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Identification of Dominant Low Frequency Oscillation Modes Based on Blind Source Separation.

Authors :
Zhang, A. Q.
Zhang, L. L.
Li, M. S.
Wu, Q. H.
Source :
IEEE Transactions on Power Systems. Nov2017, Vol. 32 Issue 6, p4774-4782. 9p.
Publication Year :
2017

Abstract

On-line monitoring and analysis of low frequency oscillation (LFO) are important for stability and security of a power system. This paper proposes a blind source separation (BSS) based method for LFO modal analysis of one-channel measured signal, which consists of a second-order blind identification (SOBI) algorithm and the Hilbert transform (HT) technique. This is the first time when a BSS technique is applied as a modal decomposition tool in this field. The proposed SOBI-HT based dominant mode identification method combines an iteration procedure with an identification procedure to determine the model order, and then identify dominant modes. The performance of the proposed method is evaluated on numerical simulation signals and a record of real data, verifying its effectiveness and accuracy. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISSN :
08858950
Volume :
32
Issue :
6
Database :
Academic Search Index
Journal :
IEEE Transactions on Power Systems
Publication Type :
Academic Journal
Accession number :
125813529
Full Text :
https://doi.org/10.1109/TPWRS.2017.2685533