Steady-State Cascading Failure Model With Voltage Instability Event Detection

This study proposes a cascading failure model for power systems that addresses event-triggered power flow divergence. After a cascading failure event, voltage instability is a major cause of event-triggered power flow divergence. To detect voltage instability events, we track the steady-state voltage profiles across successive cascade generations by adopting continuation power flow (CPF). Various cascading failure events are incorporated into the CPF computation. Hence, the proposed model can identify voltage instability by monitoring the emergence of buses that hit a saddle-node bifurcation (SNB) point. In this way, the proposed cascading failure model is able to derive equilibrium points, if they exist, under all conditions. Furthermore, the model incorporates primary frequency control instead of slack buses to account for power losses, thereby improving the accuracy of the results. In addition, we propose a set of metrics to measure the cascading failure propagation rate and the influence of voltage instability events on cascading failure outcomes. Experimental results indicate that power system configurations exert a significant influence on voltage instability events.