Characterising the resilience of electro–hydrogen coupled system via convex hull estimation

Abstract Frequent outbreaks of severe natural disasters underscore the importance of power system resilience. With high efficiency and rapid response, hydrogen energy can enhance power system resilience during such incidents. Traditional post‐event resilience assessment methods, which are event‐triggered, focus on a single indicator, leading to an ambiguous portrayal of the power capacity of coupled systems. To address this limitation, based on a two‐stage electro–hydrogen coupled model, the concept of electro–hydrogen coupled region (EHCR) is proposed to illustrate the potential relationships between resilience indicators, exploring the accurate power capacity of the coupled system to critical loads during extreme events. The convex hull estimation is employed to determine the EHCR. A max–min diagnostic model is introduced as the convergence criterion for resilience margins. An external cutting‐plane algorithm is developed to interactively obtain the EHCR by progressively eliminating non‐capacity regions of the current space based on the diagnostic model. The efficacy of the proposed methods is validated through case studies based on an IEEE 30‐bus and Belgium 20‐node coupled system under ice disaster scenarios.

Authors

Institutions

Publication Details

Journal
Energy Conversion and Economics
Published
2025-02-01
DOI
https://doi.org/10.1049/enc2.70002
Citations
1
Primary Topic
Infrastructure Resilience and Vulnerability Analysis
Type
article
Field-Weighted Citation Impact
0.95

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Characterising the resilience of electro–hydrogen coupled system via convex hull estimation

Gengyin Li, Qiteng Hong, Ming Zhou, Jianxiao Wang et al.
1 citations
Energy Conversion and Economics
Infrastructure Resilience and Vulnerability Analysis
0.95
article

Characterising the resilience of electro–hydrogen coupled system via convex hull estimation

Gengyin Li, Qiteng Hong, Ming Zhou, Jianxiao Wang, Tiance Zhang, S.H. Chang
article en
1 citations

Abstract

Abstract Frequent outbreaks of severe natural disasters underscore the importance of power system resilience. With high efficiency and rapid response, hydrogen energy can enhance power system resilience during such incidents. Traditional post‐event resilience assessment methods, which are event‐triggered, focus on a single indicator, leading to an ambiguous portrayal of the power capacity of coupled systems. To address this limitation, based on a two‐stage electro–hydrogen coupled model, the concept of electro–hydrogen coupled region (EHCR) is proposed to illustrate the potential relationships between resilience indicators, exploring the accurate power capacity of the coupled system to critical loads during extreme events. The convex hull estimation is employed to determine the EHCR. A max–min diagnostic model is introduced as the convergence criterion for resilience margins. An external cutting‐plane algorithm is developed to interactively obtain the EHCR by progressively eliminating non‐capacity regions of the current space based on the diagnostic model. The efficacy of the proposed methods is validated through case studies based on an IEEE 30‐bus and Belgium 20‐node coupled system under ice disaster scenarios.

Energy Conversion and EconomicsVol. 6(1)
North China Electric Power University (CN), University of Strathclyde (GB), Peking University (CN)
China Postdoctoral Science Foundation, Science and Technology Department of Gansu Province, Engineering and Physical Sciences Research Council
Climate action
Openalex Percentile: Top 29%
Infrastructure Resilience and Vulnerability Analysis
0.95
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.