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http://dx.doi.org/10.5370/KIEE.2017.66.2.261

Eigenvalue Analysis and Detection of Low Frequency Oscillation using PMU Data in KEPCO System  

Shim, Kwan-Shik (Dept. of Electrical Engineering, Chonnam National University)
Kim, Sang-Tae (Energy Solution Team, LG CNS Ltd.)
Kim, Tae-Kyun (Korea Electric Power Corporation(KEPCO))
Ahn, Seon-Ju (Dept. of Electrical Engineering, Chonnam National University)
Choi, Joon-Ho (Dept. of Electrical Engineering, Chonnam National University)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.66, no.2, 2017 , pp. 261-284 More about this Journal
Abstract
This paper describes the results of a low-frequency oscillation analysis using data measured in PMU installed in the KEPCO system, and the comparison with eigenvalues computed from the linear model. The dominant oscillation modes are estimated by applying various algorithms. The algorithms are: the extended Prony method; multiple time interval parameter estimation method; subspace system identification method; and spectral analysis. From the measurement data, modes of frequency 0.68[Hz] and 0.92[Hz] were estimated, and modes of frequency 0.63[Hz] and 0.80[Hz] were computed from the eigenvalue calculation. There was a difference between the mode estimated from measurement data and that from the linear model. This is possibly because of an error in the dynamic data of the KEPCO system used in eigenvalue calculation. Because wide area modes exist in the KEPCO system, these modes should be monitored continuously for the reliable operation of the system. In order to prevent total blackouts caused by wide area oscillation, moreover, contingency analysis should be performed in relation to this mode and appropriate measures should be established.
Keywords
Eigenvalue; Oscillation mode; Parameter estimation; PMU; Prediction error polynomial; Subspace method;
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Times Cited By KSCI : 3  (Citation Analysis)
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