Identification of the critical cluster of generators by during fault angle trajectory estimation for transient stability analysis

Decades ago, limitations in computing power led to the creation of fast direct stability analysis (TSA) methods. Driven by the increasing complexity of power systems and the escalation of critical scenarios, these methods are in demand once again. The identification of the critical cluster (CC) of generators is a prerequisite for direct transient stability analysis techniques, such as the extended equal area criterion. Current research in CC identification prioritizes the use of real-time data or time-domain simulations. While promising, these methodologies do not align with the minimal data requirements of direct TSA methods. This paper proposes a straightforward method to identify potentially
critical generators with low data requirements. The method is based on Taylor series expansion of generator angles to identify the ones exhibiting the most significant angle deviations during sustained fault conditions. Extensive simulations on the French
network strongly support the idea and confirm the improvement achieved by the proposed methodology.