Advisor(s)

Hanoch Lev-Ari

Contributor(s)

Ali Abur (1957-), Dana H. Brooks

Date of Award

2010

Date Accepted

12-2010

Degree Grantor

Northeastern University

Degree Level

M.S.

Degree Name

Master of Science

Department or Academic Unit

College of Engineering. Department of Electrical and Computer Engineering.

Keywords

customized wavelets, fault location, power system faults, waveform peakedness, waveform sharpness

Disciplines

Electrical and Computer Engineering | Engineering

Abstract

A procedure for generating customized wavelets for detecting the location of a fault in a power transmission line is presented and analyzed. A typical fault waveform consists of a 60Hz component and multiple reflections of a short transient. Measuring the time-difference-of-arrival (TDOA) between two consecutive transient reflections provides an accurate estimate of the location of the fault. Highly accurate TDOA estimates can be obtained only when the processed fault waveform consists of short/peaked pulses. Our customization procedure enhances the "peakedness" of the transient waveform by optimizing a suitable peakedness metric. This approach yields more accurate estimates than a previously proposed method [1], which used a standard (Daubechies-4) wavelet to process the fault waveform. Our analysis also provides us with some insight as to why a discrete wavelet transform (including the one used in [1]) can significantly enhance the peakedness of a wide variety of power system fault waveforms.

Document Type

Master's Thesis

Rights Holder

Argyropoulos Paraskevas


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