Abstract
Extreme weather events, such as hurricanes, tornadoes, and floods, have caused significant damage to power grid systems, affecting critical infrastructures like substations, transmission lines, and generation plants. This damage often results in widespread power outages in disaster-affected areas, disrupting essential services such as healthcare, transportation, and national security. Annually, these power outage events due to extreme weather lead to economic losses ranging from 25 to 70 billion in the United States [1] ). Analyzing and understanding grid resiliency - particularly the dynamics of power outages under various weather events - is crucial for effective resource planning and maintaining reliable grid operations during such events. In this study, we conducted a preliminary analysis to model grid system resiliency under different extreme weather events across various states.
| Original language | English |
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| Title of host publication | Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024 |
| Editors | Wei Ding, Chang-Tien Lu, Fusheng Wang, Liping Di, Kesheng Wu, Jun Huan, Raghu Nambiar, Jundong Li, Filip Ilievski, Ricardo Baeza-Yates, Xiaohua Hu |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 8849-8851 |
| Number of pages | 3 |
| ISBN (Electronic) | 9798350362480 |
| DOIs | |
| State | Published - 2024 |
| Event | 2024 IEEE International Conference on Big Data, BigData 2024 - Washington, United States Duration: Dec 15 2024 → Dec 18 2024 |
Publication series
| Name | Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024 |
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Conference
| Conference | 2024 IEEE International Conference on Big Data, BigData 2024 |
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| Country/Territory | United States |
| City | Washington |
| Period | 12/15/24 → 12/18/24 |
Funding
This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript or allow others to do so, for US government purposes.
Keywords
- Power outage
- System resiliency
- Time-series forecasting