DocumentCode
672639
Title
Power system harmonics estimation using sliding window based LMS
Author
Alhaj, Hussam M. M. ; Nor, N.M. ; Asirvadam, Vijanth S. ; Abdullah, Mohd Faris
Author_Institution
Electr. & Electron. Dept., Univ. Teknol. PETRONAS, Tronoh, Malaysia
fYear
2013
fDate
8-10 Oct. 2013
Firstpage
327
Lastpage
332
Abstract
The widespread use of power electronics devises and nonlinear loads in power system grids is increasing in the last decades leads to rise of harmonic in power system signals. Great damage to power system gird can happen due to harmonics. Thus it is important to precisely estimate the harmonics components that may help to avoid its harmful effect of the electrical grid performance. The more common algorithm that has been used to estimate the harmonic component is the Fast Fourier Transform (FFT), however FFT has few limitations, furthermore, modern power system network getting complex and noisy. Therefore, fast and accurate harmonic estimation in the presence of noise is needed. Sliding window based least mean square (LMS) algorithm is introduced in this paper to estimate the harmonic components in noisy environment. The result shows that the sliding window method able to give a good estimation to the harmonic component even when the signal to noise ratio (SNR) is 0 dB.
Keywords
fast Fourier transforms; least mean squares methods; power electronics; power grids; power system harmonics; FFT; electrical grid performance; fast Fourier transform; harmonic component estimation; least mean square; nonlinear loads; power electronics; power system grids; power system harmonic estimation; power system network; power system signals; sliding window based LMS algorithm; Estimation; Frequency estimation; Harmonic analysis; Least squares approximations; Power harmonic filters; Signal to noise ratio;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal and Image Processing Applications (ICSIPA), 2013 IEEE International Conference on
Conference_Location
Melaka
Print_ISBN
978-1-4799-0267-5
Type
conf
DOI
10.1109/ICSIPA.2013.6708027
Filename
6708027
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