Technical Papers
Oct 28, 2015

Efficient Resilience Assessment Framework for Electric Power Systems Affected by Hurricane Events

Publication: Journal of Structural Engineering
Volume 142, Issue 8

Abstract

Ensuring electric power system resilience against natural and anthropogenic hazards is vital for public health, economy, security, and well-being across modern societies. This paper presents a resilience assessment framework that focuses on computationally efficient algorithms for quantifying the response of electric power systems to hurricane events, while demonstrating its applicability to large real systems by spanning hazards, structural and system responses, and restoration processes. The study models the transmission system responses as a Bayesian network to represent probabilistic dependencies in an intuitive and tractable manner. It propagates hurricane-induced failures throughout the system to service customers while efficiently considering the physics and constraints of power flow. The framework computes customer outages in distributed 1-km2 blocks connected by radial distribution feeders across the entire system, and simulates system restoration according to resource mobilization practices and a range of prioritization sequences. An illustration example using the electric power grid of Harris County, Texas, under Hurricane Ike in 2008 shows that the framework yields system responses that are in good agreement with actual outages reported after the event. It also shows that the framework requires only a fraction (2.3%) of the computation time needed by a previous outage assessment model. The example also illustrates how a resilience-informed restoration strategy can significantly improve the system-level functionality, particularly in the aftermath of hurricane events. The framework provides an efficient tool for exploring a wide range of what-if scenarios in large real systems, and supports practical use by citizens and city officials for rapid recovery and high resilience attainment.

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Acknowledgments

This research has been partly funded by the Department of Civil and Environmental Engineering at Rice University, the Office of Public Safety and Homeland Security of the City of Houston under Grant 2008-CP-T8-0023, National Science Foundation (NSF) through award CMMI 1436845, and the U.S. Department of Defense through its Army Research Office via MURI grant W911NF-13-1-0340. The authors appreciate the support from these institutions towards resiliency research.

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Information & Authors

Information

Published In

Go to Journal of Structural Engineering
Journal of Structural Engineering
Volume 142Issue 8August 2016

History

Received: Jun 27, 2014
Accepted: Aug 21, 2015
Published online: Oct 28, 2015
Discussion open until: Mar 28, 2016
Published in print: Aug 1, 2016

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Authors

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Akwasi F. Mensah, Ph.D., S.M.ASCE [email protected]
Modeler, Model Development, Risk Management Solutions (RMS), 7575 Gateway Blvd., Newark, CA 94560 (corresponding author). E-mail: [email protected]
Leonardo Dueñas-Osorio, Ph.D., A.M.ASCE [email protected]
Associate Professor, Dept. of Civil and Environmental Engineering, Rice Univ., 6100 Main St., MS-318, Houston, TX 77005. E-mail: [email protected]

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