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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Portante, Edgar C. Folga, Stephen F. Kavicky, James A. Malone, Leah Talaber |
| Copyright Year | 2014 |
| Description | Author affiliation: Argonne National Laboratory, 9700 South Cass Avenue, IL 60432, USA (Portante, Edgar C.; Folga, Stephen F.; Kavicky, James A.; Malone, Leah Talaber) |
| Abstract | The development of predictive tools for emergency management has recently become a subject of major consideration among emergency responders, especially at the federal level. Often the news of an impending high-consequence threat causes significant stress on these agencies because of their inability to apprise management of probable impacts with sufficient certainty. This paper documents Argonne National Laboratory's effort to demonstrate the predictive capability of its newly enhanced tool called EPfast in estimating the impacts of postulated events on our power system. Specifically, the study focuses on EPfast's ability to estimate power outage areas resulting from random system contingencies. The San Diego September 8, 2011, blackout that affected most of southern California was selected for simulation using EPfast. Results showed agreement with actual reported impacts in both spatial and quantitative terms. The method, assumptions, and data used are presented here, and results showing their potential application to emergency planning are discussed. |
| Starting Page | 1527 |
| Ending Page | 1538 |
| File Size | 1476272 |
| Page Count | 12 |
| File Format | |
| e-ISBN | 9781479974863 |
| DOI | 10.1109/WSC.2014.7020005 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-12-07 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Generators Power system faults Schedules Power system protection Data models Storage area networks Laboratories |
| Content Type | Text |
| Resource Type | Article |
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