Power Systems Transient Stability Indices: Hierarchical Clustering Based Detection of Coherent Groups Of Generators

In power system stability analysis, the identification of coherent groups of generators, i.e., machines with strongly correlated rotor angles, holds significant importance. This study presents a real-time methodology that employs hierarchical clustering techniques to assess the level of coherence among generators using the synchronization coefficient and the correlation coefficient of the generator's rotor angle as indicators of coherency. Additionally, the study utilizes Power Transient Stability Indices (PTSI) to investigate the dynamic response of the power system. The method incorporates power system transient Stability indices, including the Power Connectivity Factor (CF) index, which highlights the generators exhibiting strong coherence within groups, the Power Separation Factor (SF) index, which reveals the extent to which generators in different groups tend to deviate from one another in the event of a disturbance, and the overall system separation index, demonstrating the system's overall separation status (CF/SF). To validate the approach, extensive assessments were conducted using an IEEE-39 test system featuring a fully dynamic model. The simulation results presented in this paper underscore the effectiveness of the proposed methodology.