Adaptive parameter estimation of power system dynamic model using modal information

Song Guo, Sean Norris, Janusz Bialek

Research output: Contribution to journalArticlepeer-review

29 Citations (Scopus)


A novel method for estimating parameters of a dynamic system model is presented using estimates of dynamic system modes (frequency and damping) obtained from wide area measurement systems (WAMS). The parameter estimation scheme is based on weighted least squares (WLS) method that utilizes sensitivities of the measured modal frequencies and damping to the parameters. The paper concentrates on estimating the values of generator inertias but the proposed methodology is general and can be used to identify other generator parameters such as damping coefficients. The methodology has been tested using a wide range of accuracy in the measured modes of oscillations. The results suggest that the methodology is capable of estimating accurately inertias and replicating the dynamic behavior of the power system. It has been shown that the damping measurements do not influence estimation of generator inertia. The method has overcome the problem of observability, when there were fewer measurements than the parameters to be estimated, by including the assumed values of parameters as pseudo-measurements.

Original languageEnglish
Article number6805671
Pages (from-to)2854-2861
Number of pages8
JournalIEEE Transactions on Power Systems
Issue number6
Publication statusPublished - 1 Nov 2014
Externally publishedYes


  • Dynamic power system modeling
  • parameter estimation
  • small signal analysis
  • synchronous generators
  • wide area measurements


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