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

Critical energy infrastructures are increasingly relying on advanced sensing and control technologies for efficient and optimal utilization of flexible energy resources. Algorithmic procedures are needed to ensure that such systems are designed to be resilient to a wide range of cyber-physical adversarial events. This paper provides a robust optimization framework to quantify the range of adversarial perturbations that a system can accommodate without violating pre-specified resiliency metrics. An inner-approximation of the set of adversarial events which can be mitigated by the available flexibility is constructed using an optimization based approach. The proposed algorithm is illustrated on an islanded microgrid example: a modified IEEE 123-node feeder with distributed energy resources. Simulations are carried out to validate that the resiliency metrics are met for any event sampled from the constructed adversarial set for varying levels of available flexibility (energy reserves).
accepted at the IEEE American Control Conference 2022