Limiting the Failure Impact of Interdependent Power-Communication Networks via Optimal Partitioning

The mutual dependency between the power grid and communication network increases the risk of large-scale cascading failure, making the mitigation of outages a difficult task. In this paper, we use the concept of joint partitioning of the power and communication subsystems by identifying the most vulnerable typed-graphlets. This results in higher-order partitions, which prevent cascading failures from propagating globally in the system. For this purpose, we first formulate the problem of partitioning the interdependent system as a large-scale optimization problem with the objective of minimizing the overall load shedding subject to: i) power flow convergence, ii) power stability, iii) partition connectivity, iv) communication congestion/delay control, and v) a high partition quality. Then, using Benders' method, we solve the problem by decomposing it into a relaxed master problem that consists of constrained spectral clustering, and a linear subproblem that consists of minimizing the load shedding subject to power flow convergence, stability, and congestion/delay control. Simulations are conducted on an IEEE 118-bus supported by a 118-node communication network. Our investigations reveal an average of 62% decrease in damage when the system is optimally partitioned.