Harmonic estimation in a power system using adaptive perceptrons

Author

Dash, P.K. ; Swain, D.P. ; Routray, A. ; Liew, A.C.

Author_Institution

Dept. of Electr. Eng., Nat. Univ. of Singapore, Singapore

Volume

143

Issue

6

fYear

1996

fDate

11/1/1996 12:00:00 AM

Firstpage

565

Lastpage

574

Abstract

The paper presents an adaptive neural network approach to the estimation of the harmonic components of a power system. The neural estimator is based on the use of an adaptive perceptron comprising a linear adaptive neuron called Adaline. The learning parameters in the proposed 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 performed 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. Data from a laboratory test is used to validate the performance of this new approach

Keywords

adaptive estimation; difference equations; perceptrons; power system analysis computing; power system harmonics; Adaline; Fourier coefficients; adaptive neural network; adaptive perceptrons; algorithm; decaying DC components; difference error equation; harmonic estimation; learning parameters; linear adaptive neuron; performance; power system harmonic components; power system signals; signal noise;

fLanguage

English

Journal_Title

Generation, Transmission and Distribution, IEE Proceedings-

Publisher

iet

ISSN

1350-2360

Type

jour

DOI

10.1049/ip-gtd:19960464

Filename

556744