Maximum Lyapunov Exponent Based Nearest Neighbor Algorithm For Real-Time Transient Stability Assessment

In power systems, ensuring transient stability is paramount to prevent unforeseen blackouts and power failures. Transient stability assessment is crucial for the early detection and mitigation of instabilities, providing a rapid response to severe fault situations. The concept of the maximum Lyapunov exponent facilitates fast predictions for transient stability assessment after severe disturbances. This paper introduces an efficient maximum Lyapunov exponent algorithm for online transient stability assessment, representing the primary contribution of this work. This approach uses the time series data from the rotor angles of generators or the phase angles of generator terminal buses. Case studies are conducted on the Nordic Power System, with simulations performed in DigSilent PowerFactory. This study contributes by offering insights into the performance and adaptability of the proposed algorithm. •Enhancing transient stability assessment with MLE based nearest neighbor algorithm.•Model independent approach for real-time data utilization.•Versatility in input signal for comprehensive analysis.