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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Harmonic identification using parallel neural networks in single-phase systems

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Author(s):
do Nascimento, Claudionor Francisco [1] ; de Oliveira, Jr., Azauri Albano [2] ; Goedtel, Alessandro [3] ; Amaral Serni, Paulo Jose [4]
Total Authors: 4
Affiliation:
[1] Fed Univ ABC UFABC, CECS, BR-09210170 Santo Andre, SP - Brazil
[2] Univ Sao Paulo USP, Dept Elect Engn, BR-13566590 Sao Carlos, SP - Brazil
[3] Fed Univ Technol UTFPR, Dept Elect Engn, BR-86300000 Cornelio Procopio, PR - Brazil
[4] Sao Paulo State Univ UNESP, FEB, BR-17033360 Bauru, SP - Brazil
Total Affiliations: 4
Document type: Journal article
Source: APPLIED SOFT COMPUTING; v. 11, n. 2, p. 2178-2185, MAR 2011.
Web of Science Citations: 13
Abstract

In this paper, artificial neural networks are employed in a novel approach to identify harmonic components of single-phase nonlinear load currents, whose amplitude and phase angle are subject to unpredictable changes, even in steady-state. The first six harmonic current components are identified through the variation analysis of waveform characteristics. The effectiveness of this method is tested by applying it to the model of a single-phase active power filter, dedicated to the selective compensation of harmonic current drained by an AC controller. Simulation and experimental results are presented to validate the proposed approach. (C) 2010 Elsevier B. V. All rights reserved. (AU)