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dc.contributor.advisorR. Scott Kemp.en_US
dc.contributor.authorBiegel, Kathryn Een_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Nuclear Science and Engineering.en_US
dc.date.accessioned2016-07-18T20:03:34Z
dc.date.available2016-07-18T20:03:34Z
dc.date.issued2015en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/103714
dc.descriptionThesis: S.B., Massachusetts Institute of Technology, Department of Nuclear Science and Engineering, 2015.en_US
dc.description"June 2015." Cataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 44-47).en_US
dc.description.abstractIn historical and current experience, the economics of nuclear power have proven to be problematic for utility companies. Construction costs and schedules have proven to be highly unpredictable, with the average reactor construction project costing two to three times more than its initial budget and taking almost twice as long to complete as expected. The causes of this phenomenon have not been well-characterized, even two decades after the last new reactor was brought online in 1996. Scenario generation can provide useful information about the economic viability of nuclear construction projects over a variety of parameter spaces without having to make prescriptive assertions about likely single values for delay and other difficult-to-predict parameters. The MEERKAT model creates scenarios over two different reactor types (Westinghouse AP1000 and NuScale SMR plant); three delay cases (optimistic, median, and pessimistic based on historical data); and six different utility company credit ratings (which translate into varying costs of capital). MEERKAT outputs the levelized cost of electricity (LCOE) for each scenario and compares them to average electricity prices for a number of regions in the United States. These scenarios produce levelized costs of electricity (LCOEs) that are not competitive in a deregulated market in any case, and which may be competitive in regulated markets under certain optimistic conditions. If the AP1000 is considered as more credit-stressful than the SMR project, the SMR becomes more competitive with the AP1000, but the projects' viability in the wider market remains unchanged. However, in general terms the smaller up-front cost of the SMR makes it a more feasible endeavor for a wider variety of utility companies, increasing the potential customer base for nuclear power generation units.en_US
dc.description.statementofresponsibilityby Kathryn E. Biegel.en_US
dc.format.extent47 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.subjectNuclear Science and Engineering.en_US
dc.titleScenario modeling for feasibility assessment of nuclear power plant construction projectsen_US
dc.typeThesisen_US
dc.description.degreeS.B.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Nuclear Science and Engineering.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Nuclear Science and Engineering
dc.identifier.oclc953292042en_US


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