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Performance Tests of a Support Vector Machine used for Classification of Voltage Disturbances

Peter G.V. Axelberg (Institutionen för signaler och system, Signalbehandling) ; Irene Y.H. Gu (Institutionen för signaler och system, Signalbehandling) ; Math H.J. Bollen
in proc. of 12th International conf. on Harmonics and Quality of Power (ICHQP 2006), Cascais, Portugal, Oct.1-5, 2006 (2006)
[Konferensbidrag, refereegranskat]

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.

Nyckelord: Power distribution, power quality, statistical learning theory, support vector machine, event classification

Denna post skapades 2006-08-25. Senast ändrad 2007-04-11.
CPL Pubid: 22060


Institutioner (Chalmers)

Institutionen för signaler och system, Signalbehandling (1900-2017)



Chalmers infrastruktur