Classification of Underlying Causes of Power Quality Disturbances: Deterministic versus Statistical Methods. (8th February 2007)

• Record Type: Journal Article
• Authors: Bollen Bollen, Math H. J. Math H. J.; Gu Gu, Irene Y. H. Irene Y. H.; Axelberg Axelberg, Peter G. V. Peter G. V.; Styvaktakis Styvaktakis, Emmanouil Emmanouil
• Other Names: Ribeiro Ribeiro Moisés Vidal Moisés Vidal Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2007(2007)
• Publication Date: 2007-02-08
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2007/79747
• Languages: English
• ISSNs: 1687-6172

Abstract

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.