TY - JOUR
T1 - Post-disruption performance recovery to enhance resilience of interconnected network systems
AU - Wu, Jiaxin
AU - Wang, Pingfeng
N1 - Funding Information:
This research is partially supported by the National Science Foundation through the Faculty Early Career Development (CAREER) award (CMMI-1813111), and the Institute of Sustainability, Energy and Environment (iSEE) at The University of Illinois at Urbana-Champaign.
Publisher Copyright:
© 2020 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2021
Y1 - 2021
N2 - Mitigating the effect of disruptive events at the operating phase of complex systems therefore improving the systems’ resilience is an important yet challenging task. To improve the resilience, one way is to enhance the failure restoration capability with appropriate performance recovery strategies. However, considering different characteristics of disruptive events, the challenge is to develop a generally applicable framework to optimally coordinate different recovery strategies within a given budget. In order to tackle the challenge, this paper presents a post-disruption recovery framework for networked systems to optimize the performance. In this study, coordination of different recovery agents is achieved by using mathematical programming technique, while the assignment of the required resource for restoration is found by a heuristic algorithm. Case studies based on IEEE test feeders are used to demonstrate the feasibility of the developed framework, as well as the effects of optimal resource allocation nested in the restoration framework.
AB - Mitigating the effect of disruptive events at the operating phase of complex systems therefore improving the systems’ resilience is an important yet challenging task. To improve the resilience, one way is to enhance the failure restoration capability with appropriate performance recovery strategies. However, considering different characteristics of disruptive events, the challenge is to develop a generally applicable framework to optimally coordinate different recovery strategies within a given budget. In order to tackle the challenge, this paper presents a post-disruption recovery framework for networked systems to optimize the performance. In this study, coordination of different recovery agents is achieved by using mathematical programming technique, while the assignment of the required resource for restoration is found by a heuristic algorithm. Case studies based on IEEE test feeders are used to demonstrate the feasibility of the developed framework, as well as the effects of optimal resource allocation nested in the restoration framework.
KW - Resilience
KW - disruption management
KW - networked system
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U2 - 10.1080/23789689.2019.1710073
DO - 10.1080/23789689.2019.1710073
M3 - Article
AN - SCOPUS:85082017188
VL - 6
SP - 107
EP - 123
JO - Sustainable and Resilient Infrastructure
JF - Sustainable and Resilient Infrastructure
SN - 2378-9689
IS - 1-2
ER -