Feasibility Study of Applicability of Recurrence Quantification Analysis for Clustering of Power System Dynamic Responses

A methodology based on Recurrence Quantification Analysis (RQA) for the clustering of generator dynamic behavior is presented. RQA is a nonlinear data analysis method, which is used in this paper to extract features from measured generator rotor angle responses that can be used to cluster generators in groups with similar oscillatory behavior. The possibility of extracting features relevant to damping and frequency of oscillations present in power systems is studied. The k-Means clustering algorithm is further used to cluster the generator responses in groups exhibiting well or poorly damped oscillations, based on the extracted features from RQA. The effectiveness of RQA is investigated using simulated responses from a modified version of the IEEE 68 bus network, including renewable energy resources.