Dataset for: Electric Vulnerability Index: Targeted Energy Storage Implementation Metric

Kerby, Jessica; Tarekegne, Bethel W; Miller, Lee Matthew

doi:10.25584/2569841

Title: Dataset for: Electric Vulnerability Index: Targeted Energy Storage Implementation Metric

Dataset
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Abstract

Uninterrupted access to electricity is critical to the safety and security of American households. More frequent and extreme emergency events increase outages across the country, disproportionately impacting vulnerable communities that experience the most frequent and longest outages, are most sensitive to the loss of electric power, and have the least capacity to adapt to these conditions. This study devises a metric, the Electric Vulnerability Index (EVI), and validates this metric against the 2021 Winter Storm Uri in Texas. Though not ubiquitous, similar trends were observed between adjacent areas with higher EVI and those with higher outage rates from this storm. EVI is offered as a viable approach to quantify a population’s vulnerability to electric outages and maps that index across the continental United States to aid policymakers, advocates, and energy system stakeholders in the targeted deployment of resilience solutions, such as energy storage, to communities most in need. This dataset includes the geopackage file containing all relevant attributes used to generate the maps used in the accompanying paper.

Authors:

;

; Miller, Lee Matthew

Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Publication Date:: Mon Jun 02 00:00:00 EDT 2025

DOE Contract Number:: AC05-76RL01830

Research Org.:: PNNL (PNNL2)

Sponsoring Org.:: USDOE Office of Electricity (OE)

Collaborations:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

OSTI Identifier:: 2569841

DOI:: https://doi.org/10.25584/2569841

Citation Formats


                    Kerby, Jessica, Tarekegne, Bethel W, and Miller, Lee Matthew. Dataset for: Electric Vulnerability Index: Targeted Energy Storage Implementation Metric.  United States: N. p., 2025. 
        Web.  doi:10.25584/2569841.

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                    Kerby, Jessica, Tarekegne, Bethel W, & Miller, Lee Matthew. Dataset for: Electric Vulnerability Index: Targeted Energy Storage Implementation Metric.  United States.  doi:https://doi.org/10.25584/2569841

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                    Kerby, Jessica, Tarekegne, Bethel W, and Miller, Lee Matthew. 2025.  
"Dataset for: Electric Vulnerability Index: Targeted Energy Storage Implementation Metric".  United States.  doi:https://doi.org/10.25584/2569841.  https://www.osti.gov/servlets/purl/2569841. Pub date:Mon Jun 02 00:00:00 EDT 2025

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@article{osti_2569841,

  title        = {Dataset for: Electric Vulnerability Index: Targeted Energy Storage Implementation Metric},

  author       = {Kerby, Jessica and Tarekegne, Bethel W and Miller, Lee Matthew},

  abstractNote = {Uninterrupted access to electricity is critical to the safety and security of American households. More frequent and extreme emergency events increase outages across the country, disproportionately impacting vulnerable communities that experience the most frequent and longest outages, are most sensitive to the loss of electric power, and have the least capacity to adapt to these conditions. This study devises a metric, the Electric Vulnerability Index (EVI), and validates this metric against the 2021 Winter Storm Uri in Texas. Though not ubiquitous, similar trends were observed between adjacent areas with higher EVI and those with higher outage rates from this storm. EVI is offered as a viable approach to quantify a population’s vulnerability to electric outages and maps that index across the continental United States to aid policymakers, advocates, and energy system stakeholders in the targeted deployment of resilience solutions, such as energy storage, to communities most in need. This dataset includes the geopackage file containing all relevant attributes used to generate the maps used in the accompanying paper.},

  doi          = {10.25584/2569841},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Mon Jun 02 00:00:00 EDT 2025},

  month        = {Mon Jun 02 00:00:00 EDT 2025}

}

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DOI: https://doi.org/10.25584/2569841

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