Distributed Control of PEV Charging Based on Energy Demand Forecast

dc.citation.epage341en_US
dc.citation.issueNumber1en_US
dc.citation.spage332en_US
dc.citation.volumeNumber14en_US
dc.contributor.authorKisacikoglu, M. C.en_US
dc.contributor.authorErden, F.en_US
dc.contributor.authorErdogan, N.en_US
dc.date.accessioned2019-02-21T16:05:33Z
dc.date.available2019-02-21T16:05:33Z
dc.date.issued2018en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.description.abstractThis paper presents a new distributed smart charging strategy for grid integration of plug-in electric vehicles (PEVs). The main goal is to smooth the daily grid load profile while ensuring that each PEV has a desired state of charge level at the time of departure. Communication and computational overhead, and PEV user privacy are also considered during the development of the proposed strategy. It consists of two stages: 1) an offline process to estimate a reference operating power level based on the forecasted mobility energy demand and base loading profile, and 2) a real-time process to determine the charging power for each PEV so that the aggregated load tracks the reference loading level. Tests are carried out both on primary and secondary distribution networks for different heuristic charging scenarios and PEV penetration levels. Results are compared to that of the optimal solution and other state-of-the-art techniques in terms of variance and peak values, and shown to be competitive. Finally, a real vehicle test implementation is done using a commercial-of-the-shelf charging station and an electric vehicle.
dc.description.provenanceMade available in DSpace on 2019-02-21T16:05:33Z (GMT). No. of bitstreams: 1 Bilkent-research-paper.pdf: 222869 bytes, checksum: 842af2b9bd649e7f548593affdbafbb3 (MD5) Previous issue date: 2018en
dc.identifier.doi10.1109/TII.2017.2705075
dc.identifier.issn1551-3203
dc.identifier.urihttp://hdl.handle.net/11693/50259
dc.language.isoEnglish
dc.publisherIEEE Computer Society
dc.relation.isversionofhttps://doi.org/10.1109/TII.2017.2705075
dc.source.titleIEEE Transactions on Industrial Informaticsen_US
dc.subjectDistributed controlen_US
dc.subjectGrid integrationen_US
dc.subjectPeak shavingen_US
dc.subjectPlug-in electric vehicle (PEV)en_US
dc.subjectSmart chargingen_US
dc.titleDistributed Control of PEV Charging Based on Energy Demand Forecasten_US
dc.typeArticleen_US

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