• DocumentCode
    31904
  • Title

    Predicting Hurricane Power Outages to Support Storm Response Planning

  • Author

    Guikema, Seth David ; Nateghi, Roshanak ; Quiring, Steven M. ; Staid, Andrea ; Reilly, Allison C. ; Gao, Ming-Liang

  • Author_Institution
    Johns Hopkins Univ., Baltimore, MD, USA
  • Volume
    2
  • fYear
    2014
  • fDate
    2014
  • Firstpage
    1364
  • Lastpage
    1373
  • Abstract
    Hurricanes regularly cause widespread and prolonged power outages along the U.S. coastline. These power outages have significant impacts on other infrastructure dependent on electric power and on the population living in the impacted area. Efficient and effective emergency response planning within power utilities, other utilities dependent on electric power, private companies, and local, state, and federal government agencies benefit from accurate estimates of the extent and spatial distribution of power outages in advance of an approaching hurricane. A number of models have been developed for predicting power outages in advance of a hurricane, but these have been specific to a given utility service area, limiting their use to support wider emergency response planning. In this paper, we describe the development of a hurricane power outage prediction model applicable along the full U.S. coastline using only publicly available data, we demonstrate the use of the model for Hurricane Sandy, and we use the model to estimate what the impacts of a number of historic storms, including Typhoon Haiyan, would be on current U.S. energy infrastructure.
  • Keywords
    emergency services; power system faults; power system planning; storms; Hurricane Sandy; Typhoon Haiyan; emergency response planning; hurricane power outage prediction model; storm response planning; utility service area; Contingency planning; Emergency services; Hurricanes; Power outages; Power system restoration; Predictive models; Storms; Hurricane; hurricane; outage model; outage prediction; storm response planning;
  • fLanguage
    English
  • Journal_Title
    Access, IEEE
  • Publisher
    ieee
  • ISSN
    2169-3536
  • Type

    jour

  • DOI
    10.1109/ACCESS.2014.2365716
  • Filename
    6949604