Harmonic identification using parallel neural networks in single-phase systems

被引：22
|
作者：
do Nascimento, Claudionor Francisco [2 ]
de Oliveira, Azauri Albano, Jr. [3 ]
Goedtel, Alessandro [1 ]
Amaral Serni, Paulo Jose [4 ]
机构：
[1] Fed Univ Technol UTFPR, Dept Elect Engn, BR-86300000 Cornelio Procopio, PR, Brazil
[2] Fed Univ ABC UFABC, CECS, BR-09210170 Santo Andre, SP, Brazil
[3] Univ Sao Paulo, Dept Elect Engn, BR-13566590 Sao Carlos, SP, Brazil
[4] Sao Paulo State Univ UNESP, FEB, BR-17033360 Bauru, SP, Brazil
来源：
APPLIED SOFT COMPUTING | 2011年 / 11卷 / 02期
基金：
巴西圣保罗研究基金会;
关键词：
Harmonic distortion; Neural network application; Single-phase power system; Power electronics; ACTIVE POWER FILTER;
D O I：
10.1016/j.asoc.2010.07.017
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：2178 / 2185
页数：8
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