Adaptive Robust Linear Programming Model for the Charging Scheduling and Reactive Power Control of EV Fleets

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual de Campinas (UNICAMP)-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorArias, Nataly Banol-
Autor(es): dc.creatorLopez, Juan C.-
Autor(es): dc.creatorRider, Marcos J.-
Autor(es): dc.creatorFredy Franco, John-
Data de aceite: dc.date.accessioned2025-08-21T21:13:43Z-
Data de disponibilização: dc.date.available2025-08-21T21:13:43Z-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2021-06-28-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/PowerTech46648.2021.9494898-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/229309-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/229309-
Descrição: dc.descriptionHigh penetration of electric vehicles (EVs) triggers challenges and opportunities for distribution system operators. Inverter-based EV chargers with active/reactive power control can be used to coordinate the EV fleet's charging process while providing local volt/var regulation. This paper proposes an adaptive robust programming model for the charging scheduling of EV fleets that exploits their capability to locally support the grid via reactive power control. The proposed model aims at maximizing the aggregator's revenue while considering the worst-case scenario in terms of active power losses at the supporting grid. Operational constraints of unbalanced three-phase distribution networks under demand uncertainty are also enforced. The proposed robust model is a min-max problem that can be linearized and solved using a column-and-constraint generation (CCG) method. Tests performed in a 25-node distribution system illustrate the EV fleet's capacity to support the grid while minimizing the total energy not supplied.-
Descrição: dc.descriptionUniversity of Campinas (UNICAMP) School of Electrical and Computing Engineering, Campinas-
Descrição: dc.descriptionSão Paulo State University (UNESP) School of Energy Engineering, Rosana-
Descrição: dc.descriptionSão Paulo State University (UNESP) School of Energy Engineering, Rosana-
Idioma: dc.languageen-
Relação: dc.relation2021 IEEE Madrid PowerTech, PowerTech 2021 - Conference Proceedings-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectAdaptive robust optimization-
Palavras-chave: dc.subjectaggregators-
Palavras-chave: dc.subjectdistribution systems-
Palavras-chave: dc.subjectelectric vehicle fleets-
Palavras-chave: dc.subjectlinear programming-
Palavras-chave: dc.subjectreactive power control-
Título: dc.titleAdaptive Robust Linear Programming Model for the Charging Scheduling and Reactive Power Control of EV Fleets-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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