Power Restoration Prediction Following Extreme Events and Disasters

Romney B. Duffey

doi:10.1007/s13753-018-0189-2

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Article Navigation > International Journal of Disaster Risk Science > 2019 > 10(1): 134-148

Romney B. Duffey. Power Restoration Prediction Following Extreme Events and Disasters[J]. International Journal of Disaster Risk Science, 2019, 10(1): 134-148. doi: 10.1007/s13753-018-0189-2

Citation:

Romney B. Duffey. Power Restoration Prediction Following Extreme Events and Disasters[J]. International Journal of Disaster Risk Science, 2019, 10(1): 134-148. doi: 10.1007/s13753-018-0189-2

Romney B. Duffey. Power Restoration Prediction Following Extreme Events and Disasters[J]. International Journal of Disaster Risk Science, 2019, 10(1): 134-148. doi: 10.1007/s13753-018-0189-2

Citation:

Romney B. Duffey. Power Restoration Prediction Following Extreme Events and Disasters[J]. International Journal of Disaster Risk Science, 2019, 10(1): 134-148. doi: 10.1007/s13753-018-0189-2

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Power Restoration Prediction Following Extreme Events and Disasters

doi: 10.1007/s13753-018-0189-2

Romney B. Duffey^,

Idaho Falls, ID 83404, USA

Available Online: 2021-04-26

Abstract

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.
- Damage categories,
- Hurricanes,
- Restoration probability,
- Storms,
- Wildfires

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References(35)

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