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Metadados | Descrição | Idioma |
---|---|---|
Autor(es): dc.contributor | Universidade Estadual Paulista (Unesp) | - |
Autor(es): dc.contributor | Ryerson University | - |
Autor(es): dc.creator | Quijano, Darwin A. [UNESP] | - |
Autor(es): dc.creator | Melgar-Dominguez, Ozy D. [UNESP] | - |
Autor(es): dc.creator | Sabillon, Carlos | - |
Autor(es): dc.creator | Venkatesh, Bala | - |
Autor(es): dc.creator | Padilha-Feltrin, Antonio [UNESP] | - |
Data de aceite: dc.date.accessioned | 2022-02-22T00:54:17Z | - |
Data de disponibilização: dc.date.available | 2022-02-22T00:54:17Z | - |
Data de envio: dc.date.issued | 2021-06-25 | - |
Data de envio: dc.date.issued | 2021-06-25 | - |
Data de envio: dc.date.issued | 2020-12-31 | - |
Fonte completa do material: dc.identifier | http://dx.doi.org/10.1049/gtd2.12026 | - |
Fonte completa do material: dc.identifier | http://hdl.handle.net/11449/208740 | - |
Fonte: dc.identifier.uri | http://educapes.capes.gov.br/handle/11449/208740 | - |
Descrição: dc.description | This work presents a novel strategy, designed from the distribution system operator viewpoint, aimed at estimating the hosting capacity in electric distribution systems when controllable plug-in electric vehicles are in place. The strategy seeks to determine the maximum wind-based distributed generation penetration by coordinating, on a forecast basis, the dispatch of electric vehicle aggregators, the operation of voltage regulation devices, and the active and reactive distributed generation power injections. Different from previous works, the proposed approach leverages controllable features of electric vehicles taking into account technical electric vehicle characteristics, driving behaviour of electric vehicle owners, and electric vehicle energy requirements to accomplish their primary purpose. The presented strategy is formulated as a two-stage stochastic mixed-integer linear programming problem. The first stage maximises the distributed generation installed capacity, while the second stage minimises the energy losses during the planning horizon. Probability density functions are used to describe the uncertainties associated with renewable distributed generation, conventional demand, and electric vehicle driving patterns. Obtained results show that controlling the power dispatched to electric vehicle aggregators can increase the distributed generation hosting capacity by up to 15% (given a 40% electric vehicle penetration), when compared to an uncontrolled electric vehicle approach. | - |
Descrição: dc.description | Electrical Engineering Department São Paulo State University (UNESP) | - |
Descrição: dc.description | Centre for Urban Energy Ryerson University | - |
Descrição: dc.description | Electrical Engineering Department São Paulo State University (UNESP) | - |
Formato: dc.format | 359-370 | - |
Idioma: dc.language | en | - |
Relação: dc.relation | IET Generation, Transmission and Distribution | - |
???dc.source???: dc.source | Scopus | - |
Título: dc.title | Increasing distributed generation hosting capacity in distribution systems via optimal coordination of electric vehicle aggregators | - |
Tipo de arquivo: dc.type | livro digital | - |
Aparece nas coleções: | Repositório Institucional - Unesp |
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