Modeling, Simulation, and Mitigation of Cascading Failures in Power Systems

Among various power system disturbances, cascading failures are considered the most serious and extreme threats to grid operations, potentially leading to significant stability issues or even widespread power blackouts. The intricate mechanism of cascading failures, characterized by multi-timescale dynamics, presents exceptional challenges for their modeling, simulation, and mitigation.

First, this work proposes an energy function-embedded quasi-steady-state model for efficient simulation of cascading failures on a power grid while addressing transient stability concerns. Compared to quasi-steady-state models, the proposed model incorporates short-term dynamic simulation and an energy function method to efficiently evaluate the transient stability of a power grid together with outage propagation without transient stability simulation.

Second, since interaction graphs on cascading failures provide valuable insights into how cascading failures evolve and propagate, this work studies the sensitivity of the interaction graphs to the system’s loading conditions, suggesting the need to choose an appropriate interaction graph for more effective mitigation strategies against cascading failures under different loading conditions.

Third, this work proposes a transient stability-incorporated interaction graph. This graph statistically quantifies the interactions among line outages and instabilities of generators. Compared with an interaction graph that only models line outages, this new interaction graph provides important insights on how transient instability occurs along with cascading failures.

Fourth, to better quantify interactions between component failures, this work proposes a stochastic interaction graph. Different types of modes on failure propagations are defined and characterized by the eigenvalues of a stochastic interaction matrix. Finding and interpreting these modes helps identify the probable patterns of failure propagation. Then, by lowering the failure probabilities of critical components highly participating in a mode of widespread failures, cascading can be mitigated.

Finally, a framework for a cascading failure simulation and analysis platform, which integrates various simulation models and analysis tools, is designed to support the platform’s future development.