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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01ng451m121
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dc.contributor.advisorPowell, Warren B.-
dc.contributor.authorGuzzi, Ginevra-
dc.date.accessioned2017-07-19T18:11:10Z-
dc.date.available2017-07-19T18:11:10Z-
dc.date.created2017-04-15-
dc.date.issued2017-4-15-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01ng451m121-
dc.description.abstractThe goal of this study is to develop a feasible, reliable and cost-efficient energy procurement portfolio for Princeton University to enable its campus to achieve net-zero carbon emissions by 2046. Our analysis includes the introduction of solar and wind farms owned by the University in combination with storage systems and a small modular nuclear reactor, creating a diversified energy portfolio. It maintains the connection between the grid and the University and it allows the flow of energy to go in either direction. Throughout the study we focus on achieving high standards of sustainability and reliability, while keeping the system affordable. These criteria are achieved by building a stochastic optimization model that minimizes the cost function associated with the system setup, while satisfying strict requirements for carbon emissions and probability of outage. This model relies partially on deterministic rules and partially on an approximate backward dynamic programming algorithm. We show that achieving carbon neutrality for Princeton University is possible and cost-competitive with the campus’ current energy procurement setup.en_US
dc.language.isoen_USen_US
dc.titleInvestigating a Feasible, Reliable and Cost-Efficient Energy Portfolio In a Net-Zero Carbon Emissions Landscapeen_US
dc.typePrinceton University Senior Theses-
pu.date.classyear2017en_US
pu.departmentOperations Research and Financial Engineeringen_US
pu.pdf.coverpageSeniorThesisCoverPage-
pu.contributor.authorid960863044-
pu.contributor.advisorid010003590-
pu.certificateSustainable Energy Programen_US
Appears in Collections:Operations Research and Financial Engineering, 2000-2020

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