Enhancing Power Grid Resilience: A Novel Labeling System for Assessing Climate Vulnerabilities in US Substations

Power grids are essential infrastructure networks composed of components including transformers, circuit breakers, and substations, which guarantee the reliable delivery of electricity throughout the world. Climate change poses significant risks to these systems through factors, such as increased flood risk and extreme weather events. To address the vulnerability of power grids to these climate impacts, our study develops an innovative system for labeling the components of power substations, enabling a detailed analysis of their exposure to external stressors. Our research catalogs over 1300 substations across the United States using this labeling system. In our ongoing research, we aim to use our comprehensive database and intersect it with tropical storm data under various climate scenarios, creating visual representations of our hazard analysis. These visualizations will highlight the specific vulnerabilities within the power grid when exposed to different storm conditions, allowing for precise simulations of their performance during extreme weather events. Additionally, our ongoing research aims to provide deeper insights into the long-term degradation and economic costs associated with these impacts. Initial results demonstrate the potential of our approach to enhance the predictive accuracy of climate impact models on power infrastructure. The findings for our study prove to be significant, offering critical information that can inform future strategies to bolster the resilience of the US power grid against climate-related challenges, ensuring the reliability and stability of electricity delivery for all across the globe.

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Publication Details

Journal
George Mason University
Published
2024-10-11
DOI
https://doi.org/10.13021/jssr2024.4289
Primary Topic
Prenatal Screening and Diagnostics
Type
article
Field-Weighted Citation Impact
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article

Enhancing Power Grid Resilience: A Novel Labeling System for Assessing Climate Vulnerabilities in US Substations

George Mason University
Prenatal Screening and Diagnostics
article

Enhancing Power Grid Resilience: A Novel Labeling System for Assessing Climate Vulnerabilities in US Substations

article en

Abstract

Power grids are essential infrastructure networks composed of components including transformers, circuit breakers, and substations, which guarantee the reliable delivery of electricity throughout the world. Climate change poses significant risks to these systems through factors, such as increased flood risk and extreme weather events. To address the vulnerability of power grids to these climate impacts, our study develops an innovative system for labeling the components of power substations, enabling a detailed analysis of their exposure to external stressors. Our research catalogs over 1300 substations across the United States using this labeling system. In our ongoing research, we aim to use our comprehensive database and intersect it with tropical storm data under various climate scenarios, creating visual representations of our hazard analysis. These visualizations will highlight the specific vulnerabilities within the power grid when exposed to different storm conditions, allowing for precise simulations of their performance during extreme weather events. Additionally, our ongoing research aims to provide deeper insights into the long-term degradation and economic costs associated with these impacts. Initial results demonstrate the potential of our approach to enhance the predictive accuracy of climate impact models on power infrastructure. The findings for our study prove to be significant, offering critical information that can inform future strategies to bolster the resilience of the US power grid against climate-related challenges, ensuring the reliability and stability of electricity delivery for all across the globe.

George Mason University
George Mason University (US)
Climate action
Openalex Percentile: Top 27%
Prenatal Screening and Diagnostics
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