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dc.contributor.advisorDavid J. Perreault and Khurram K. Afridi.en_US
dc.contributor.authorGunter, Samantha Joellynen_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2012-01-12T19:32:39Z
dc.date.available2012-01-12T19:32:39Z
dc.date.copyright2011en_US
dc.date.issued2011en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/68500
dc.descriptionThesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 125-131).en_US
dc.description.abstractPlug-in electric vehicles and distributed generation are expected to appear in growing numbers over the next few decades. Large scale unregulated penetration of plug-in electric vehicles and distributed generation can each have detrimental impact on the existing electric grid infrastructure. However, appropriate pairing of the two technologies along with some storage could mitigate their individual negative impacts. This thesis develops a methodology and an optimization tool for the design of grid connected electric vehicle chargers that integrate distributed generation and storage into a single system. The optimization tool is based on a linear programming approach that identifies designs with the minimum system lifecycle cost. The thesis also develops the component and system cost models needed for this optimization. The tool can handle single and multiple charger systems with centralized or distributed generation and storage. To verify the tool's accuracy, a search-based optimization technique that works for single chargers with centralized generation and storage is also developed and used to validate the tool. To demonstrate the usefulness of the optimization tool, it is used to design optimal architectures for a single-charger residential charging case and a multi-charger public charging case. It is shown that designs that draw the maximum available power from the grid have the lowest 20-year system lifecycle cost. When storage is needed because the grid cannot provide full charging power, optimal designs may or may not include solar PV based distributed generation depending on the location. For example, in locations with solar irradiation profiles like Los Angeles, CA, electric vehicle charger designs that include solar PV generation are optimal, while in locations like Eugene, OR, optimal designs do not include solar PV. It is also shown that with the available technology, wind turbines are not cost effective for use in residential chargers in locations with wind speeds similar to Los Angeles, CA and Boulder, CO. For the multicharger public charging case, designs with centralized storage and generation are optimal.en_US
dc.description.statementofresponsibilityby Samantha Joellyn Gunter.en_US
dc.format.extent131 p.en_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.subjectElectrical Engineering and Computer Science.en_US
dc.titleMethodology for combined Integration of electric vehicles and distributed resources into the electric griden_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc770669273en_US


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