A method for coherency identification based on singular value decomposition

Abstract

A novel method to identify coherent generator groups based on singular value decomposition (SVD) in power system is presented in this paper. Via the SVD algorithm, the high-dimensional real-time rotor-angle data of generators is projected into low-dimensional subspace, and the key characteristic coefficients indicating the information of coherency is obtained. Then, the coherency identification is realized by running k-means clustering algorithm on the coefficients. The dimensionality reduction for clustering algorithm by SVD speeds up the coherency identification. Using the real-time rotor-angle data, the proposed method has the potential to be applied to measured data to implement coherency identification. The effectiveness of this method is demonstrated by the simulation results on IEEE 39-bus system.