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Open Access

Classification of Underlying Causes of Power Quality Disturbances: Deterministic versus Statistical Methods

  • Math H.J. Bollen1, 2Email author,
  • Irene Y.H. Gu3,
  • Peter G.V. Axelberg3 and
  • Emmanouil Styvaktakis4
EURASIP Journal on Advances in Signal Processing20072007:079747

https://doi.org/10.1155/2007/79747

Received: 30 April 2006

Accepted: 15 November 2006

Published: 8 February 2007

Abstract

This paper presents the two main types of classification methods for power quality disturbances based on underlying causes: deterministic classification, giving an expert system as an example, and statistical classification, with support vector machines (a novel method) as an example. An expert system is suitable when one has limited amount of data and sufficient power system expert knowledge; however, its application requires a set of threshold values. Statistical methods are suitable when large amount of data is available for training. Two important issues to guarantee the effectiveness of a classifier, data segmentation, and feature extraction are discussed. Segmentation of a sequence of data recording is preprocessing to partition the data into segments each representing a duration containing either an event or a transition between two events. Extraction of features is applied to each segment individually. Some useful features and their effectiveness are then discussed. Some experimental results are included for demonstrating the effectiveness of both systems. Finally, conclusions are given together with the discussion of some future research directions.

Keywords

Support Vector MachineStatistical MethodInformation TechnologySupport VectorFeature Extraction

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Authors’ Affiliations

(1)
STRI AB, Ludvika, Sweden
(2)
EMC-on-Site, Luleå University of Technology, Skellefteå, Sweden
(3)
Department of Signals and Systems, Chalmers University of Technology, Gothenburg, Sweden
(4)
The Hellenic Transmission System Operator, Athens, Greece

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Copyright

© Bollen et al. 2007

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