DocumentCode
140431
Title
An improved Empirical Mode Decomposition method for monitoring electromechanical oscillations
Author
Peng, Jimmy C.-H. ; Kirtley, James L.
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., Masdar Inst. of Sci. & Technol., Abu Dhabi, United Arab Emirates
fYear
2014
fDate
19-22 Feb. 2014
Firstpage
1
Lastpage
5
Abstract
The use of Hilbert-Huang Transform (HHT) demonstrated to be effective in detecting time-varying electromechanical oscillations. HHT is a two-step algorithm, consisting of Empirical Mode Decomposition (EMD) and Hilbert Transform. EMD decomposes a signal into a set of Intrinsic Mode Functions, each containing the one oscillatory function. In this paper, the focus is on improving the EMD operation. The proposed enhancements increase the resistance of EMD against mode mixing. Mode mixing is defined as the intermittency of oscillatory dynamics due to operating conditions or abrupt disturbances. The improved EMD (IEMD) is comparatively evaluated with the conventional EMD (CEMD) for tracking simple synthetic signals and simulated system measurements. Based on observations, IEMD provides better mode tracking capability than CEMD.
Keywords
Hilbert transforms; oscillations; phasor measurement; power grids; CEMD; HHT; Hilbert-Huang transform; IEMD; conventional EMD; empirical mode decomposition method; improved EMD; intrinsic mode functions; mode mixing; oscillatory dynamics; oscillatory function; synchrophasor measurement; synthetic signal tracking; time-varying electromechanical oscillation monitoring; Damping; Empirical mode decomposition; Monitoring; Oscillators; Power system dynamics; Power system stability; Electromechanical oscillation; Empirical Mode Decomposition (EMD); Hilbert-Huang Transform (HHT); Inter-area oscillation; Synchrophasor measurements;
fLanguage
English
Publisher
ieee
Conference_Titel
Innovative Smart Grid Technologies Conference (ISGT), 2014 IEEE PES
Conference_Location
Washington, DC
Type
conf
DOI
10.1109/ISGT.2014.6816433
Filename
6816433
Link To Document