In previous research a novel methodology to assess structural vulnerability was proposed and applied in IEEE test system and high voltage transmission networks of 94 buses, by using graph theory to investigate various risk scenarios that can trigger cascading failures. In this paper, we ratify the application of this methodology in larger networks by applying a case study on the transmission network 230 and 400 kV of Mexico. The events of cascading failures are simulated through two elimination strategies: by deliberate attacks on critical nodes or by random errors. Iterations are performed by running successive N-1 contingencies on a network that is constantly changing its structure with the elimination of each node. The power flows are not necessary and only the calculation of the graph statistical parameter "geodesic vulnerability" is required. This reduces the computation time and leads to a comparative analysis of structural vulnerability.

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In this paper, we evaluate the use of statistical indexes from graph theory as a possible alternative to power-flow techniques for analyzing cascading failures in coupled electric power and natural gas transmission systems. Both methodologies are applied comparatively to coupled IEEE and natural gas test networks. The cascading failure events are simulated through two strategies of network decomposition: Deliberate attacks on highly connected nodes and random faults. The analysis is performed by simulating successive N-k contingencies in a coupled network, where the network structure changes with the elimination of each node. The suitability of graph-theoretic techniques for assessing the vulnerability of interdependent electric power and natural gas infrastructures is demonstrated.

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