NDLI: Automating natural disaster impact analysis: An open resource to visually estimate a hurricane's impact on the electric grid

Content Provider	IEEE Xplore Digital Library
Author	Barker, A.M. Freer, E.B. Omitaomu, O.A. Fernandez, S.J. Chinthavali, S. Kodysh, J.B.
Copyright Year	2013
Description	Author affiliation: Oak Ridge Nat. Lab., Oak Ridge, TN, USA (Barker, A.M.; Freer, E.B.; Omitaomu, O.A.; Fernandez, S.J.; Chinthavali, S.; Kodysh, J.B.)
Abstract	An ORNL team working on the Energy Awareness and Resiliency Standardized Services (EARSS) project developed a fully automated procedure to take wind speed and location estimates provided by hurricane forecasters and provide a geospatial estimate on the impact to the electric grid in terms of outage areas and projected duration of outages. Hurricane Sandy was one of the worst US storms ever, with reported injuries and deaths, millions of people without power for several days, and billions of dollars in economic impact. Hurricane advisories were released for Sandy from October 22 through 31, 2012. The fact that the geoprocessing was automated was significant - there were 64 advisories for Sandy. Manual analysis typically takes about one hour for each advisory. During a storm event, advisories are released every two to three hours around the clock, and an analyst capable of performing the manual analysis has other tasks they would like to focus on. Initial predictions of a big impact and landfall usually occur three days in advance, so time is of the essence to prepare for utility repair. Automated processing developed at ORNL allowed this analysis to be completed and made publicly available within minutes of each new advisory being released.
Starting Page	1
Ending Page	3
File Size	612021
Page Count	3
File Format	PDF
ISBN	9781479900527
ISSN	1558058X
e-ISBN	9781479900534
DOI	10.1109/SECON.2013.6567495
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-04-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hurricanes Wind speed Substations Storms Government Manuals Real-time systems Python Hurricane Electric Grid EARSS
Content Type	Text
Resource Type	Article

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