Numerical Comparison of Optimal Charging Schemes for Electric Vehicles

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2012

Documents

DOI

View graph of relations

The optimal charging schemes for Electric vehicles (EV) generally differ from each other in the choice of charging periods and the possibility of performing vehicle-to-grid (V2G), and have different impacts on EV economics. Regarding these variations, this paper presents a numerical comparison of four
different charging schemes, namely night charging, night charging with V2G, 24 hour charging and 24 hour charging with V2G, on the basis of real driving data and electricity price of Denmark in 2003. For all schemes, optimal charging plans with 5 minute resolution are derived through the solving of a mixed
integer programming problem which aims to minimize the charging cost and meanwhile takes into account the users' driving needs and the practical limitations of the EV battery. In the post processing stage, the rainflow counting algorithm is implemented to assess the lifetime usage of a lithium-ion EV
battery for the four charging schemes. The night charging scheme is found to be the cheapest solution after conducting an annual cost comparison.
Original languageEnglish
Title of host publicationProceedings of IEEE PES General Meeting
Number of pages6
PublisherIEEE
Publication date2012
ISBN (print)9781467327275
DOIs
StatePublished

Conference

Conference2012 IEEE Power & Energy Society General Meeting
CountryUnited States
CitySan Diego, CA
Period22/07/1226/07/12
Internet addresshttp://pes-gm.org/2012/
CitationsWeb of Science® Times Cited: No match on DOI

Keywords

  • Electric vehicle, Mixed integer programming, Optimal charging, Rainflow counting, Vehicle-to-grid, V2G
Download as:
Download as PDF
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
PDF
Download as HTML
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
HTML
Download as Word
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
Word

Download statistics

No data available

ID: 10492500