An improved Hilbert Vibration Decomposition method for analysis of low frequency oscillations

Author

Ramos, J.J. ; Reyes, J.I. ; Barocio, E.

Author_Institution

Dept. of Electr. Eng., Cinvestav IPN, Zapopan, Mexico

fYear

2014

fDate

10-13 Sept. 2014

Firstpage

1

Lastpage

6

Abstract

In this paper, a masking-based Hilbert Vibration Decomposition (HVD) method is proposed to analyze nonlinear and non-stationary power system data. An adaptive masking signal method derived from the data itself is used to improve the decomposition ability of the HVD method. Techniques to compute the masking signal are described and precise criteria to increase the modal resolution of the HVD method are derived. Simulation results using both synthetic and simulated data show that the technique can be used to characterize complex oscillatory processes in power systems.

Keywords

Hilbert transforms; adaptive signal processing; power system stability; vibrations; HVD method; Hilbert-Huang transform; adaptive masking signal method; complex oscillatory processes; improved Hilbert vibration decomposition method; low frequency oscillation analysis; modal resolution; nonlinear power system data analysis; nonstationary power system data analysis; Demodulation; Estimation; Frequency estimation; Oscillators; Power systems; Transient analysis; Vibrations; HVD method; low-frequency oscillation; masking signal; non-stationary signals;

fLanguage

English

Publisher

ieee

Conference_Titel

Transmission & Distribution Conference and Exposition - Latin America (PES T&D-LA), 2014 IEEE PES

Conference_Location

Medellin

Print_ISBN

978-1-4799-6250-1

Type

conf

DOI

10.1109/TDC-LA.2014.6955216

Filename

6955216