power quality disturbances recognition based on a multiresolution generalized s-transform and a pso-improved decision tree

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ID: 175350
2015
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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.
Reference Key
huang2015energiespower Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Nantian Huang;Shuxin Zhang;Guowei Cai;Dianguo Xu
Journal acs combinatorial science
Year 2015
DOI
10.3390/en8010549
URL
http://www.mdpi.com/1996-1073/8/1/549
Keywords
particle swarm optimization

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