Application of Morlet wavelets to supervise power system disturbances

Shyh Jier Huang; Cheng Tao Hsieh; Ching Lien Huang

doi:10.1109/61.736728

Application of Morlet wavelets to supervise power system disturbances

Shyh Jier Huang, Cheng Tao Hsieh, Ching Lien Huang

Department of Electrical Engineering

Research output: Contribution to journal › Article › peer-review

203 Citations (Scopus)

Abstract

A wavelet transform approach using Morlet basis function is proposed to supervise power system disturbances in this paper. With the time-frequency localization characteristics embedded in wavelets, the time and frequency information of a waveform can be presented as a visualized scheme. Different from the fast Fourier transform, the wavelet transform approach is more efficient in monitoring various disturbances as time varies. The method has been tested on the detection of various simulated disturbances including voltage sag, voltage swell, momentary interruption and oscillatory transients, and on the harmonic analysis of the arc furnace from the field test data Testing results demonstrated the practicality and advantages of the proposed method for the applications.

Original language	English
Pages (from-to)	235-241
Number of pages	7
Journal	IEEE Transactions on Power Delivery
Volume	14
Issue number	1
DOIs	https://doi.org/10.1109/61.736728
Publication status	Published - 1999

All Science Journal Classification (ASJC) codes

Energy Engineering and Power Technology
Electrical and Electronic Engineering

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10.1109/61.736728

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abstract = "A wavelet transform approach using Morlet basis function is proposed to supervise power system disturbances in this paper. With the time-frequency localization characteristics embedded in wavelets, the time and frequency information of a waveform can be presented as a visualized scheme. Different from the fast Fourier transform, the wavelet transform approach is more efficient in monitoring various disturbances as time varies. The method has been tested on the detection of various simulated disturbances including voltage sag, voltage swell, momentary interruption and oscillatory transients, and on the harmonic analysis of the arc furnace from the field test data Testing results demonstrated the practicality and advantages of the proposed method for the applications.",

author = "Huang, {Shyh Jier} and Hsieh, {Cheng Tao} and Huang, {Ching Lien}",

note = "Funding Information: The authors would like to express their thanks to the financial support gven by the National Science Council of Republic of China under contract number NSC85-2213-E-214-007 and the technical support from Taiwan Power Company.",

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AU - Huang, Shyh Jier

AU - Hsieh, Cheng Tao

AU - Huang, Ching Lien

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Y1 - 1999

N2 - A wavelet transform approach using Morlet basis function is proposed to supervise power system disturbances in this paper. With the time-frequency localization characteristics embedded in wavelets, the time and frequency information of a waveform can be presented as a visualized scheme. Different from the fast Fourier transform, the wavelet transform approach is more efficient in monitoring various disturbances as time varies. The method has been tested on the detection of various simulated disturbances including voltage sag, voltage swell, momentary interruption and oscillatory transients, and on the harmonic analysis of the arc furnace from the field test data Testing results demonstrated the practicality and advantages of the proposed method for the applications.

AB - A wavelet transform approach using Morlet basis function is proposed to supervise power system disturbances in this paper. With the time-frequency localization characteristics embedded in wavelets, the time and frequency information of a waveform can be presented as a visualized scheme. Different from the fast Fourier transform, the wavelet transform approach is more efficient in monitoring various disturbances as time varies. The method has been tested on the detection of various simulated disturbances including voltage sag, voltage swell, momentary interruption and oscillatory transients, and on the harmonic analysis of the arc furnace from the field test data Testing results demonstrated the practicality and advantages of the proposed method for the applications.

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Application of Morlet wavelets to supervise power system disturbances

Abstract

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