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 has a negative impact on every sector of a region, such as education, medical services, financial, recreation. 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. We consider three types of factors (hazard characteristics, built-environment characteristics, and socio-demographic factors) that might be associated with longer restoration times of power outages during 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) that accounts for spatial dependence among observations for time to event data. Considering spatial correlation in time to event data has improved the model fit by 12%. Using GAFT model and Hurricane Irma 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, and socioeconomic attributes. We have found that factors such as maximum sustained wind speed, percentage of customers facing power outage, percentage of customers served by investor-owned power company, median household income, and number of power plants are strongly associated with restoration time. This paper identifies the key factors in predicting the restoration time of hurricane-induced power outages.

翻译：重大灾害（如山火、龙卷风、飓风、热带风暴、洪水）会引发基础设施系统中断，包括电力中断、供水系统 disruption、废水管理故障、通信失效及交通设施瘫痪。电力基础设施 disruption 对区域各领域（如教育、医疗服务、金融、娱乐）产生负面影响。本研究提出一种新方法，用于探究飓风后电力服务恢复时间较长相关的因素。我们考虑三类可能影响飓风期间电力中断恢复时间的因素（灾害特征、建筑环境特征和社会人口特征）。以恢复时间为因变量，利用全面的县级数据，我们估计了一种广义加速失效时间（GAFT）模型，该模型考虑了事件时间数据观测值之间的空间依赖性。在事件时间数据中纳入空间相关性使模型拟合度提高了12%。以GAFT模型和飓风伊尔玛为案例，我们考察了：（1）不同类型电力公司（投资者所有电力公司、农村和市政合作社）在电力中断和恢复率方面的差异；（2）电力中断时长与电力系统变量及社会经济属性之间的关系。我们发现，最大持续风速、面临电力中断的客户比例、由投资者所有电力公司服务的客户比例、家庭收入中位数及发电厂数量等因素与恢复时间密切相关。本文确定了预测飓风引发电力中断恢复时间的关键因素。