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

TL;DR

This paper introduces a robust optimization framework to quantify and verify the resiliency of microgrids against cyber-physical adversarial events, ensuring system stability under various perturbations.

Contribution

It develops an optimization-based method to characterize the maximal set of adversarial events that a microgrid can withstand without violating resiliency metrics.

Findings

The framework successfully identifies the adversarial set in a microgrid example.

Simulations confirm the system maintains resiliency metrics under sampled adversarial events.

The approach adapts to different levels of energy reserves and flexibility.

Abstract

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).