Signal processing techniques for sensing based generator coherency analysis

In this paper generator coherency analysis of power system is investigated via some signal processing techniques. Sensor data analysis here designed is based on the fusion of advanced signal processing techniques for sensing-based coherency identification, including k-means and fuzzy k-means clustering, agglomerative hierarchical cluster tree, and Independent Component Analysis (ICA). Detailed results are presented and discussed in order to prove the effectiveness of the techniques and carry out a comparative assessment.