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Title: Application of Ensemble Kalman Filter in Power System State Tracking and Sensitivity

Abstract

Ensemble Kalman Filter (EnKF) is proposed to track dynamic states of generators. The algorithm of EnKF and its application to generator state tracking are presented in detail. The accuracy and sensitivity of the method are analyzed with respect to initial state errors, measurement noise, unknown fault locations, time steps and parameter errors. It is demonstrated through simulation studies that even with some errors in the parameters, the developed EnKF can effectively track generator dynamic states using disturbance data.

Authors:
; ; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1092038
Report Number(s):
PNNL-SA-82886
KJ0401000
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Conference
Resource Relation:
Conference: IEEE PES Transmission and Distribution Conference and Exposition (T&D 2012), May 7-10, 2012, Orlando, Florida , 1-8
Country of Publication:
United States
Language:
English
Subject:
dynamic state tracking; ensemble Kalman filter; power system; sensitivity analysis.

Citation Formats

Li, Yulan, Huang, Zhenyu, Zhou, Ning, Lee, Barry, Diao, Ruisheng, and Du, Pengwei. Application of Ensemble Kalman Filter in Power System State Tracking and Sensitivity. United States: N. p., 2012. Web. doi:10.1109/TDC.2012.6281499.
Li, Yulan, Huang, Zhenyu, Zhou, Ning, Lee, Barry, Diao, Ruisheng, & Du, Pengwei. Application of Ensemble Kalman Filter in Power System State Tracking and Sensitivity. United States. https://doi.org/10.1109/TDC.2012.6281499
Li, Yulan, Huang, Zhenyu, Zhou, Ning, Lee, Barry, Diao, Ruisheng, and Du, Pengwei. Tue . "Application of Ensemble Kalman Filter in Power System State Tracking and Sensitivity". United States. https://doi.org/10.1109/TDC.2012.6281499.
@article{osti_1092038,
title = {Application of Ensemble Kalman Filter in Power System State Tracking and Sensitivity},
author = {Li, Yulan and Huang, Zhenyu and Zhou, Ning and Lee, Barry and Diao, Ruisheng and Du, Pengwei},
abstractNote = {Ensemble Kalman Filter (EnKF) is proposed to track dynamic states of generators. The algorithm of EnKF and its application to generator state tracking are presented in detail. The accuracy and sensitivity of the method are analyzed with respect to initial state errors, measurement noise, unknown fault locations, time steps and parameter errors. It is demonstrated through simulation studies that even with some errors in the parameters, the developed EnKF can effectively track generator dynamic states using disturbance data.},
doi = {10.1109/TDC.2012.6281499},
url = {https://www.osti.gov/biblio/1092038}, journal = {},
number = ,
volume = ,
place = {United States},
year = {2012},
month = {5}
}

Conference:
Other availability
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