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Power outage prediction for natural hazards using synthetic power distribution systems
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“They can be very accurate in aggregate for types of disruptions that are frequent and already have a long historic record [74].”
From Energy system resilience – A review (2021) · cites this paper as [74]
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Research works printed but not linked: 38
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Cited by
Sorted by citations
Energy system resilience – A review
Jasiūnas, J., Lund, P. D., & Mikkola, J. (2021) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2021.111476 · Cited by 412
“They can be very accurate in aggregate for types of disruptions that are frequent and already have a long historic record [74].”
Background
Metadata
- Authors
- Zhai, C., Chen, T. Y.-J., White, A. G., & Guikema, S. D.
- Affiliations
- University of Michigan (US)
- Corresponding author
- Zhai, Chengwei
- Venue
- Reliability Engineering & System Safety
- Publisher
- Elsevier BV
- Published
- 2021-04
- Volume
- 208
- Pages
- 107348
- ISSN
- 0951-8320 (ISSN-L)
- OpenAlex
- W3108081744
- Cited by
- 64
- References
- 0
- Citations by year
- 2026: 8 · 2025: 14 · 2024: 16 · 2023: 8 · 2022: 12 · 2021: 6
- FWCI
- 3.80
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Reliability Engineering & System Safety (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- One Concern, Inc.
- Topics
- Physical Sciences › Engineering › Civil and Structural Engineering › Infrastructure Resilience and Vulnerability Analysis
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Power System Reliability and Maintenance
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
- Keywords
- power outage prediction, natural hazards, fragility curves, power system reliability
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