JOURNAL ARTICLE

Estimation of Power System Harmonic Using Modified Normalized Least Mean Square

Abstract

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).

Keywords:
Estimator Harmonic Least mean squares filter Mathematics Control theory (sociology) Adaptive estimator Power (physics) Harmonic mean Stochastic gradient descent Tracking (education) Gradient descent Algorithm Adaptive filter Computer science Statistics Artificial neural network Artificial intelligence Acoustics Physics

Metrics

2
Cited By
0.40
FWCI (Field Weighted Citation Impact)
6
Refs
0.65
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Adaptive Filtering Techniques
Physical Sciences →  Engineering →  Computational Mechanics
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Power Quality and Harmonics
Physical Sciences →  Engineering →  Electrical and Electronic Engineering

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