Smoothness Prior Approach to Removing Nonlinear Trends from Signals in Identification of Low Frequency Oscillation Mode

Abstract:

The online identification of low frequency oscillation mode based on measured signal from PMU is the base of damping control. Removing nonlinear trend from the signal effectively can ensure the precision of mode identification. A method named smoothness prior approach (SPA) is proposed to remove the nonlinear trend from measured signal. In order to meet the demand of removing nonlinear trend for identification of low frequency oscillation based on analyzing the basic principle of smoothness prior approach, it determines regularization parameter of smoothness prior approach according to its characteristic of frequency response. It is used to analyze the simulation signals from IEEE-39 bus power system and the measured signals in some power grid, and compared with empirical mode decomposition and digital filter method. The results demonstrate that this proposed method can successfully remove nonlinear trend from the signal and improve the speed of computation, as well as the precision of mode identification, which has a relatively high practical value.

• Periodical: Applied Mechanics and Materials (Volumes 672-674)
• Pages: 1070-1074
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.672-674.1070
• Online since: October 2014
• Authors: Yu Jiang Wang*, Jian Li, Hui Xu, Hai Ou Yan, Jia Yuan, Jun Hua Li, Xiao Hui Liu, Qi Zhou, Na Li
• Keywords: Low Frequency Oscillation Mode, Measured Signal, Nonlinear Trend, Online Identification, Smoothness Prior Approach

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