Identification of power system dynamic signature using hierarchical clustering

This paper applies Hierarchical Clustering to identify the dynamic signature of power system, within database of post-disturbance system responses obtained by Monte Carlo simulation. Two different approaches are proposed to cut off the dendrogram so that generators can be grouped based on the similarity of their rotor angle behavior for a large number of contingencies automatically. The application of the method is illustrated on a 16-machine, 68-bus test system. Hierarchical Clustering provides accurate results in terms of generator grouping. 8 patterns of system responses are identified from the database. This work can be used to label the training data in the problem of on-line prediction of dynamic signature.