Comparative realistic objectives oriented optimization framework for EV charging scheduling in a distribution system

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dc.contributor.authorGüldorum, Hilmi Cihan
dc.contributor.authorErenoğlu, Ayşe Kübra
dc.contributor.authorErdinç, Ozan
dc.contributor.authorŞengör, İbrahim
dc.contributor.funderTürkiye Bilimsel ve Teknolojik Araştirma Kurumuen
dc.contributor.funderTürkiye Bilimler Akademisien
dc.date.accessioned2022-05-25T11:34:57Z
dc.date.available2022-05-25T11:34:57Z
dc.date.issued2022-05-18
dc.description.abstractThe integration of large-scale electric vehicles (EVs) into the distribution system has emerged as a critical topic of research with the proliferation of EVs over the years. To mitigate the negative effects of EVs on the distribution system (DS), in this study, the optimal operation of an EVPL is investigated with a model in the form of mixed-integer quadratic constrained programming (MIQCP) that aims to minimize a variety of realistic objectives including active power losses, charging cost or voltage deviations while taking DS constraints into account. Also, uncertain behavior of the EVPL has been considered via machine-learning based forecasting by using historic data. The effectiveness of the proposed model has been evaluated using a 33-bus test system with 15-minute time granularity and compared to models that had various objective functions.en
dc.description.sponsorshipTürkiye Bilimsel ve Teknolojik Araştirma Kurumu (Grant 119E215); Türkiye Bilimler Akademisi (Distinguished Young Scientist Programme GEBİP)en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationGüldorum, H. C., Erenoğlu, A. K., Erdinç, O. and Şengör, İ. (2022) ‘Comparative realistic objectives oriented optimization framework for EV charging scheduling in a distribution system’, 2022 3rd International Conference on Smart Grid and Renewable Energy (SGRE), Doha, Qatar, 20-22 March, pp. 1-6. doi: 10.1109/SGRE53517.2022.9774244.en
dc.identifier.doi10.1109/SGRE53517.2022.9774244.en
dc.identifier.endpage6en
dc.identifier.isbn978-1-6654-7908-0
dc.identifier.isbn978-1-6654-7909-7
dc.identifier.startpage1en
dc.identifier.urihttps://hdl.handle.net/10468/13253
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.ispartof2022 3rd International Conference on Smart Grid and Renewable Energy (SGRE), Doha, Qatar, 20-22 March
dc.relation.urihttp://www.sgre-qa.org/
dc.rights© 2022, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en
dc.subjectElectric vehicleen
dc.subjectMixed-integer quadratic constrained programmingen
dc.subjectOptimal power flowen
dc.subjectPower lossesen
dc.titleComparative realistic objectives oriented optimization framework for EV charging scheduling in a distribution systemen
dc.typeConference itemen
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