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Critical energy infrastructures are increasingly relying on advanced sensingand control technologies for efficient and optimal utilization of flexibleenergy resources. Algorithmic procedures are needed to ensure that such systemsare designed to be resilient to a wide range of cyber-physical adversarialevents. This paper provides a robust optimization framework to quantify therange of adversarial perturbations that a system can accommodate withoutviolating pre-specified resiliency metrics. An inner-approximation of the setof adversarial events which can be mitigated by the available flexibility isconstructed using an optimization based approach. The proposed algorithm isillustrated on an islanded microgrid example: a modified IEEE 123-node feederwith distributed energy resources. Simulations are carried out to validate thatthe resiliency metrics are met for any event sampled from the constructedadversarial set for varying levels of available flexibility (energy reserves).

Optimization-Based Resiliency Verification in Microgrids via Maximal Adversarial Set Characterization