Do topological models provide good information about vulnerability in electric power networks?

TL;DR

This study assesses whether topological graph models accurately reflect vulnerability in electric power networks by comparing topological metrics with cascading failure models across various attack scenarios.

Contribution

It provides an empirical evaluation of the effectiveness of topological measures in predicting power network vulnerability, highlighting their limitations.

Findings

Directed attacks cause larger failures than random failures.

Topological metrics only mildly correlate with actual blackout sizes.

Purely topological vulnerability metrics can be misleading.

Abstract

In order to identify the extent to which results from topological graph models are useful for modeling vulnerability in electricity infrastructure, we measure the susceptibility of power networks to random failures and directed attacks using three measures of vulnerability: characteristic path lengths, connectivity loss and blackout sizes. The first two are purely topological metrics. The blackout size calculation results from a model of cascading failure in power networks. Testing the response of 40 areas within the Eastern US power grid and a standard IEEE test case to a variety of attack/failure vectors indicates that directed attacks result in larger failures using all three vulnerability measures, but the attack vectors that appear to cause the most damage depend on the measure chosen. While our topological and power grid model results show some trends that are similar, there is only a mild correlation between the vulnerability measures for individual simulations. We conclude that evaluating vulnerability in power networks using purely topological metrics can be misleading.