An adaptive linear combiner for on-line tracking of power system harmonics

Author

Dash, P.K. ; Swain, D.P. ; Liew, A.C. ; Rahman, Saifur

Author_Institution

Dept. of Electr. Eng., Regional Eng. Coll., Rourkela, India

Volume

11

Issue

4

fYear

1996

fDate

11/1/1996 12:00:00 AM

Firstpage

1730

Lastpage

1735

Abstract

The paper presents a new approach for the estimation of harmonic components of a power system using a linear adaptive neuron called Adaline. The learning parameters in the proposed neural estimation algorithm are adjusted to force the error between the actual and desired outputs to satisfy a stable difference error equation. The estimator tracks the Fourier coefficients of the signal data corrupted with noise and decaying DC components very accurately. Adaptive tracking of harmonic components of a power system can easily be done using this algorithm. Several numerical tests have been conducted for the adaptive estimation of harmonic components of power system signals mixed with noise and decaying DC components

Keywords

Fourier transforms; neural nets; parameter estimation; power system analysis computing; power system harmonics; Adaline; Fourier coefficients tracking; adaptive linear combiner; corrupted signal data; decaying DC components; harmonic components estimation; learning parameters; linear adaptive neuron; neural estimation algorithm; on-line tracking; power system harmonics; power system signals; stable difference error equation; Adaptive estimation; Backpropagation algorithms; Difference equations; Frequency estimation; Neural networks; Power engineering and energy; Power harmonic filters; Power system harmonics; System testing; Vectors;

fLanguage

English

Journal_Title

Power Systems, IEEE Transactions on

Publisher

ieee

ISSN

0885-8950

Type

jour

DOI

10.1109/59.544635

Filename

544635