title: Time-dependent resilience assessment and improvement of urban infrastructure systems.
abstract: This paper introduces an approach to assess and improve the time-dependent resilience of urban infrastructure systems, where resilience is defined as the systems' ability to resist various possible hazards, absorb the initial damage from hazards, and recover to normal operation one or multiple times during a time period T. For different values of T and its position relative to current time, there are three forms of resilience: previous resilience, current potential resilience, and future potential resilience. This paper mainly discusses the third form that takes into account the systems' future evolving processes. Taking the power transmission grid in Harris County, Texas, USA as an example, the time-dependent features of resilience and the effectiveness of some resilience-inspired strategies, including enhancement of situational awareness, management of consumer demand, and integration of distributed generators, are all simulated and discussed. Results show a nonlinear nature of resilience as a function of T, which may exhibit a transition from an increasing function to a decreasing function at either a threshold of post-blackout improvement rate, a threshold of load profile with consumer demand management, or a threshold number of integrated distributed generators. These results are further confirmed by studying a typical benchmark system such as the IEEE RTS-96. Such common trends indicate that some resilience strategies may enhance infrastructure system resilience in the short term, but if not managed well, they may compromise practical utility system resilience in the long run.
authors.affiliation: Department of Control Science and Engineering, Image Processing and Intelligent Control Key Laboratory of the Education Ministry of China, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China. min.ouyang@hust.edu.cn
authors.forename: Min
authors.initials: M
authors.lastname: Ouyang
authors.forename: Leonardo
authors.initials: L
authors.lastname: Dueñas-Osorio