An Optimal Hybrid Management of Electric Vehicle Fleet Charging and Load Scheduling in Active Electric Distribution System

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dc.authorscopusid57550278400en_US
dc.authorscopusid58278729200en_US
dc.authorscopusid57216711870en_US
dc.authorscopusid14631882700en_US
dc.contributor.authorAygun, A.I.
dc.contributor.authorHasan, M.S.
dc.contributor.authorJoshi, A.
dc.contributor.authorKamalasadan, S.
dc.date.accessioned2024-08-23T16:07:32Z
dc.date.available2024-08-23T16:07:32Z
dc.date.issued2024en_US
dc.departmentDüzce Üniversitesien_US
dc.description.abstractThis paper introduces a novel scheduling framework designed to manage the charging of electric vehicles (EVs) in a way that considers its effects on the power grid. Leveraging the Alternating Direction Method of Multipliers (ADMM), the methodology offers a significant advantage by enabling decentralized sub-problems, allowing for efficient and rapid solutions. The methodology developed as an algorithmic framework incorporates various scheduling approaches for EV charging, including demand management techniques like valley filling and peak shaving, along with real-time pricing (RTP) considerations. These strategies aim to modify individual electricity consumption patterns to reduce peak demand, ultimately enhancing energy efficiency and ensuring the stability of the power system. The results of the study highlight the crucial role of distributed optimization in improving both demand management strategies and cost objectives. The results indicated that the proposed method shows significant improvement in overall energy efficiency when compared to the state-of-the-art centralized convex optimization framework. © 1972-2012 IEEE.en_US
dc.identifier.doi10.1109/TIA.2024.3384343
dc.identifier.endpage5316en_US
dc.identifier.issn0093-9994
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85189633026en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage5304en_US
dc.identifier.urihttps://doi.org/10.1109/TIA.2024.3384343
dc.identifier.urihttps://hdl.handle.net/20.500.12684/14720
dc.identifier.volume60en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofIEEE Transactions on Industry Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectalternating direction method of multipliers (ADMM)en_US
dc.subjectdemand side managementen_US
dc.subjectElectric vehicle integrationen_US
dc.subjectenergy management systemen_US
dc.subjectload balancingen_US
dc.subjectConvex optimizationen_US
dc.subjectCostsen_US
dc.subjectDemand side managementen_US
dc.subjectElectric power distributionen_US
dc.subjectEnergy efficiencyen_US
dc.subjectEnergy managementen_US
dc.subjectEnergy management systemsen_US
dc.subjectFleet operationsen_US
dc.subjectInteractive computer systemsen_US
dc.subjectAlternating direction method of multiplieren_US
dc.subjectAlternating directions method of multipliersen_US
dc.subjectConvex functionsen_US
dc.subjectElectric vehicle integrationsen_US
dc.subjectLoad schedulingen_US
dc.subjectLoad-Balancingen_US
dc.subjectOptimisationsen_US
dc.subjectPower systems stabilityen_US
dc.subjectReal - Time systemen_US
dc.subjectVehicle fleetsen_US
dc.subjectReal time systemsen_US
dc.titleAn Optimal Hybrid Management of Electric Vehicle Fleet Charging and Load Scheduling in Active Electric Distribution Systemen_US
dc.typeArticleen_US

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