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Title: Fast Robust Power System Dynamic State Estimation using Model Transformation

Abstract

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 effectivenessmore » and robustness of the proposed approach under various conditions.« less

Authors:
 [1];  [2];  [3];  [4]
  1. Xi’an University of Science and Technology
  2. Virginia Polytechnic Institute
  3. The University of Manchester
  4. BATTELLE (PACIFIC NW LAB)
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1532527
Report Number(s):
PNNL-SA-144598
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Journal Name:
International Journal of Electrical Power & Energy Systems
Additional Journal Information:
Journal Volume: 114
Country of Publication:
United States
Language:
English

Citation Formats

Wang, Xueyuan, Zhao, Junbo, Terzija, Vladimir, and Wang, Shaobu. Fast Robust Power System Dynamic State Estimation using Model Transformation. United States: N. p., 2020. Web. doi:10.1016/j.ijepes.2019.105390.
Wang, Xueyuan, Zhao, Junbo, Terzija, Vladimir, & Wang, Shaobu. Fast Robust Power System Dynamic State Estimation using Model Transformation. United States. doi:10.1016/j.ijepes.2019.105390.
Wang, Xueyuan, Zhao, Junbo, Terzija, Vladimir, and Wang, Shaobu. Wed . "Fast Robust Power System Dynamic State Estimation using Model Transformation". United States. doi:10.1016/j.ijepes.2019.105390.
@article{osti_1532527,
title = {Fast Robust Power System Dynamic State Estimation using Model Transformation},
author = {Wang, Xueyuan and Zhao, Junbo and Terzija, Vladimir and Wang, Shaobu},
abstractNote = {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.},
doi = {10.1016/j.ijepes.2019.105390},
journal = {International Journal of Electrical Power & Energy Systems},
number = ,
volume = 114,
place = {United States},
year = {2020},
month = {1}
}