NDLI: Magnitude and phase determination of harmonic currents by adaptive learning back-propagation neural network

Content Provider	IEEE Xplore Digital Library
Author	Rukonuzzaman, M. Nakaoka, M.
Copyright Year	1999
Description	Author affiliation: Graduate Sch. of Sci & Eng., Yamaguchi Univ., Japan (Rukonuzzaman, M.)
Abstract	Harmonic currents are significant and inevitable when power electronic installations are used in industry and telecommunication energy plants. In order to compensate the instantaneous harmonic current components by active power filtering technique, it is a prerequisite to estimate the magnitude and phase of each harmonic component in real time. In this paper, a promethean approach is proposed for the determination of magnitude and phase of each current harmonic component from the distorted line currents. This approach introduces an adaptive learning multi-layer backpropagation neural network which converges faster than simple back-propagation neural network. Unlike conventional methods of harmonic current determination, this method requires only half cycle of the distorted current waves. This method is four times faster than the conventional method and this makes the on-line determination of instantaneous harmonic components.
Starting Page	1168
Ending Page	1173
File Size	384771
Page Count	6
File Format	PDF
ISBN	0780357698
DOI	10.1109/PEDS.1999.792874
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-07-27
Publisher Place	Hong Kong
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Power harmonic filters Power system harmonics Harmonic distortion Neural networks Multi-layer neural network Power electronics Communication industry Electronics industry Active filters Phase estimation
Content Type	Text
Resource Type	Article

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