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dc.contributor.advisorAnuradha M. Annaswamy.en_US
dc.contributor.authorJenkins, Sandra Elizabethen_US
dc.contributor.otherMassachusetts Institute of Technology. Technology and Policy Program.en_US
dc.coverage.spatialn-us---en_US
dc.date.accessioned2014-09-19T21:36:56Z
dc.date.available2014-09-19T21:36:56Z
dc.date.copyright2014en_US
dc.date.issued2014en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/90053
dc.descriptionThesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2014.en_US
dc.description81en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 73-81).en_US
dc.description.abstractDue to high storage costs and limited storage availability, natural gas is generally used as a just-in- time resource that needs to be delivered as it is consumed. With the shale gas revolution, coal retirements and environmental regulations, the interdependency of natural gas and electricity has increased. These changes impact pipeline financing and power generation dispatch. Potential solutions to gas-electricity interdependency challenges such as mismatched market schedules are not too difficult to determine. However, a quantitative model is needed in order to evaluate these solutions in order to provide insights into which solutions to interdependency concerns offer the best outcomes. While it is clear that natural gas constraints will affect the cost of the electricity system, there is a need for modeling to explore the relationship between fuel uncertainty and system cost. In this thesis, a quantitative optimal flow model with a dynamic market mechanism is used to measure the effects of natural gas-fired power producer's fuel uncertainty on the net social benefit to consumers and producers. Modeling results indicate that fuel price uncertainty negatively affects social welfare while demand response, information availability and coordination improvements limit the impact of natural gas fuel uncertainty. To simulate improved coordination, a second model is developed which includes natural gas network constraints. The results of this model demonstrate how joint optimization of the networks could relax fuel constraints on gas-fired generators and improve social welfare.en_US
dc.description.statementofresponsibilityby Sandra Elizabeth Jenkins.en_US
dc.format.extent81 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectEngineering Systems Division.en_US
dc.subjectTechnology and Policy Program.en_US
dc.titleInterdependency of electricity and natural gas markets in the United States : a dynamic computational modelen_US
dc.typeThesisen_US
dc.description.degreeS.M. in Technology and Policyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division
dc.contributor.departmentTechnology and Policy Program
dc.identifier.oclc890140357en_US


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