Robustness Assessment of Hetero-Functional Graph Theory Based Model of Interdependent Urban Utility Networks

TL;DR

This paper introduces a weighted hetero-functional graph theory framework for modeling interdependent urban utility networks and assesses their robustness against various attack scenarios, providing new metrics for comprehensive evaluation.

Contribution

It develops a novel weighted HFGT model for integrated infrastructure networks and proposes robustness metrics, advancing the analysis of system vulnerability and resilience.

Findings

Weighted HFGT effectively captures resource dependencies.

Network robustness improves with better information security.

Vulnerability varies with attack type and scenario.

Abstract

The increasing urban population imposes a substantial and growing burden on the supporting infrastructure, such as electricity, water, heating, natural gas, road transportation, etc. This paper presents a Hetero-functional graph theory (HFGT) based modeling framework for these integrated infrastructures followed by an analysis of network robustness. The supporting infrastructures along with the infrastructure repair facilities are considered. In contrast to conventional graph representations, a weighted HFGT model is used to capture the system processes and mutual dependencies among resources. To assess robustness of the inter-dependent networks, impacts of complete/partial and random/targeted attacks are quantified. Specifically, various contingency scenarios are simulated and the vulnerability of the network is evaluated. Additionally, several robustness metrics are proposed to provide a comprehensive evaluation of system robustness. The proposed weighted HFGT modeling and robustness assessment approach is tested using a synthetic interdependent network, comprising of an electrical power system, a water network, a district heating network, a natural gas system and a road transportation network. Results demonstrate that system robustness can be enhanced via securing system information and mitigating attack strength.