Metrics for the resilience of electric infrastructure
Abstract/Contents
- Abstract
- Natural disasters have shaped human history, affecting lives, health, access to water, energy, food, and economic wellbeing. In the United States, natural disasters are becoming increasingly costly. In 2020 alone, disaster events caused $95.0 billion in damages, more than double the 41-year average natural disaster losses of $45.7 billion. Natural hazards are a significant source of electric power disruption as well. The Department of Energy estimates that outages cost the American economy over $150 Billion per year. The electric grid provides many benefits at the personal, business, and societal levels. However, the consequences of power losses can also threaten life from equipment shutoffs, such as medical, communication, air temperature control, or safety control. Among natural disasters, wildfires pose a unique challenge to California where wildfires are not only a threat to its electric infrastructure but are also caused by that same infrastructure. To model the impact of disasters on the grid and to plan for the future of the grid, researchers must be able to assess how grid parameters influence outcomes for society so that the grid can be designed and managed with a minimal impact on human life-safety and the economy. However, a review of the literature on both infrastructure performance metrics and resiliency metrics reveals that there is little consensus on which parameters should be used to optimize the grid for resilience to outages caused by natural disasters. This also means that there are no metrics that would enable the translation of the impact of disasters on the grid to economic impacts. Instead of contributing to this complicated landscape by adding one more proposed resilience metric, the focus herein is to uncover some metrics that can be tracked, measured, and optimized to maximize the resilience of the electrical infrastructure to disasters by minimizing outages experienced by customers. These metrics are the ones that can, hopefully, be controlled in the future, when new grid designs and decisions are made in order to create a more resilient grid. The knowledge of the metrics and how much of a lever they do provide will be critical for future design and investments in the grid.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2022; ©2022 |
| Publication date | 2022; 2022 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Strong, Anne-Laure |
|---|---|
| Degree supervisor | Fischer, Martin, 1960 July 11- |
| Thesis advisor | Fischer, Martin, 1960 July 11- |
| Thesis advisor | Tatum, Clyde |
| Thesis advisor | Zoback, Mary Lou C |
| Degree committee member | Tatum, Clyde |
| Degree committee member | Zoback, Mary Lou C |
| Associated with | Stanford University, Civil & Environmental Engineering Department |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Anne-Laure Strong. |
|---|---|
| Note | Submitted to the Civil & Environmental Engineering Department. |
| Thesis | Thesis Ph.D. Stanford University 2022. |
| Location | https://purl.stanford.edu/vs733pt2819 |
Access conditions
- Copyright
- © 2022 by Anne-Laure Strong
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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