%0 Conference Paper
%A Alhaj, H.M.M.
%A Nor, N.M.
%A Asirvadam, V.S.
%A Abdullah, M.F.
%D 2013
%F scholars:3879
%I IEEE Computer Society
%K Algorithms; Complex networks; Fast Fourier transforms; Harmonic analysis; Image processing; Power electronics; Signal to noise ratio, Harmonic components; Harmonics component; Least mean square algorithms; Power system harmonics; Power system networks; Power system signal; Sliding window methods; Sliding window-based, Estimation
%P 327-332
%R 10.1109/ICSIPA.2013.6708027
%T Power system harmonics estimation using sliding window based LMS
%U https://khub.utp.edu.my/scholars/3879/
%X 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. © 2013 IEEE.
%Z cited By 10; Conference of 2013 3rd IEEE International Conference on Signal and Image Processing Applications, IEEE ICSIPA 2013 ; Conference Date: 8 October 2013 Through 10 October 2013; Conference Code:102487