Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/18431
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dc.contributor.authorDe Ridder, Fjo-
dc.contributor.authorD'Hulst, Reinhilde-
dc.contributor.authorKNAPEN, Luk-
dc.contributor.authorJANSSENS, Davy-
dc.date.accessioned2015-03-25T12:50:19Z-
dc.date.available2015-03-25T12:50:19Z-
dc.date.issued2013-
dc.identifier.citationProcedia Computer Science, 19, p. 847-853-
dc.identifier.issn1877-0509-
dc.identifier.urihttp://hdl.handle.net/1942/18431-
dc.description.abstractWe have explored to what extent charging electrical vehicles (EVs) can be exploited to stabilize smart grids. Firstly, we discuss the transition to a future with a lot of renewable energy resources. Next, a decentralized coordinated charging schedule for EVs is proposed, taking into account the comfort settings of the consumers and local and temporal flexibility. Based on the vehicle behavior information (trajectories, parking places and duration, etc.) the algorithm assures that all vehicles can follow their planned trajectories and that power constraints on each car park are always met. An advantage of this decentralized coordination algorithm is that the privacy of consumers, including their future trajectory planning, charging controllers, parking duration, etc. are all treated on local processors on board. As a consequence the responsibility for constructing the charging schedules is put only with the vehicle owner. On the other hand, the parking managers need only to be concerned with the network congestion issues. A first application focuses on controlling the power flows at these parking locations and on rescheduling the charging of the electrical vehicles, so that costs are minimized within the comfort settings and within the physical limitations of the charging stations. This coordinated charging is applied on a car fleet of 200 electrical vehicles and 56 parking locations. Trajectories are computed with an activity based model (FEATHERS). In a second application, the imbalance costs are taken into account as well. The main advantage is for the retailer, who can now actively use the flexibility of the charging process to lower his power trading costs.-
dc.language.isoen-
dc.rights© 2013 The Authors. Published by Elsevier B.V. Selection and peer-review under responsibility of Elhadi M. Shakshuki Open access under CC BY-NC-ND license-
dc.subject.othersmart grids; cooperative scheduling; activity planning; schedule generation; electric mobility models; optimal and distributed control-
dc.titleApplying an activity based model to explore the potential of electrical vehicles in the smart grid-
dc.typeProceedings Paper-
local.bibliographicCitation.conferencedate25-28 June 2013-
local.bibliographicCitation.conferencenameThe 4th International Conference on Ambient Systems, Networks and Technologies-
local.bibliographicCitation.conferenceplaceHalifax, Canada-
dc.identifier.epage853-
dc.identifier.spage847-
dc.identifier.volume19-
local.bibliographicCitation.jcatA2-
dc.description.notesCorresponding author. Tel.: +32 14 33 59 71; fax: +32 14 32 11 85. E-mail address: fjo.deridder@vito.be.-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper-
dc.identifier.doi10.1016/j.procs.2013.06.113-
dc.identifier.urlhttp://www.sciencedirect.com/science/article/pii/S1877050913007217-
local.bibliographicCitation.btitleProcedia Computer Science-
item.fulltextWith Fulltext-
item.accessRightsOpen Access-
item.fullcitationDe Ridder, Fjo; D'Hulst, Reinhilde; KNAPEN, Luk & JANSSENS, Davy (2013) Applying an activity based model to explore the potential of electrical vehicles in the smart grid. In: Procedia Computer Science, 19, p. 847-853.-
item.contributorDe Ridder, Fjo-
item.contributorD'Hulst, Reinhilde-
item.contributorKNAPEN, Luk-
item.contributorJANSSENS, Davy-
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