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Energies 2015, 8(1), 549-572; doi:10.3390/en8010549

Power Quality Disturbances Recognition Based on a Multiresolution Generalized S-Transform and a PSO-Improved Decision Tree

1
School of Electrical Engineering, Northeast Dianli University, Jilin 132012, China
2
Department of Electrical Engineering, Harbin Institute of Technology, Harbin 150001, China
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Josep M. Guerrero
Received: 30 September 2014 / Accepted: 7 January 2015 / Published: 15 January 2015
(This article belongs to the Special Issue Microgrids)
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Abstract

In a microgrid, the distributed generators (DG) can power the user loads directly. As a result, power quality (PQ) events are more likely to affect the users. This paper proposes a Multiresolution Generalized S-transform (MGST) approach to improve the ability of analyzing and monitoring the power quality in a microgrid. Firstly, the time-frequency distribution characteristics of different types of disturbances are analyzed. Based on the characteristics, the frequency domain is segmented into three frequency areas. After that, the width factor of the window function in the S-transform is set in different frequency areas. MGST has different time-frequency resolution in each frequency area to satisfy the recognition requirements of different disturbances in each frequency area. Then, a rule-based decision tree classifier is designed. In addition, particle swarm optimization (PSO) is applied to extract the applicable features. Finally, the proposed method is compared with some others. The simulation experiments show that the new approach has better accuracy and noise immunity. View Full-Text
Keywords: power quality disturbances; S-transform; multiresolution; particle swarm optimization; decision tree power quality disturbances; S-transform; multiresolution; particle swarm optimization; decision tree
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Huang, N.; Zhang, S.; Cai, G.; Xu, D. Power Quality Disturbances Recognition Based on a Multiresolution Generalized S-Transform and a PSO-Improved Decision Tree. Energies 2015, 8, 549-572.

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