Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/93947
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dc.contributorDepartment of Electrical Engineeringen_US
dc.creatorLu, Xen_US
dc.creatorXia, Sen_US
dc.creatorGu, Wen_US
dc.creatorChan, KWen_US
dc.creatorShahidehpour, Men_US
dc.date.accessioned2022-08-03T08:49:26Z-
dc.date.available2022-08-03T08:49:26Z-
dc.identifier.issn0360-5442en_US
dc.identifier.urihttp://hdl.handle.net/10397/93947-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.rights© 2021 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.en_US
dc.rightsThe following publication Lu, X., Xia, S., Gu, W., Chan, K. W., & Shahidehpour, M. (2021). Two-stage robust distribution system operation by coordinating electric vehicle aggregator charging and load curtailments. Energy, 226, 120345 is available at https://doi.org/10.1016/j.energy.2021.120345.en_US
dc.subjectDistribution systemen_US
dc.subjectDistributionally robust optimizationen_US
dc.subjectEconomic performanceen_US
dc.subjectElectric vehicle aggregatoren_US
dc.subjectLoad curtailmenten_US
dc.subjectRobust optimizationen_US
dc.subjectSystem securityen_US
dc.titleTwo-stage robust distribution system operation by coordinating electric vehicle aggregator charging and load curtailmentsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume226en_US
dc.identifier.doi10.1016/j.energy.2021.120345en_US
dcterms.abstractIn this paper, a comprehensive two-stage robust distribution system operation model is proposed by adjusting the charging of electric vehicle aggregators (EVAs) and curtailing loads. Because uncertainties in EVA charging demands are involved in the second stage of the adopted two-stage framework, distributionally robust optimization is used to improve the average economic performance of the proposed model, and security of distribution system operation is guaranteed by applying the Farkas lemma and robust optimization. The proposed model is solved by iteratively adding optimality cuts and feasibility cuts through a novel constraint generation algorithm, whose mathematical Proof is provided. The case studies show that the proposed model is capable of properly handling EVA uncertainties and coordinating EVA charging and load curtailments. The optimal coordination depends on several key parameters including the cost coefficients of delaying EVA charging and curtailing loads, the limits on delaying EVA charging, the system load level, and the EVA uncertainty level.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationEnergy, 1 July 2021, v. 226, 120345en_US
dcterms.isPartOfEnergyen_US
dcterms.issued2021-07-01-
dc.identifier.scopus2-s2.0-85103125150-
dc.identifier.eissn1873-6785en_US
dc.identifier.artn120345en_US
dc.description.validate202205 bchyen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberEE-0016-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Natural Science Foundation of China; National Key Research and Development Project; Jiangsu Basic Research Project; Fundamental Research Funds for the Central Universitiesen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS54440661-
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