Quantifying Power System Resilience Improvement Through Network Reconfiguration In Cases Of Extreme Emergencies
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Electricity grid complexity together with a diversity of critical infrastructures (CIs), such as generating units, transportation network, etc., are increasingly evolving into a complicated network that is vulnerable to unpredictable hazards. Disruptive events, whether they are natural catastrophes like floods, hurricanes, thunderstorms, etc., or malicious cyber-attacks or even human-caused faults, may have significant impacts on such real-time complex power networks composed of numerous interconnected structural and functional components. In these emergency scenarios, some part of the electric power plant may adversely be affected, which puts the power network in an unstable condition due to loss of some components. The question is how to restore the system performance to its normal working condition and thus, improve the resiliency of the system. This thesis proposes a temporary restoration plan in response to the forecasted High Impact Low Probability (HILP) events, in which utilizes the current network infrastructure with the goal of enhancing the power system resilience in cases of such extreme emergencies. Two types of metrics are provided to quantify the system resilience followed by the proposed restoration plan. The presented framework helps the system operators to evaluate the outage recovery options considering their impacts on system resilience and decide on the final restoration plan for implementation. The proposed approach has been tested and verified through the IEEE 118-bus test system facing with HILP events, and the results reveal its applicability and efficiency.