A fast and efficient coordinated vehicle-to-grid discharging control scheme for peak shaving in power distribution system

dc.citation.epage566en_US
dc.citation.issueNumber3en_US
dc.citation.spage555en_US
dc.citation.volumeNumber6en_US
dc.contributor.authorErdogan, N.en_US
dc.contributor.authorErden, F.en_US
dc.contributor.authorKisacikoglu, M.en_US
dc.date.accessioned2019-02-21T16:01:21Z
dc.date.available2019-02-21T16:01:21Z
dc.date.issued2018en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.description.abstractThis study focuses on the potential role of plug-in electric vehicles (PEVs) as a distributed energy storage unit to provide peak demand minimization in power distribution systems. Vehicle-to-grid (V2G) power and currently available information transfer technology enables utility companies to use this stored energy. The V2G process is first formulated as an optimal control problem. Then, a two-stage V2G discharging control scheme is proposed. In the first stage, a desired level for peak shaving and duration for V2G service are determined off-line based on forecasted loading profile and PEV mobility model. In the second stage, the discharging rates of PEVs are dynamically adjusted in real time by considering the actual grid load and the characteristics of PEVs connected to the grid. The optimal and proposed V2G algorithms are tested using a real residential distribution transformer and PEV mobility data collected from field with different battery and charger ratings for heuristic user case scenarios. The peak shaving performance is assessed in terms of peak shaving index and peak load reduction. Proposed solution is shown to be competitive with the optimal solution while avoiding high computational loads. The impact of the V2G management strategy on the system loading at night is also analyzed by implementing an off-line charging scheduling algorithm.
dc.description.provenanceMade available in DSpace on 2019-02-21T16:01:21Z (GMT). No. of bitstreams: 1 Bilkent-research-paper.pdf: 222869 bytes, checksum: 842af2b9bd649e7f548593affdbafbb3 (MD5) Previous issue date: 2018en
dc.description.sponsorshipAcknowledgements This work was supported in part by the Scientific and Technological Research Council of Turkey through the International PostDoctoral Fellowship Program under Grant 2219. The authors also would like to acknowledge the support of Baskent Electricity Distribution Company that provided the distribution transformer data within the scope of the project DAGSIS (Impact Analysis and Optimization of Distribution-Embedded Systems) funded by Turkish Energy Market Regulatory Authority (EPDK).
dc.identifier.doi10.1007/s40565-017-0375-z
dc.identifier.issn2196-5625
dc.identifier.urihttp://hdl.handle.net/11693/49825
dc.language.isoEnglish
dc.publisherSpringer Heidelberg
dc.relation.isversionofhttps://doi.org/10.1007/s40565-017-0375-z
dc.relation.projectTürkiye Bilimsel ve Teknolojik Araştirma Kurumu, TÜBITAK: 2219
dc.rightsinfo:eu-repo/semantics/openAccess
dc.source.titleJournal of Modern Power Systems and Clean Energyen_US
dc.subjectDistribution transformeren_US
dc.subjectOptimal discharging controlen_US
dc.subjectPeak shavingen_US
dc.subjectPlug-in electric vehiclesen_US
dc.subjectVehicle-to-griden_US
dc.titleA fast and efficient coordinated vehicle-to-grid discharging control scheme for peak shaving in power distribution systemen_US
dc.typeArticleen_US

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