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dc.contributor.authorŞengör, İbrahim
dc.contributor.authorErenoğlu, Ayşe Kübra
dc.contributor.authorErdinç, Ozan
dc.contributor.authorTasçıkaraoğlu, Akın
dc.contributor.authorCatalao, Joao P. S.
dc.date.accessioned2020-11-20T14:50:39Z
dc.date.available2020-11-20T14:50:39Z
dc.date.issued2018
dc.identifier.isbn978-1-5386-5326-5
dc.identifier.urihttps://hdl.handle.net/20.500.12809/1588
dc.descriptionInternational Conference on Smart Energy Systems and Technologies (SEST) - SEP 10-12, 2018 - Sevilla, SPAINen_US
dc.description0000-0001-8696-6516en_US
dc.descriptionWOS: 000450802300029en_US
dc.description.abstractDemand response (DR) provides enormous opportunities to distribution system operators so as to conduct the power system in a sustainable manner. Due to the increasing penetration of electric vehicles (EV) in the power system, the necessity of enhancing flexibility has gained importance in the charging operation process. With the aid of the smart grid concept and DR programs, more flexible grid operations are provided. In this study, an optimal day-ahead EV charging strategy through electric vehicle parking lots (EVPL) aggregators is intended for the purpose of maximizing the load factor during daily operation. Furthermore, the behavioral uncertainty of EVs and peak load limitation based DR programs are also taken into account in the devised model. In order to reveal the effectiveness of the proposed EVPL aggregator energy management strategy, various case studies are performed, and credible results are reported.en_US
dc.description.sponsorshipUniv Sevilla, ENDESA, IEEE, IEEE Seccion Espana, IESen_US
dc.description.sponsorshipFEDER funds through COMPETE 2020; Portuguese funds through FCT [SAICT-PAC/0004/2015 - POCI-01-0145-FEDER-016434, POCI-01-0145-FEDER-006961, UID/EEA/50014/2013, UID/CEC/50021/2013, UID/EMS/00151/2013, 02/SAICT/2017 - POCI-01-0145-FEDER-029803]; EU 7th Framework Programme FP7/2007-2013European Union (EU) [309048]en_US
dc.description.sponsorshipJ.P.S. Catalao acknowledges the support by FEDER funds through COMPETE 2020 and by Portuguese funds through FCT, under Projects SAICT-PAC/0004/2015 - POCI-01-0145-FEDER-016434, POCI-01-0145-FEDER-006961, UID/EEA/50014/2013, UID/CEC/50021/2013, UID/EMS/00151/2013, and 02/SAICT/2017 - POCI-01-0145-FEDER-029803, and also funding from the EU 7th Framework Programme FP7/2007-2013 under GA no. 309048.en_US
dc.item-language.isoengen_US
dc.publisherIeeeen_US
dc.item-rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectEnergy Managementen_US
dc.subjectEV Parking Lotsen_US
dc.subjectAggregatoren_US
dc.subjectDemand Responseen_US
dc.subjectStochastic Programmingen_US
dc.subjectLoad Factoren_US
dc.titleOptimal Coordination of EV Charging through Aggregators under Peak Load Limitation Based DR Considering Stochasticityen_US
dc.item-typeconferenceObjecten_US
dc.contributor.departmentMÜ, Mühendislik Fakültesi, Elektrik Elektronik Mühendisliği Bölümüen_US
dc.contributor.institutionauthorTasçıkaraoğlu, Akın
dc.relation.journal2018 International Conference on Smart Energy Systems and Technologies (Sest)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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