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Coordinated Vehicle-to-Grid Scheduling to Minimize Grid Load Variance

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dc.citedby4
dc.contributor.authorHashim M.S.en_US
dc.contributor.authorYong J.Y.en_US
dc.contributor.authorRamachandaramurthy V.K.en_US
dc.contributor.authorTan K.M.en_US
dc.contributor.authorTariq M.en_US
dc.contributor.authorid57216688148en_US
dc.contributor.authorid56119339200en_US
dc.contributor.authorid6602912020en_US
dc.contributor.authorid56119108600en_US
dc.contributor.authorid57220656842en_US
dc.date.accessioned2023-05-29T07:22:37Z
dc.date.available2023-05-29T07:22:37Z
dc.date.issued2019
dc.descriptionAutomotive batteries; Charging (batteries); Commercial vehicles; Electric discharges; Electric vehicles; Scheduling; Scheduling algorithms; Vehicle-to-grid; Electric vehicle batteries; Grid-connected; Load leveling; Load profiles; Peak load; Power grids; Residential areas; Electric power transmission networksen_US
dc.description.abstractThis paper presents the Vehicle-to-Grid scheduling algorithm to minimize the grid load variance by utilizing the grid-connected electric vehicle battery. The algorithm performs in two modes, which are load leveling and peak load shaving. In the load leveling mode, the grid-connected electric vehicle is charged from the power grid and hence, increase the grid loading. Meanwhile, the grid loading is reduced in peak load shaving mode since electric vehicle discharges energy from the battery to support the power grid. Various constraints have been considered to ensure the practicality of this study. The Vehicle-to-Grid study was implemented in a commercial-residential area with electric vehicle mobility of 1300. Both uncoordinated charging and coordinated Vehicle-to-Grid scheduling were performed and compared. The results showed that the uncoordinated charging of electric vehicle will induce a new peak in the power grid load profile. On the other hand, the results showed that the proposed coordinated Vehicle-to-Grid scheduling algorithm successfully minimized the grid load variance while satisfying all the constraints and power grid requirements. � 2019 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo8980281
dc.identifier.doi10.1109/UPCON47278.2019.8980281
dc.identifier.scopus2-s2.0-85084278596
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85084278596&doi=10.1109%2fUPCON47278.2019.8980281&partnerID=40&md5=48cc17f344b17ce0fda878b7d644f11b
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24289
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitleProceedings - 2019 International Conference on Electrical, Electronics and Computer Engineering, UPCON 2019
dc.titleCoordinated Vehicle-to-Grid Scheduling to Minimize Grid Load Varianceen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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