Real-time critical machine identification for online transient stability analysis

Critical machine identification is of primary importance for online transient stability analysis and emergency control. In this paper, a novel real-time critical cluster identification scheme using WAMS information is proposed. First, the candidate clustering modes are obtained by the relative big angle gaps. Second, choose the clustering mode which gets the maximum equal angle after single-machine transform as the correct cluster mode which can be used to analyze the transient stability. The scheme has the advantage of little computation, fast identification speed and high accuracy according to the simulation results on IEEE standard 39-bus 10-unit system.