Estimation of Power System Harmonic Using Modified Normalized Least Mean Square

A new adaptive power system harmonic estimator is presented, which is competent of tracking power system harmonic components. The proposed estimator technique is based on the normalized Least Mean Square (LMS), which is a stochastic gradient descent algorithm. The learning method of the proposed est...

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Bibliographic Details
Published inApplied Mechanics and Materials Vol. 785; no. Recent Trends in Power Engineering; pp. 378 - 382
Main Authors Nor, N.M., Abdullah, M.F., Alhaj, H.M.M., Ibrahim, T., Asirvadam, Vijanth S.
Format Journal Article
LanguageEnglish
Published Zurich Trans Tech Publications Ltd 01.08.2015
Subjects
Algorithms
Estimators
Harmonics
Learning
Least mean squares
Least mean squares algorithm
Recursive
Tracking
ADALINE
Harmonic Estimation
R-NLMS
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Summary:A new adaptive power system harmonic estimator is presented, which is competent of tracking power system harmonic components. The proposed estimator technique is based on the normalized Least Mean Square (LMS), which is a stochastic gradient descent algorithm. The learning method of the proposed estimator is based upon the recursive estimate of the signal power, and is faster tracking of harmonic components as compared to the introduced Adaptive Linear Element (ADALINE).
Bibliography:Selected, peer reviewed papers from the 2015 9th International Power Engineering and Optimization Conference (PEOCO 2015), March 18-19, 2015, Melaka, Malaysia
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ISBN:9783038355120
3038355127
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.785.378