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Exploring cascading outages and weather via processing historic data
Hawaii International Conference on System Sciences 2018 (HICSS-51)
  • Ian Dobson, Iowa State University
  • Nichelle'Le Carrington, Iowa State University
  • Kai Zhou, Iowa State University
  • Zhaoyu Wang, Iowa State University
  • Benjamin Carreras, BACV solutions Inc.
  • Jose Reynolds-Barredo, Universidad Carlos III de Madrid
Location
Hilton Waikoloa Village, Hawaii
Event Website
http://hicss.hawaii.edu/
Start Date
1-3-2018
End Date
1-6-2018
Description

We describe some bulk statistics of historical initial line outages and the implications for forming contingency lists and understanding which initial outages are likely to lead to further cascading. We use historical outage data to estimate the effect of weather on cascading via cause codes and via NOAA storm data. Bad weather significantly increases outage rates and interacts with cascading effects, and should be accounted for in cascading models and simulations. We suggest how weather effects can be incorporated into the OPA cascading simulation and validated. There are very good prospects for improving data processing and models for the bulk statistics of historical outage data so that cascading can be better understood and quantified.

Citation Information
Ian Dobson, Nichelle'Le Carrington, Kai Zhou, Zhaoyu Wang, et al.. "Exploring cascading outages and weather via processing historic data" (2018)
Available at: http://works.bepress.com/ian-dobson/27/