Quantifying system-level dependencies between connected electricity and transport infrastructure networks incorporating expert judgement. Issue 3 (3rd July 2021)

• Record Type: Journal Article
• Authors: Zorn, Conrad; Pant, Raghav; Thacker, Scott; Andreae, Lea; Shamseldin, Asaad Y.
• Is Part Of: Civil engineering and environmental systems. Volume 38:Issue 3(2021)
• Page Start: 176
• Page End: 196
• Publication Date: 2021-07-03
• Subjects: Vulnerability assessment -- networks -- interdependency -- electricity network -- transportation -- expert-elicitation; Civil engineering -- Periodicals; 628.092
• DOI: 10.1080/10286608.2021.1943664
• Languages: English
• ISSNs: 1028-6608

Abstract

ABSTRACT: Critical infrastructure systems are typically managed as isolated systems, however, past events have demonstrated that disruptions to electricity supply can initiate major social and economic impacts on dependent infrastructure. This paper investigates the role of electricity on the functioning of the New Zealand national passenger–transportation sectors, namely: airports, ferries, rail, and petroleum distribution via state highways. Expert-elicited relationships used to define electricity-transport dependencies in practice are compared and updated using a national-scale network-of-networks simulation model – a methodology with the advantage of capturing a far greater range of possible dependency relationships compared to a single expert-elicited curve. Examining the geographic and functional dependence on the electricity transmission/distribution networks, critical substations for normal transportation sector functionality are identified. Through simulating disruptive scenarios, we derive a synthesised set of curves integrating the qualitative and quantitative approaches to characterising infrastructure dependencies. While urban areas show dense co-location of transport assets and critical substations with significant potential for disrupting transportation, the routing of petroleum from bulk storage terminals to retail stations reveal the criticality of road networks beyond simple traffic count metrics. This approach in modelling infrastructure dependencies at the national scale is not without limitations and these are reflected on accordingly.