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Understanding EV owners' preferences towards enrolling in smart charging programs

Author(s)
Rodriguez Jimenez, William A. Rodriguez.
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Download1128868322-MIT.pdf (2.377Mb)
Alternative title
Understanding electric vehicle owners' preferences towards enrolling in smart charging programs
Other Contributors
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Sara Fisher Ellison.
Terms of use
MIT 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. http://dspace.mit.edu/handle/1721.1/7582
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Abstract
Demand for electricity has been increasing in recent years, bolstered by growing adoption of electric vehicles (EVs). To smooth demand at peak periods, under demand response or "smart-charging" programs, power utilities can make electric vehicles extend or delay their charging. An EV owner can save money on their power bill by opting in to such programs. However, it is not well known if EV owners would actually be willing to opt-in, given the radically different refueling model between non-EVs and EVs. This investigation attempts to better understand EV owners' preferences towards enrolling in a particular smart charging program. I do this by constructing an adaptive contingent valuation survey that assesses savings amounts, among other variables. Through this method, I am able to quantify that more than half of EV owners are willing to participate in "smart-charging" for low monthly savings of five dollars or less.
Description
Thesis: M. Eng. in Computer Science and Engineering, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019
 
Cataloged from PDF version of thesis.
 
Includes bibliographical references (pages 41-42).
 
Date issued
2019
URI
https://hdl.handle.net/1721.1/123201
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

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