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The purpose of this study is to increase the understanding of power system resilience through pattern recognition of disaster-induced system disruption. This study consists of analyzing power system failure and recovery patterns in a post-extreme event environment to determine relevant pattern characteristics relating to power system resilience. Specifically, the methodology of this study consists of (1) collecting and processing data from power system failures induced by natural disasters categorized by power companies, states, counties, and natural disaster occurrence.; (2) developing failure and recovery curves for the collected data; (3) investigating and establishing statistical distribution models that correlate to the goodness of fit for plotted curves best characterizing the system behaviour for each extreme external occurrence; and (4) creating a quantitative algorithm for specifying the resilience of such engineered systems. The resultant algorithm will assist in answering questions about the resiliency of power systems. Since modern society relies extensively on power systems to survive, this increased insight into power system resilience will provide better situational awareness for stakeholders during future decision-making discussions regarding power system construction.
Primary Advisor's Department
Engineering Management, Systems, and Technology
Stander Symposium, School of Engineering
Institutional Learning Goals
Practical Wisdom; Scholarship
"Analysis of Power System Resilience Subject to Extreme Events" (2023). Stander Symposium Projects. 3204.