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Massachusetts Institute of Technology

Understanding Correlated Threats to Department of Defense Energy Systems

Abstract

dc:description.abstract

Climate change poses an existential threat to the United States military’s energy systems. We researched current trends in energy, economics, and weather, translating those trends into quantifiable threats to the military’s secondary power systems. We also assembled a data set about secondary power systems on domestic U.S. military bases. Because that data set was missing critical information, we formulated and then evaluated an imputation method to complete the data set. This imputation method successfully predicted expected cost for the missing installation data. We ran simulations using our quantified trends and data set on existing software to predict the effects of those trends on certain U.S. military bases. Ultimately, we identified threats that could potentially cost 150 million dollars and cause more than a week of additional electrical downtime for those select bases.

Degree

thesis:*
Name thesis:degree_name
Master
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2021

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Adams Goffinet, Katherine
Advisor dc:contributor.advisor
  • Roozbehani, Mardavij

Rights

dc:rights
Statement dc:rights
  • In Copyright - Educational Use Permitted
  • Copyright MIT

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/139375
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/139375

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Adams Goffinet, Katherine. Understanding Correlated Threats to Department of Defense Energy Systems. Massachusetts Institute of Technology, 2021. https://hdl.handle.net/1721.1/139375