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Optimizing coordinated spatio-temporal control of electric vehicles for enhanced energy sharing and performance across building communities
Dalarna University, School of Information and Engineering, Energy Technology.ORCID iD: 0000-0003-3025-6333
2024 (English)In: Energy and Buildings, ISSN 0378-7788, E-ISSN 1872-6178, Vol. 312, article id 114167Article in journal (Refereed) Published
Sustainable development
SDG 7: Affordable and clean energy
Abstract [en]

Most of the existing electric vehicles (EVs) charging controls consider power balance regulation in only one community while neglecting their mobility capability. EVs can be considered as mobile batteries and thus deliver and share electricity between multiple building communities, i.e., Community-to-EV-to-Community (C2V2C). Since different communities can have different power regulation needs, it is challenging to consider the various spatio-temporal needs and balance them. This study aims to bridge the research gap by developing a genetic algorithm based advanced C2V2C control to optimize EV charging and electricity delivery between multiple communities. The developed control considers the spatio-temporal power regulating needs of multiple communities and balances these needs based on the users’ requirements via a weighting factor. Using two building communities as case studies, the developed control is compared with a conventional independent control under two control objectives. The results demonstrated the effectiveness of the C2V2C service in reducing the aggregated peak power exchanges with the grid (e.g., by 1 %∼6%) and reducing the total electricity costs (e.g., by up to 282 %) of multiple communities. The impacts of the users’ preferences are also discussed. This study provides a novel and resource-efficient solution for electricity sharing between different buildings. © 2024 The Authors

Place, publisher, year, edition, pages
Elsevier, 2024. Vol. 312, article id 114167
Keywords [en]
Building Community, C2V2C (Community-to-vehicle-to-community), Coordinated Control, Electric Vehicles, Energy Balance, Buildings, Charging (batteries), Costs, Electric power system control, Energy policy, Energy utilization, Vehicle performance, Co-ordinated control, Electric vehicle charging controls, Energy performance, Energy sharings, Power balance, Spatio-temporal, Temporal controls, Genetic algorithms
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:du-48517DOI: 10.1016/j.enbuild.2024.114167ISI: 001231306100002Scopus ID: 2-s2.0-85190773861OAI: oai:DiVA.org:du-48517DiVA, id: diva2:1857800
Available from: 2024-05-14 Created: 2024-05-14 Last updated: 2024-06-20Bibliographically approved

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Huang, Pei

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • 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
  • html
  • text
  • asciidoc
  • rtf