Critical Machine Identification for Power Systems Transient Stability Problems using Data Mining

DIEGO ECHEVERRÍA; JAIME CEPEDA; D. GRACIELA COLOMÉ

Congreso; Transmission & Distribution Conference and Exposition - Latin America (PES T&D-LA), 2014 IEEE PES; 2014

IEEE PES Colombia

This paper presents a new methodology based on data mining to identify the cluster of critical machines, i.e. the machines responsible for the loss of synchronization in a power system after the occurrence of a disturbance. Since only the postfault trajectory is required, the proposed method is independent of system modeling and could be extended for multi-swing stability assessment. Numerical results obtained by applying the approach on the New England test system demonstrates the feasibility and effectiveness that could be achieved in identifying the critical machines, which is also of great value for assessing transient stability problems and defining suitable emergency control actions.