Major disasters such as wildfire, tornado, hurricane, tropical storm, and flooding cause disruptions in infrastructure systems such as power and water supply, wastewater management, telecommunication, and transportation facilities. Disruptions in electricity infrastructure have negative impacts on sectors throughout a region, including education, medical services, financial services, and recreation. In this study, we introduced a novel approach to investigate the factors that can be associated with longer restoration time of power service after a hurricane. Considering restoration time as the dependent variable and using a comprehensive set of county-level data, we 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 the 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; and (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 study identified the key factors to predict restoration time of hurricane-induced power outages, allowing disaster management agencies to adopt strategies required for restoration process.

野火、龙卷风、飓风、热带风暴和洪水等重大灾害会导致电力和供水、废水管理、电信和交通设施等基础设施系统中断。电力基础设施中断会对整个地区的各个部门产生负面影响，包括教育、医疗服务、金融服务和娱乐。在这项研究中，我们引入了一种新颖的方法来调查飓风后与较长的电力服务恢复时间相关的因素。将恢复时间作为因变量并使用一组全面的县级数据，我们估计了广义加速失效时间（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。考虑到事件数据的时间相关性的影响后，模型拟合度提高了 12%。以GAFT模型和飓风艾尔玛对佛罗里达州的影响为例，我们研究了：（1）不同类型电力公司（投资者所有的电力公司、农村和市政合作社）之间停电和恢复率的差异；(2)停电持续时间与电力系统变量之间的关系；(3)停电持续时间与社会经济属性之间的关系。这项研究的结果表明，投资者拥有的电力公司为客户提供服务的比例较高且家庭收入中位数较低的县面临停电的时间较长。这项研究确定了预测飓风引起的停电恢复时间的关键因素，使灾害管理机构能够采取恢复过程所需的策略。