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Vehicle-to-Grid Profitability Considering EV Battery Degradation
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.ORCID iD: 0000-0002-8189-2420
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2016 (English)In: 2016 IEEE PES ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC), IEEE conference proceedings, 2016, p. 310-314Conference paper, Published paper (Refereed)
Abstract [en]

The electrification of the transportation sector is likely to contribute reducing the global dependency on oil and is expected to drive investments to renewable and intermittent energy sources, by taking advantage of it energy storage capacity. In order to facilitate the EV integration to the grid, and to take advantage of the battery storage and the Vehicle-to-Grid (V2G) scheme, smart charging strategies will be required. However, these strategies rarely consider all relevant costs, such as battery degradation. This work analyses the profitability of bidirectional energy transfer, i.e. the possibility of using aggregated EV batteries as storage for energy which can be injected back to the grid, by considering battery degradation as a cost included in the proposed strategy. A mixed integer linear problem (MILP) for minimizing energy costs and battery ageing costs for EV owners is formulated. The battery degradation due to charging and discharging in the V2G scheme is accounted for in the model used. Two case studies of overnight charging of EVs in Sweden and in Spain are proposed. Results show that given current energy prices and battery costs, V2G is not profitable for EV owners, but if battery prices decrease as expected, the V2G will be present in the medium term.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2016. p. 310-314
Series
Asia-Pacific Power and Energy Engineering Conference, ISSN 2157-4839
Keywords [en]
Electric Vehicle, Battery Degradation, V2G, Energy Management Models
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-201302DOI: 10.1109/APPEEC.2016.7779518ISI: 000391237400061Scopus ID: 2-s2.0-85009945298ISBN: 978-1-5090-5418-3 (print)OAI: oai:DiVA.org:kth-201302DiVA, id: diva2:1073780
Conference
IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), OCT 25-28, 2016, Xian, PEOPLES R CHINA
Note

QC 20170213

Available from: 2017-02-13 Created: 2017-02-13 Last updated: 2017-06-29Bibliographically approved

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Söder, Lennart

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • asciidoc
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