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

• Published in: IEEE transactions on smart grid Vol. 14; no. 1; pp. 732 - 745
• Main Authors: Atat, Rachad, Ismail, Muhammad, Serpedin, Erchin
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: and cascading; Benders decomposition; Bending machines; Clustering; Communication; Communication networks; Communications networks; Congestion; constrained clustering; Convergence; Flow stability; Generators; interdependency; Load flow; Load shedding; Optimization; Partitioning; Power flow; Power grids; Power system faults; Power system protection; Power system stability; Risk communication; Smart grid; Subsystems; typed-graphlets
• ISSN: 1949-3053; 1949-3061
• DOI: 10.1109/TSG.2022.3188648

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.