Resilience Modeling of Interdependent Traffic-Electric Power System Subject to Hurricanes
Publication: Journal of Infrastructure Systems
Volume 26, Issue 1
Abstract
Highly interconnected critical infrastructure systems (CISs) are the backbone of the well-being of the modern societies. It is crucial to account for the interdependencies among CISs in assessing the community resilience. This study presents a framework for resilience assessment of an interdependent traffic-electric power system subject to hurricanes. The traffic and electric power systems are both characterized using the flow-based mathematical representation, and three types of interdependency are captured. A modeling procedure coupled with the Monte Carlo simulation is presented to assess the resilience of both systems and to integrate different improvement strategies into corresponding stages of resilience. The traffic and electric power systems in Centerville, considering three improvement strategies, are studied to demonstrate the proposed framework. The results show that interdependencies can significantly affect the resilience of both systems, leading to different and the most effective strategies for each system. While hardening hurricane-vulnerable components and adopting a better repair schedule, both improve resilience of the electric power system significantly; adopting a better repair schedule works best for the resilience of the traffic system. The equal repair mode can achieve the resilience improvement in a balanced fashion. The results also highlight the importance of repair scheduling to the resilience improvement of these two interdependent systems when the available recovery resources are limited. Due to the interdependencies, the faster the functionality of traffic system can recover, the more efficiently the repair activities can be conducted, and thus, the greater resilience of both systems can be achieved.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available from the corresponding author by request, including the configurations of the transportation and electric power networks; and the results of the illustrative example (i.e., data for Figs. 5–9 and Tables 5 and 6).
Acknowledgments
The authors gratefully acknowledge the support of this research by the Center for Risk-Based Community Resilience sponsored by the National Institute of Standards and Technology (NIST) (Award No. 70NANB15H044). Any opinions, findings, and conclusions expressed in this material are those of the investigators and do not necessarily reflect the views of the sponsor. And the authors also wish to thank the reviewers for careful review of the manuscript and constructive comments that helped to improve the paper.
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Journal of Infrastructure Systems
Volume 26 • Issue 1 • March 2020
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©2019 American Society of Civil Engineers.
History
Received: Apr 17, 2018
Accepted: Jul 29, 2019
Published online: Dec 17, 2019
Published in print: Mar 1, 2020
Discussion open until: May 17, 2020
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