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Frequency domain interpolation wavelet transform based algorithm for harmonic analysis of power system

Authors: null Tianjun Du; null Guangju Chen; null Yong Lei;

Frequency domain interpolation wavelet transform based algorithm for harmonic analysis of power system

Abstract

A power system harmonic detection technique based on a frequency domain interpolation wavelet transform is proposed. Aiming at harmonic detection, a fast Fourier transform (FFT) can only detect integer harmonics; a short time Fourier transform (STFT) can detect non-integer harmonics with low resolution; a wavelet transform can detect non-integer harmonics, but it has spectral aliasing and spectral leakage phenomena, which result in low resolution. This paper uses a frequency domain interpolation algorithm to detect a harmonic signal by choosing a Shannon wavelet. Simulation and comparative results obtained by three algorithms reveal that: the proposed method can effectively eliminate spectral aliasing, spectral leakage and the Gibbs phenomenon; it can precisely detect a harmonic signal, so it provides an effective means for power system harmonic analysis and detection.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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