Nonlinear estimation of synchronous machine parameters using operating data

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

    Research output: Contribution to journalArticlepeer-review


    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. © 2011 IEEE.
    Original languageEnglish
    Article number5937045
    Pages (from-to)831-839
    Number of pages8
    JournalIEEE Transactions on Energy Conversion
    Issue number3
    Publication statusPublished - Sept 2011


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


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