Keywords
power outage, restoration time, Generalized Accelerated Failure Time model, hurricanes, investor-owned power companies, median income.
Abstract
Major disasters such as wildfire, tornado, hurricane, tropical storm, flooding cause disruptions in infrastructure systems such as power outage, disruption to water supply system, wastewater management, telecommunication failures, and transportation facilities. Disruptions in electricity infrastructures have negative impacts on sectors throughout a region, including education, medical services, financial, and recreation sectors. In this study, we introduce a novel approach to investigate the factors which can be associated with longer restoration time of power service after a hurricane. Considering restoration time as the dependent variable and utilizing a comprehensive set of county-level data, we have estimated a Generalized Accelerated Failure Time (GAFT) model that accounts for spatial dependence among observations for time to event data. The model fit improved by 12% after considering the effects of spatial correlation in time to event data. Using GAFT model and Hurricane Irma's impact on Florida as a case study, we examined: (1) differences in electric power outages and restoration rates among different types of power companies: investor-owned power companies, rural and municipal cooperatives; (2) the relationship between the duration of power outage and power system variables; (3) the relationship between the duration of power outage and socioeconomic attributes. The findings of this study indicate that counties with a higher percentage of customers served by investor-owned electric companies and lower median household income, faced power outage for a longer time. This paper identifies the key factors to predict restoration time of hurricane-induced power outages, allowing disaster management agencies to adopt strategies required for restoration process.
Completion Date
2023
Semester
Fall
Committee Chair
Hasan, Samiul
Degree
Master of Science in Civil Engineering (M.S.C.E.)
College
College of Engineering and Computer Science
Department
Civil, Environmental, and Construction Engineering
Format
application/pdf
Identifier
DP0028047
URL
https://purls.library.ucf.edu/go/DP0028047
Language
English
Release Date
December 2023
Length of Campus-only Access
None
Access Status
Masters Thesis (Open Access)
Campus Location
Orlando (Main) Campus
STARS Citation
Jamal, Tasnuba Binte, "A Generalized Accelerated Failure Time Model to Predict Restoration Time from Power Outages" (2023). Graduate Thesis and Dissertation 2023-2024. 22.
https://stars.library.ucf.edu/etd2023/22