinear estimation of synchronous machine parameters using operating data. / Valverde, Gustavo; Kyriakides, Elias; Heydt, Gerald T.; Terzija, Vladimir.

In: IEEE Transactions on Energy Conversion, Vol. 26, No. 3, 5937045, 09.2011, p. 831-839.

Research output: Contribution to journalArticle

Valverde, Gustavo ; Kyriakides, Elias ; Heydt, Gerald T. ; Terzija, Vladimir. / Nonlinear estimation of synchronous machine parameters using operating data. In: IEEE Transactions on Energy Conversion. 2011 ; Vol. 26, No. 3. pp. 831-839.
@article{a921f49398bd4bc5859fd0bb106348d5,
title = "Nonlinear estimation of synchronous machine parameters using operating data",
abstract = "This paper presents a nonlinear parameter estimator for synchronous machines based on the unscented Kalman filter. The proposed methodology uses voltages and current signals recorded from the stator and the field winding to update the parameters of the classical model of the synchronous machine for stability studies. The methodology can be applied without interrupting the normal operation of the generator. Parks Transformation is included in the estimation process to relate the stator measurements (in abc components) to the nonlinear voltage equations in the qd0 reference frame. The proposed robust methodology has been validated using real and simulated data to estimate the model parameters of a 483-MVA round rotor machine.",
keywords = "Generator modeling, parameter estimation, synchronous machines, unscented Kalman filter (UKF)",
author = "Gustavo Valverde and Elias Kyriakides and Heydt, {Gerald T.} and Vladimir Terzija",
year = "2011",
month = "9",
doi = "10.1109/TEC.2011.2141136",
language = "English (US)",
volume = "26",
pages = "831--839",
journal = "IEEE Transactions on Energy Conversion",
issn = "0885-8969",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "3",

}

TY - JOUR

T1 - Nonlinear estimation of synchronous machine parameters using operating data

AU - Valverde, Gustavo

AU - Kyriakides, Elias

AU - Heydt, Gerald T.

AU - Terzija, Vladimir

PY - 2011/9

Y1 - 2011/9

N2 - This paper presents a nonlinear parameter estimator for synchronous machines based on the unscented Kalman filter. The proposed methodology uses voltages and current signals recorded from the stator and the field winding to update the parameters of the classical model of the synchronous machine for stability studies. The methodology can be applied without interrupting the normal operation of the generator. Parks Transformation is included in the estimation process to relate the stator measurements (in abc components) to the nonlinear voltage equations in the qd0 reference frame. The proposed robust methodology has been validated using real and simulated data to estimate the model parameters of a 483-MVA round rotor machine.

AB - This paper presents a nonlinear parameter estimator for synchronous machines based on the unscented Kalman filter. The proposed methodology uses voltages and current signals recorded from the stator and the field winding to update the parameters of the classical model of the synchronous machine for stability studies. The methodology can be applied without interrupting the normal operation of the generator. Parks Transformation is included in the estimation process to relate the stator measurements (in abc components) to the nonlinear voltage equations in the qd0 reference frame. The proposed robust methodology has been validated using real and simulated data to estimate the model parameters of a 483-MVA round rotor machine.

KW - Generator modeling

KW - parameter estimation

KW - synchronous machines

KW - unscented Kalman filter (UKF)

UR - http://www.scopus.com/inward/record.url?scp=80052054349&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80052054349&partnerID=8YFLogxK

U2 - 10.1109/TEC.2011.2141136

DO - 10.1109/TEC.2011.2141136

M3 - Article

AN - SCOPUS:80052054349

VL - 26

SP - 831

EP - 839

JO - IEEE Transactions on Energy Conversion

JF - IEEE Transactions on Energy Conversion

SN - 0885-8969

IS - 3

M1 - 5937045

ER -