Power system coherency assessment by the affinity propagation algorithm and distance correlation

This paper assesses the coherency in power systems employing affinity propagation (AP) algorithm with different distance metrics and quality measurements. assessment allows determining appropriate metric to cluster a frequency dataset that possesses coherent patterns. Thanks AP method does not require initialization for number of clusters, its convergence characteristics guaranteed by optimization process, capacity using as input, is adopted identify distinguish such patterns embody collective motion an operative area system. The data-driven uses matrix i.e., square computed pairwise distances. Since function significantly impacts resulting clustering, this contribution evaluates three metrics, correlation, results are compared four indexes. data collection constituted set signals representative objects nodes identified center each area. presents experimental simulated added noise real event captured 94 PMUs. We found our proposed strategy achieves highly competitive identifying generator non-generator buses large-scale systems.