Identification of Power Quality Disturbances Based on EEMD and TEO

Abstract:

The empirical mode decomposition (EMD) is a good time-frequency analysis method, which can deal with nonlinear and non-stationary signals. Aiming at improving modal aliasing problem brought by the traditional EMD, white noise is introduced into the improved aided analysis algorithm namely ensemble empirical mode decomposition (EEMD), instantaneous amplitude and frequency can be obtained by using teager energy operator (TEO), which is adopted to identify the type of power quality disturbance. The anti-aliasing of EEMD and real-time detection of TEO are verified by the signal simulation in Matlab. Simulation and experimental results show that the proposed algorithm can detect and locate power quality disturbances accurately and quickly, with excellent detection effects.

• Periodical: Applied Mechanics and Materials (Volumes 433-435)
• Pages: 469-476
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.433-435.469
• Online since: October 2013
• Authors: Song Jun Wang, Qing Fen Liao*, Di Chen Liu, Yu Tian Zhou, Bin Kun Xu, Yi Fei Wang, Lie Lu
• Keywords: Disturbance Identification, Ensemble Empirical Mode Decomposition (EEMD), Power Quality (PQ), Teager Energy Operator (TEO)

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