An Improved Empirical Mode Decomposition Method for Monitoring Electromechanical Oscillations

被引：0

作者：

Peng, J. C-H ^{[1
]}

Kirtley, J. L., Jr. ^{[2
]}

机构：

[1] Masdar Inst Sci & Technol, Dept Elect Engn & Comp Sci, Abu Dhabi, U Arab Emirates

[2] MIT, Dept Elect Engn & Comp Sci, Cambridge, MA 02139 USA

来源：

2014 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE (ISGT) | 2014年

关键词：

Electromechanical oscillation; Empirical Mode Decomposition (EMD); Hilbert-Huang Transform (HHT); Inter-area oscillation; Synchrophasor measurements; HILBERT SPECTRUM; IDENTIFICATION; STABILITY; FILTER;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页数：5

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