Harmonic identification using parallel neural networks in single-phase systems
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Undergraduate course
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Elsevier B.V.
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Article
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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.
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Keywords
Harmonic distortion, Neural network application, Single-phase power system, Power electronics
Language
English
Citation
Applied Soft Computing. Amsterdam: Elsevier B.V., v. 11, n. 2, p. 2178-2185, 2011.
