Joint Optimal Allocation of Electric Vehicle Charging Stations and Renewable Energy Sources Including CO2 Emissions

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Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorPolitécnico do Porto-
Autor(es): dc.creatorde Lima, Tayenne Dias-
Autor(es): dc.creatorFranco, John F.-
Autor(es): dc.creatorLezama, Fernando-
Autor(es): dc.creatorSoares, João-
Autor(es): dc.creatorVale, Zita-
Data de aceite: dc.date.accessioned2025-08-21T16:43:08Z-
Data de disponibilização: dc.date.available2025-08-21T16:43:08Z-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2021-09-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1186/s42162-021-00157-5-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/222474-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/222474-
Descrição: dc.descriptionIn the coming years, several transformations in the transport sector are expected, associated with the increase in electric vehicles (EVs). These changes directly impact electrical distribution systems (EDSs), introducing new challenges in their planning and operation. One way to assist in the desired integration of this technology is to allocate EV charging stations (EVCSs). Efforts have been made towards the development of EVCSs, with the ability to recharge the vehicle at a similar time than conventional vehicle filling stations. Besides, EVs can bring environmental benefits by reducing greenhouse gas emissions. However, depending on the energy matrix of the country in which the EVs fleet circulates, there may be indirect emissions of polluting gases. Therefore, the development of this technology must be combined with the growth of renewable generation. Thus, this proposal aims to develop a mathematical model that includes EVs integration in the distribution system. To this end, a mixed-integer linear programming (MILP) model is proposed to solve the allocation problem of EVCSs including renewable energy sources. The model addresses the environmental impact and uncertainties associated with demand (conventional and EVs) and renewable generation. Moreover, an EV charging forecast method is proposed, subject to the uncertainties related to the driver's behavior, the energy required by these vehicles, and the state of charge of the EVs. The proposed model was implemented in the AMPL modelling language and solved via the commercial solver CPLEX. Tests with a 24-node system allow evaluating the proposed method application.-
Descrição: dc.descriptionDepartamento de Engenharia Elétrica Universidade Estadual Paulista, Av. Brasil Sul, 56-
Descrição: dc.descriptionEscola de Engenharia de Energia da Universidade Estadual Paulista, Av. dos Barrageiros, 1881-
Descrição: dc.descriptionGECA D Politécnico do Porto, R. Dr. António Bernardino de Almeida, 431-
Descrição: dc.descriptionPolitécnico do Porto, R. Dr. António Bernardino de Almeida, 431-
Descrição: dc.descriptionDepartamento de Engenharia Elétrica Universidade Estadual Paulista, Av. Brasil Sul, 56-
Descrição: dc.descriptionEscola de Engenharia de Energia da Universidade Estadual Paulista, Av. dos Barrageiros, 1881-
Idioma: dc.languageen-
Relação: dc.relationEnergy Informatics-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectAllocation of electric vehicle charging stations-
Palavras-chave: dc.subjectElectric vehicle charging stations-
Palavras-chave: dc.subjectEV charging forecast method-
Palavras-chave: dc.subjectRenewable energy sources-
Título: dc.titleJoint Optimal Allocation of Electric Vehicle Charging Stations and Renewable Energy Sources Including CO2 Emissions-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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