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Performance Tests of a Support Vector Machine used for Classification of Voltage Disturbances
University of Borås, School of Engineering. [external].
2006 (English)Conference paper, Published paper (Refereed)
Abstract [en]

This paper proposes a novel method for classifying voltage disturbances in electric power systems by using the Support Vector Machine (SVM) method. The proposed SVM classifier is designed to classify five common types of voltage disturbances and experiments have been conducted on recorded disturbances with good classification results. The proposed SVM classifier is also shown to be robust in terms of using training data and testing data that originate from two different power networks.

Place, publisher, year, edition, pages
2006.
Keywords [en]
Power distribution, power quality, statistical learning theory, support vector machine, event classification, Resursåtervinning
National Category
Engineering and Technology
Research subject
Resource Recovery
Identifiers
URN: urn:nbn:se:hb:diva-8241Local ID: 2320/13161OAI: oai:DiVA.org:hb-8241DiVA, id: diva2:889124
Conference
proc. of 12th International conf. on Harmonics and Quality of Power (ICHQP 2006), Cascais, Portugal, Oct.1-5, 2006
Available from: 2015-12-22 Created: 2015-12-22 Last updated: 2017-02-02Bibliographically approved

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Axelberg, Peter G.V.

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