4.6 Article

A Study on the Association of Socioeconomic and Physical Cofactors Contributing to Power Restoration After Hurricane Maria

期刊

IEEE ACCESS
卷 9, 期 -, 页码 98654-98664

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2021.3093547

关键词

Hurricanes; Resilience; Computational modeling; Sociology; Power system reliability; Power generation; Image restoration; Extreme weather; hurricane Maria; nighttime lights; power recovery; power infrastructure; quasi-Poisson regression; resiliency; VIIRS

资金

  1. NYU Tandon School of Engineering

向作者/读者索取更多资源

The study revealed that the electric power infrastructure in Puerto Rico suffered severe damage from Hurricane Maria, resulting in a lengthy recovery process. Areas closer to the hurricane's landfall location had longer recovery times, while road connectivity and landslide impacts influenced the speed of restoration. Additionally, financially disadvantaged areas experienced more prolonged outages.
The electric power infrastructure in Puerto Rico suffered substantial damage as Hurricane Maria crossed the island on September 20, 2017. Despite significant efforts made by authorities, it took almost a year to achieve near-complete power recovery. In this study, we used spaceborne daily nighttime lights (NTL) imagery as a surrogate measure of power loss and restoration. We quantified the spatial and temporal extent of loss of electric power and trends in gradual recovery at the 889 county subdivisions for over eight months and computed days without service at the above tabulation areas. We formulated a Quasi-Poisson regression model to identify the association of the features from physical and socioeconomic domains with the power recovery effort. According to the model, the recovery time extended for areas closer to the landfall location of the hurricane, with every 50-kilometer increase in distance from the landfall corresponding to 30% fewer days without power (95% CI = 26% - 33%). Road connectivity was a major issue for the restoration effort, areas having a direct connection with hi-speed roads recovered more quickly with 7% fewer outage days (95% CI = 1% - 13%). The areas which were affected by moderate landslide needed 5.5% (95% CI = 1% - 10%), and high landslide areas needed 11.4% (95% CI = 2% - 21%) more days to recover. Financially disadvantaged areas suffered more from the extended outage. For every 10% increase in population below the poverty line, there was a 2% increase in recovery time (95% CI = 0.3% - 2.8%).

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