Qssi: A new similarity index for qualitative time series. Application to classify voltage sags

Abstract

This work is focused on defining and implementing a new similarity criterion for sequences of symbolic representations. The proposed algorithm returns a normalized index related to the degree of matching between sequences of qualitative labels. Performance of this method has been tested in the classification of voltage sags (transient reduction of voltage magnitude) gathered at 25kV distribution substations. The objective is to assist monitoring systems in locating the origin of such disturbances in the transmission (HV) or distribution (MV) system. The promising classification accuracy achieved when this method was used with test data suggests that the presented algorithm could be applied satisfactorily and confirms its utility in classification approaches. Copyright © 2011 Taylor & Francis Group, LLC.