By Topic

Online Identification of Low-Frequency Oscillation Based on Principal Component Analysis Subspace Tracking Algorithm

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Wang Fangzong ; Coll. of Electr. Eng. & Inf. Technol., China Three Gorges Univ., Yichang, China ; Li Chengcheng

The authors propose a new principal component analysis subspace tracking algorithm for analysis of low-frequency oscillations. This algorithm has the merits of prony algorithm that it can get oscillation frequency, attenuation, amplitude and phase of the system from the data, which being measured now. At the same time, because the subspace doesn't require eigenvalue decomposition of the sample correlation matrix or singular value decomposition of the data matrix, the calculation time is reduced. The results of simulation of the model of low-frequency oscillation validate the feasibility and effectiveness of the proposed method.

Published in:

Power and Energy Engineering Conference (APPEEC), 2010 Asia-Pacific

Date of Conference:

28-31 March 2010