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dc.contributor.advisorChristian Kampmann.en_US
dc.contributor.authorMendes Barlach, Leonardoen_US
dc.contributor.otherSystem Design and Management Program.en_US
dc.date.accessioned2017-10-30T15:30:00Z
dc.date.available2017-10-30T15:30:00Z
dc.date.copyright2017en_US
dc.date.issued2017en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/112066
dc.descriptionThesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, School of Engineering, System Design and Management Program, 2017.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (page 56).en_US
dc.description.abstractRenewable energy is one of the most important technologies for decarbonizing the economy and fighting climate change. In recent years, wind energy has become cheaper and more widely adopted. However, the variable nature of wind production creates unique challenges that are not faced by conventional thermal technologies. Several studies to date have showed the decrease in economic value of wind energy as penetration increases due to this variable nature. Plus, they also show that high wind penetration favors intermediate energy sources such as natural gas. I claim however, that few of these studies have considered the dynamic behavior and feedbacks of these systems, including investment delays and learning curves. This thesis uses system dynamics models to simulate the long term changes in the electric grid for Texas. The goal is to test two hypothesis: that the economic value of wind energy decreases as penetration increases, and that variable wind production favors natural gas technologies. It does this by calculating how wind energy changes the shape of the net load duration curve for a given region. This affect changes the profitability of different technologies in unique ways, due to their different fix and variable costs. The conclusions of this thesis are consistent with the literature, with the caveat that they are highly dependent on assumptions regarding the learning curve for energy technologies. The economic value of wind decreases, but this effect can be compensated by lower costs, leading to a continuing adaptation. Faster Wind adoption also reduces the profitably of technologies with high fixed costs such as coal and nuclear, and favors intermediate and peaking sources such as natural gas.en_US
dc.description.statementofresponsibilityby Leonardo Mendes Barlach.en_US
dc.format.extent56 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectEngineering and Management Program.en_US
dc.subjectSystem Design and Management Program.en_US
dc.titleDynamic modelling of variable renewable energy generation sourcesen_US
dc.typeThesisen_US
dc.description.degreeS.M. in Engineering and Managementen_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering and Management Programen_US
dc.contributor.departmentSystem Design and Management Program.en_US
dc.identifier.oclc1006733949en_US


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