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Cited by 473

The DOI matches its Crossref record; 101 of the 101 references it cites were found in a registry or an index.

State-of-the-art review on power grid resilience to extreme weather events: Definitions, frameworks, quantitative assessment methodologies, and enhancement strategies

Jufri, Fauzan Hanif, Widiputra, Victor, Jung, Jaesung·2019·Applied Energy

Abstract

Abstract The rise of power outages caused by extreme weather events and the frequency of extreme weather events has motivated the study of grid resilience. This paper presents a state-of-the-art review of existing research on the study of grid resilience, which focuses on the point of view of power system engineering with respect to extreme weather events. Firstly, it investigates confounding terminologies used in the study of grid resilience, such as the definitions, the differences with grid reliability, the extreme weather events, and their extreme impact on the power systems. Secondly, it presents a grid resilience framework as a general provision to understand the subjects in the study of grid resilience. Thirdly, it describes several methodologies of grid resilience assessment and some quantitative indices. Finally, various grid resilience enhancement strategies implementations are discussed.

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Metadata

Authors
Jufri, F. H., Widiputra, V., & Jung, J.
Venue
Applied Energy
Publisher
Elsevier BV
Published
2019-04
Volume
239
Pages
1049-1065
ISSN
0306-2619 (ISSN-L)
OpenAlex
W2913820977
Cited by
473
References
101
FWCI
35.88
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: State-of-the-art review on power grid resilience to extreme weather events: Definitions, frameworks, quantitative assessment methodologies, and enhancement strategies. https://app.cochat.ai/papers/10.1016/j.apenergy.2019.02.017
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Jufri, F. H., Widiputra, V., & Jung, J. (2019). State-of-the-art review on power grid resilience to extreme weather events: Definitions, frameworks, quantitative assessment methodologies, and enhancement strategies. Applied Energy. https://doi.org/10.1016/j.apenergy.2019.02.017

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.