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dc.contributor.advisorNewman, Alexandra M.
dc.contributor.authorWales, Jesse G.
dc.contributor.committeememberMehta, Dinesh P.
dc.contributor.committeememberJackson, Gregory
dc.contributor.committeememberFlamand, Tulay
dc.date.accessioned2020-10-19T10:07:36Z
dc.date.available2020-10-19T10:07:36Z
dc.date.issued2020
dc.descriptionIncludes bibliographical references.
dc.description2020 Summer.
dc.description.abstractRenewable energy is a growing industry, and new technologies present unique challenges for both large and small energy systems. Concentrating solar power plants utilize thousands of mirrors to direct sunlight to a collection area to heat a thermal transfer fluid, which can then be stored or used immediately to create electricity with a traditional steam power-generation system. The varying amounts of solar resources force plant operators to cycle the power system on and off and use dispatch strategies that can cause extra wear and tear on the components. In order to improve plant operating strategies, we develop a failure and maintenance simulation model for the power system that is integrated with a mixed-integer program that optimizes the dispatch of electricity. We evaluate several operating strategies in order to maximize profits while accounting for long-term maintenance costs; the strategies we create increase sales by about $3 million over the life of the plant compared to those espoused in prior research. Next, we consider the problem of how best to wash the thousands of mirrors that lose reflectively, and therefore reduce plant efficiency, due to soiling. We formulate a mixed-integer nonlinear program to determine the number and type of wash vehicles to use, accounting for purchase and washing costs and the loss of revenue due to soiling on the mirrors. We develop a decomposition technique to quickly provide solutions that save hundreds of thousands of dollars per year. Other renewable energy systems can be used in commercial buildings, and incorporate combined heat and power, to lower electricity and heating costs, and provide resilience from power outages. We apply a temporal decomposition to improve solve times for a mixed-integer program that determines the best mix and use of renewable technologies in a commercial building. Our methodology enables users to solve the model to an acceptable optimality gap on the order of minutes instead of hours for difficult-to-solve instances.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.identifierWales_mines_0052E_12032.pdf
dc.identifierT 9000
dc.identifier.urihttps://hdl.handle.net/11124/175343
dc.languageEnglish
dc.publisherColorado School of Mines. Arthur Lakes Library
dc.relation.ispartof2020 - Mines Theses & Dissertations
dc.rightsCopyright of the original work is retained by the author.
dc.subjectdecomposition
dc.subjectoptimization
dc.subjectsimulation
dc.subjectmixed-integer programming
dc.subjectconcentrating solar power
dc.subjectrenewable energy
dc.titleImproving renewable energy system design and operations with optimization and simulation
dc.typeText
thesis.degree.disciplineMechanical Engineering
thesis.degree.grantorColorado School of Mines
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)


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