Adedayo Joshua Aruwajoye


Presentation: 10:45-12:00, Kennedy Union Ballroom



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This study aims 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 in statistical terms. Specifically, the methodology of this progressive 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 a distribution model that correlates to the goodness of fit for plotted curves best characterizing the system behavior for each extreme external occurrence, and (4) creating an algorithm for specifying the resilience of such engineered systems. This study will then explore the resultant algorithm in modelling and answering questions about the resiliency of power systems subjected to some extreme events first, opening extensions to other kinds of natural disasters in the future. 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.

Publication Date


Project Designation

Independent Research

Primary Advisor

Henry D. Lester

Primary Advisor's Department

Engineering Management, Systems, and Technology


Stander Symposium, School of Engineering

Institutional Learning Goals

Practical Wisdom

Analysis of Power System Resilience Subject to Extreme Events