Accurate information about generator rotor speeds and angles plays an important role for power
system transient stability online assessment and protection. To address this need, this paper proposes a
fast and robust estimation approach based on the model transformation strategy. Thanks to this strategy,
the original complex nonlinear model is transformed into a linear one without linerization, which makes
the dynamical system observability analysis and the estimation problem significantly easier to solve. The
proposed model transformation strategy is achieved by taking the measured generator active power as
the input variable and the derived frequency and the rate of change of frequency measurements from the
phasor measurement units (PMUs) as the output variables of the dynamical generator model. This allows
us to estimate the generator rotor speeds and angles using only local PMU measurements and the swing
equations, relaxing the need of a detailed generator model on which the existing dynamic state estimators
are based. A robust Kalman filter is also developed to handle data quality problems as the frequency
and rate of change of frequency measurements can be biased in presence of severe disturbance or
communication issues. Comparison results carried out on the IEEE 39-bus system successfully validate
the effectiveness and robustness of the proposed approach under various conditions.
Revised: July 9, 2019 |
Published: January 1, 2020
Citation
Wang X., J. Zhao, V. Terzija, and S. Wang. 2020.Fast Robust Power System Dynamic State Estimation using Model Transformation.International Journal of Electrical Power & Energy Systems 114.PNNL-SA-144598.doi:10.1016/j.ijepes.2019.105390