Comprehensive approach for prediction and assessment of power system transient stability in real-time

Secure operation of power systems is receiving a renewed interest due to considerable structural changes and greater uncertainties. Thus, motivated by implementation of wide-area measurement systems in power systems worldwide, recent research work is being devoted to the development of enhanced tools for fast security assessment within reduced time frames. The work presented in this paper introduces an approach that exploits the post-disturbance data acquired via phasor measurement units (PMUs) by using a finite difference based method for the prediction of rotor angles, data-mining-based clustering for identification of critical machines, and single-machine-infinite bus (SMIB) transformation to evaluate the system transient stability in terms of unstable margin and time to instability. Numerical results obtained by applying the approach on the New England test system demonstrates the feasibility and effectiveness that could be achieved in predicting the critical machines and unstable conditions, which is also of great value for defining suitable emergency control actions.