Power Restoration Prediction Following Extreme Events and Disasters

Abstract This article examines electric power restoration following catastrophic damage in modern cities and regions due to extreme events and disasters. Recovery time and non-restoration probability are derived using new data from a comprehensive range of recent massive hurricanes, extensive wildfi...

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Main Author: Romney B. Duffey
Format: Article
Language:English
Published: SpringerOpen 2018-10-01
Series:International Journal of Disaster Risk Science
Subjects:
Online Access:http://link.springer.com/article/10.1007/s13753-018-0189-2
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author Romney B. Duffey
author_facet Romney B. Duffey
author_sort Romney B. Duffey
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description Abstract This article examines electric power restoration following catastrophic damage in modern cities and regions due to extreme events and disasters. Recovery time and non-restoration probability are derived using new data from a comprehensive range of recent massive hurricanes, extensive wildfires, severe snowstorms, and damaging cyclones. Despite their totally disparate origins, over three orders of magnitude severe wildfires and hurricanes have the same non-restoration probability trends, which are of simple exponential form. The results fall into categories that are dependent on and grouped by the degree of damage and social disruption. The implications are discussed for emergency response planning. These new results demonstrate that the scientific laws of probability and human learning, which dominate risk in modern technologies and societies are also applicable to a wide range of disasters and extreme events.
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spelling doaj.art-14c2401461f046baa990dfd5c3a9eecb2022-12-21T23:43:41ZengSpringerOpenInternational Journal of Disaster Risk Science2095-00552192-63952018-10-0110113414810.1007/s13753-018-0189-2Power Restoration Prediction Following Extreme Events and DisastersRomney B. DuffeyAbstract This article examines electric power restoration following catastrophic damage in modern cities and regions due to extreme events and disasters. Recovery time and non-restoration probability are derived using new data from a comprehensive range of recent massive hurricanes, extensive wildfires, severe snowstorms, and damaging cyclones. Despite their totally disparate origins, over three orders of magnitude severe wildfires and hurricanes have the same non-restoration probability trends, which are of simple exponential form. The results fall into categories that are dependent on and grouped by the degree of damage and social disruption. The implications are discussed for emergency response planning. These new results demonstrate that the scientific laws of probability and human learning, which dominate risk in modern technologies and societies are also applicable to a wide range of disasters and extreme events.http://link.springer.com/article/10.1007/s13753-018-0189-2Damage categoriesHurricanesRestoration probabilityStormsWildfires
spellingShingle Romney B. Duffey
Power Restoration Prediction Following Extreme Events and Disasters
International Journal of Disaster Risk Science
Damage categories
Hurricanes
Restoration probability
Storms
Wildfires
title Power Restoration Prediction Following Extreme Events and Disasters
title_full Power Restoration Prediction Following Extreme Events and Disasters
title_fullStr Power Restoration Prediction Following Extreme Events and Disasters
title_full_unstemmed Power Restoration Prediction Following Extreme Events and Disasters
title_short Power Restoration Prediction Following Extreme Events and Disasters
title_sort power restoration prediction following extreme events and disasters
topic Damage categories
Hurricanes
Restoration probability
Storms
Wildfires
url http://link.springer.com/article/10.1007/s13753-018-0189-2
work_keys_str_mv AT romneybduffey powerrestorationpredictionfollowingextremeeventsanddisasters