2026-09-18T22:34:35Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1048232022-01-31T17:24:11Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Pablo Dueñas Martinez and José Ignacio Perez Arriaga.
Toregozhina, Aizhan
Technology and Policy Program.
Massachusetts Institute of Technology. Engineering Systems Division
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Technology and Policy Program
n-usn--
2016-10-14T15:54:21Z
2016-10-14T15:54:21Z
2016
2016
http://hdl.handle.net/1721.1/104823
959235027
Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program, 2016.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages [61]-[65]).
According to the Presidential Policy Directive 21, the natural gas and the power systems should be able to recover quickly following a disaster and also be able to anticipate high-impact, low-probability events, rapidly recover, and absorb lessons for adapting its operation and structure for preventing or mitigating the impact of similar events in the future. All of this brings in a growing need for resiliency as the natural gas and electricity systems need to have robust recovery strategies in the face of physical, environmental, cybernetic, security or societal threats. The importance of gas and electricity system resilience increases even further, as the interdependency of the two sectors deepens, especially here in New England, where natural gas now accounts for 50% of region's total power plant capacity. In this thesis, a mixed integer linear programming (MILP) model of integrated gas and electricity system is used to do contingency analysis and determine components of both systems that are critical to improve resilience. The model's main contribution is that it represents gas dynamics accurately. Using this model, we looked at several threats at the junction of gas and electricity systems. Based on the model results, higher line-pack, and pressures, as well as additional compressor capacity investments, were shown to improve system resiliency. The model could be used as a decision support tool for policy-makers to do contingency analysis of gas-electricity systems.
by Aizhan Toregozhina.
S.M. in Technology and Policy
60 pages, 5 unnumbered pages
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Institute for Data, Systems, and Society.
Engineering Systems Division.
Technology and Policy Program.
Resiliency of interdependent gas and electricity systems : the New England case
Thesis
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Publication
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<Abstract>According to the Presidential Policy Directive 21, the natural gas and the power systems should be able to recover quickly following a disaster and also be able to anticipate high-impact, low-probability events, rapidly recover, and absorb lessons for adapting its operation and structure for preventing or mitigating the impact of similar events in the future. All of this brings in a growing need for resiliency as the natural gas and electricity systems need to have robust recovery strategies in the face of physical, environmental, cybernetic, security or societal threats. The importance of gas and electricity system resilience increases even further, as the interdependency of the two sectors deepens, especially here in New England, where natural gas now accounts for 50% of region's total power plant capacity. In this thesis, a mixed integer linear programming (MILP) model of integrated gas and electricity system is used to do contingency analysis and determine components of both systems that are critical to improve resilience. The model's main contribution is that it represents gas dynamics accurately. Using this model, we looked at several threats at the junction of gas and electricity systems. Based on the model results, higher line-pack, and pressures, as well as additional compressor capacity investments, were shown to improve system resiliency. The model could be used as a decision support tool for policy-makers to do contingency analysis of gas-electricity systems.</Abstract>
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