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dc.contributor.authorPirouzi, S.*
dc.contributor.authorAgahaei, J.*
dc.contributor.authorLatify, M.A.*
dc.contributor.authorYousefi, G.R.*
dc.contributor.authorMokryani, Geev*
dc.date.accessioned2017-03-22T12:04:34Z
dc.date.available2017-03-22T12:04:34Z
dc.date.issued2017-09
dc.identifier.citationPirouzi S, Aghaei J, Latify MA et al (2017) A robust optimization approach for active and reactive power management in smart distribution networks using electric vehicles. IEEE Systems Journal. 12(3): 2699-2710.en_US
dc.identifier.urihttp://hdl.handle.net/10454/11660
dc.descriptionYesen_US
dc.description.abstractThis paper presents a robust framework for active and reactive power management in distribution networks using electric vehicles (EVs). The method simultaneously minimizes the energy cost and the voltage deviation subject to network and EVs constraints. The uncertainties related to active and reactive loads, required energy to charge EV batteries, charge rate of batteries and charger capacity of EVs are modeled using deterministic uncertainty sets. Firstly, based on duality theory, the max min form of the model is converted to a max form. Secondly, Benders decomposition is employed to solve the problem. The effectiveness of the proposed method is demonstrated with a 33-bus distribution network.en_US
dc.language.isoenen_US
dc.rights© 2017 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_US
dc.subjectElectric vehicles (EVs); Active and reactive power management; Robust optimization; Benders decompositionen_US
dc.titleA robust optimization approach for active and reactive power management in smart distribution networks using electric vehiclesen_US
dc.status.refereedYesen_US
dc.date.application2017-07-07
dc.typeArticleen_US
dc.type.versionAccepted Manuscripten_US
dc.identifier.doihttps://doi.org/10.1109/JSYST.2017.2716980
refterms.dateFOA2018-07-25T16:07:54Z
dc.date.accepted2017-02-22


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