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Day-ahead charging operation of electric vehicles with on-site renewable energy resources in a mixed integer linear programming framework

dc.contributor.authorSengor, Ibrahim
dc.contributor.authorErenoglu, Ayse Kubra
dc.contributor.authorErdinc, Ozan
dc.contributor.authorTascikaraoglu, Akin
dc.contributor.authorCatalao, Joao P. S.
dc.date.accessioned2026-06-27T14:26:25Z
dc.date.issued2020
dc.description.abstractThe large-scale penetration of electric vehicles (EVs) into the power system will provoke new challenges needed to be handled by distribution system operators (DSOs). Demand response (DR) strategies play a key role in facilitating the integration of each new asset into the power system. With the aid of the smart grid paradigm, a day-ahead charging operation of large-scale penetration of EVs in different regions that include different aggregators and various EV parking lots (EVPLs) is propounded in this study. Moreover, the uncertainty of the related EV owners, such as the initial state-of-energy and the arrival time to the related EVPL, is taken into account. The stochasticity of PV generation is also investigated by using a scenario-based approach related to daily solar irradiation data. Last but not least, the operational flexibility is also taken into consideration by implementing peak load limitation (PLL) based DR strategies from the DSO point of view. To reveal the effectiveness of the devised scheduling model, it is performed under various case studies that have different levels of PLL, and for the cases with and without PV generation.en
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK) [119E215]
dc.description.sponsorshipFEDER funds through COMPETE 2020
dc.description.sponsorshipFCT [POCI-01-0145FEDER-029803 (02/SAICT/2017)]
dc.description.urihttps://doi.org/10.1049/iet-stg.2019.0282
dc.identifier.doi10.1049/iet-stg.2019.0282
dc.identifier.eissn2515-2947
dc.identifier.endpage375
dc.identifier.issue3
dc.identifier.startpage367
dc.identifier.urihttps://hdl.handle.net/20.500.14981/60644
dc.identifier.volume3
dc.identifier.wos000544741200010
dc.language.isoeng
dc.publisherINST ENGINEERING TECHNOLOGY-IET
dc.relation.ispartofIET SMART GRID
dc.rightsopenAccess
dc.subjectlinear programming
dc.subjectpricing
dc.subjectelectric vehicles
dc.subjectinteger programming
dc.subjectbattery storage plants
dc.subjectdemand side management
dc.subjectphotovoltaic power systems
dc.subjectsmart power grids
dc.subjectpower generation scheduling
dc.subjecton-site renewable energy resources
dc.subjectmixed integer linear programming framework
dc.subjectlarge-scale penetration
dc.subjectpower system
dc.subjectdistribution system operators
dc.subjectDSOs
dc.subjectdemand response strategies
dc.subjectsmart grid paradigm
dc.subjectdifferent aggregators
dc.subjectDR strategies
dc.subjectPLL
dc.subjectpeak load limitation
dc.subjectday-ahead charging operation
dc.subjectpeak load limitation based DR strategies
dc.subjectoperational flexibility
dc.subjectdaily solar irradiation data
dc.subjectscenario-based approach
dc.subjectPV generation
dc.subjectrelated EVPL
dc.subjectarrival time
dc.subjectstate-of-energy
dc.subjectrelated EV owners
dc.subjectEVPLs
dc.subjectEV parking lots
dc.subjectPARKING LOT
dc.subjectSYSTEM
dc.subjectCOORDINATION
dc.subjectBEHAVIOR
dc.subjectMODEL
dc.subjectEngineering
dc.titleDay-ahead charging operation of electric vehicles with on-site renewable energy resources in a mixed integer linear programming framework
dc.typeArticle
dspace.entity.typePublication
local.import.sourceWOS

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