Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/44429
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Type: | Journal article |
Title: | Investigation of effective automatic recognition systems of power-quality events |
Author: | Gargoom, A. Ertugrul, N. Soong, W. |
Citation: | IEEE Transactions on Power Delivery, 2007; 22(4):2319-2326 |
Publisher: | IEEE-Inst Electrical Electronics Engineers Inc |
Issue Date: | 2007 |
ISSN: | 0885-8977 1937-4208 |
Statement of Responsibility: | Gargoom, A.M.; Ertugrul, N.; Soong, W.L. |
Abstract: | There is a need to analyze power-quality (PQ) signals and to extract their distinctive features to take preventative actions in power systems. This paper offers an effective solution to automatically classify PQ signals using Hilbert and Clarke Transforms as new feature extraction techniques. Both techniques accommodate Nearest Neighbor Technique for automatic recognition of PQ events. The Hilbert transform is introduced as single-phase monitoring technique, while with the Clarke Transformation all the three-phases can be monitored simultaneously. The performance of each technique is compared with the most recent techniques (S-Transform and Wavelet Transform) using an extensive number of simulated PQ events that are divided into nine classes. In addition, the paper investigates the optimum selection of number of neighbors to minimize the classification errors in Nearest Neighbor Technique. |
Description: | Copyright © 2007 IEEE. All Rights Reserved. |
DOI: | 10.1109/TPWRD.2007.905424 |
Published version: | http://dx.doi.org/10.1109/tpwrd.2007.905424 |
Appears in Collections: | Aurora harvest 6 Electrical and Electronic Engineering publications Environment Institute publications |
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hdl_44429.pdf | 906.08 kB | Publisher's PDF | View/Open |
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