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Improving critical infrastructure resilience with application to power distribution networks

University of British Columbia

Our modern societies are dependent on the functioning of infrastructure systems that support economic prosperity and quality of life. These infrastructure systems face an increasingly set of threats, natural or man-made disasters, that can cause significant physical, economic, and social disruptions. Recent extreme events have shown that total protection can not be accomplished. Therefore, Critical Infrastructure Protection strategies should focus not only on the prevention of these events but also on the response and recovery following them. This shift is realized by the concept of infrastructure resilience. In this thesis, we address the problem of assessing and improving infrastructure resilience. The contributions of this thesis focus on modelling, simulation, and optimization of infrastructure systems with respect to their resilience to extreme events. We first develop a resilience assessment framework for interdependent infrastructure systems. The developed framework provides a quantitative means to assess infrastructure resilience by introducing a generalized resilience index. To account for the inherent complexity due to infrastructure interdependencies, we use the i2Sim framework for modelling and simulating the studied infrastructure. The resilience improvement problem is formulated using the proposed resilience index as a resources allocation optimization problem. The problem aims at finding the best allocation of available resources such as power and water to mitigate the consequences of a disaster. Two solutions algorithm are proposed to solve the problem: the first one uses a simulation-optimization approach based on the Ordinal Optimization theory, and the second one uses a Linear Programming formulation. Results of both algorithms show that infrastructure resilience can be greatly improved by efficient allocations of available resources. In addition, a prioritization methodology is developed to assess decision makers to direct resilience investment to the most important components in the infrastructure. Finally, an optimal power distribution network reconfiguration algorithm is developed to complement the two resources allocation algorithms by solving the technical feasibility problem of the power distribution network. A heuristic computationally inexpensive optimization algorithm is developed based on Graph theory for solving this problem. The proposed algorithms are tested using different test cases and promising results are achieved.

Text

2016-10-22

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/59533

Electrical and Computer Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/