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1. A comparative assessment of household power failure coping strategies in three American cities

   https://doi.org/10.1016/j.erss.2024.103573  

   Andresen, Adam X; Kurtz, Liza C; Chakalian, Paul M; Hondula, David M; Meerow, Sara; Gall, Melanie (August 2024, Energy Research & Social Science)

   Household power outage experiences vary based on outage characteristics and the household's ability to cope with a disruption. While disaster management scholarship has produced methods to predict where the most significant impacts of a hazard may occur, these methods do not anticipate secondary effects, such as those from power outages. This research is necessary as the expected risks associated with power outages will increase in the United States due to climate change, increasing electricity demand, and aging infrastructure. To understand households' power outage experiences, we collected 896 surveys from three cities in the United States: Detroit, MI; Miami, FL; and Phoenix, AZ. Participants were recruited through Amazon's Mechanical Turk (MTurk) service to complete a survey. We hypothesized that racial/ethnic minority groups, specifically non-white households and lower-income households experienced more frequent and prolonged power outages. We also hypothesized that the same groups were more likely to have experienced more significant adverse effects, such as throwing away perishable food and not receiving assistance. We found that non-white households in Phoenix and Detroit were more likely to experience longer outages than white households; however, this association was not present in Miami and was not statistically significant in any city. Income was not a major factor in predicting food waste or assistance received during the longest self-reported outage. Further assessments in varying geographical contexts and more generalizable samples are necessary to increase understanding of how households experience power outages. 

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2. Agent-Based Modeling Framework for Simulation of Societal Impacts of Infrastructure Service Disruptions during Disasters

   Esmalian, Amir; Ramaswamy, Maitreyi; Rasoulkhani, Kambiz; Mostafavi, Ali (January 2019, ASCE Computing in Civil Engineering Workshop)

   The objective of this paper is to model and examine the impacts of different levels of infrastructure service losses caused by disasters on the households’ well-being residing in a community. An agent-based simulation model was developed to capture complex mechanisms underlying households’ tolerance for the service outages, including household characteristics (e.g., sociodemographic, social capital, resources, and previous disaster experience), physical infrastructure attributes, and extreme disruptive events. The rules governing these mechanisms were determined using empirical survey data collected from the residents of Harris County affected by Hurricane Harvey as well as the existing models for power outages and service restoration times. The analysis results highlighted the spatial diffusion of service risks among households living in affected areas in disasters. The proposed simulation model will provide utility agencies with an analytical tool for prioritization of infrastructure service restoration actions to effectively mitigate the societal impacts of service losses. 

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3. A socio-technical approach for the assessment of critical infrastructure system vulnerability in extreme weather events

   https://doi.org/10.1038/s41560-023-01315-7  

   Montoya-Rincon, Juan P.; Mejia-Manrique, Said A.; Azad, Shams; Ghandehari, Masoud; Harmsen, Eric W.; Khanbilvardi, Reza; Gonzalez-Cruz, Jorge E. (July 2023, Nature Energy)

   The recurrence of extreme weather events has led to the development of methods for assessing the vulnerability and interdependencies of physical and human systems. A case example is Hurricane Maria (H-Maria), where Puerto Rico experienced damage to 80% of its electrical power system, leading to massive disruptions of essential services for months. Here we evaluate the effectiveness of various interventions aimed at reducing vulnerability by considering power and water infrastructure and respective water–power dependencies while also considering the social vulnerability of affected communities associated with the physical infrastructure upgrades. On the basis of the current infrastructure configuration, we found that all communities suffered enormously from power and water outages. As one upgrade option, we show that incorporating regional energy grids would reduce outages in an H-Maria scenario. However, a large portion of disadvantaged communities will face service disruption under this option. In contrast, hardening transmission lines, as the second option, would improve service delivery and, most importantly, provide uninterrupted service to the higher portion of the vulnerable population. 

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4. Enhanced solar and wind potential during widespread temperature extremes across the U.S. interconnected energy grids

   https://doi.org/10.1088/1748-9326/ad2e72  

   Singh, Deepti; Bekris, Yianna S; Rogers, Cassandra D; Doss-Gollin, James; Coffel, Ethan D; Kalashnikov, Dmitri A (March 2024, Environmental Research Letters)

   Abstract Several recent widespread temperature extremes across the United States (U.S.) have been associated with power outages, disrupting access to electricity at times that are critical for the health and well-being of communities. Building resilience to such extremes in our energy infrastructure needs a comprehensive understanding of their spatial and temporal characteristics. In this study, we systematically quantify the frequency, extent, duration, and intensity of widespread temperature extremes and their associated energy demand in the six North American Electric Reliability Corporation regions using ERA5 reanalysis data. We show that every region has experienced hot or cold extremes that affected nearly their entire extent and such events were associated with substantially higher energy demand, resulting in simultaneous stress across the entire electric gird. The western U.S. experienced significant increases in the frequency (123%), extent (32%), duration (55%) and intensity (29%) of hot extremes and Texas experienced significant increases in the frequency (132%) of hot extremes. The frequency of cold extremes has decreased across most regions without substantial changes in other characteristics. Using power outage data, we show that recent widespread extremes in nearly every region have coincided with power outages, and such outages account for between 12%–52% of all weather-related outages in the past decade depending on the region. Importantly, we find that solar potential is significantly higher during widespread hot extremes in all six regions and during widespread cold extremes in five of the six regions. Further, wind potential is significantly higher during widespread hot or cold extremes in at least three regions. Our findings indicate that increased solar and wind capacity could be leveraged to meet the higher demand for energy during such widespread extremes, improving the resilience and reliability of our energy systems in addition to limiting carbon emissions. 

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5. A Generalized Accelerated Failure Time Model to Predict Restoration Time from Power Outages

   https://doi.org/10.1007/s13753-023-00529-3  

   Jamal, Tasnuba Binte; Hasan, Samiul (December 2023, International Journal of Disaster Risk Science)

   Abstract 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. 

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