Robust Joint Expansion Planning of Electrical Distribution Systems and EV Charging Stations

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorBanol Arias, Nataly-
Autor(es): dc.creatorTabares, Alejandra-
Autor(es): dc.creatorFranco, John F.-
Autor(es): dc.creatorLavorato, Marina-
Autor(es): dc.creatorRomero, Ruben-
Data de aceite: dc.date.accessioned2021-03-11T00:56:57Z-
Data de disponibilização: dc.date.available2021-03-11T00:56:57Z-
Data de envio: dc.date.issued2018-12-11-
Data de envio: dc.date.issued2018-12-11-
Data de envio: dc.date.issued2018-04-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/TSTE.2017.2764080-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/179710-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/179710-
Descrição: dc.descriptionElectrical distribution systems (EDSs) should be prepared to cope with demand growth in order to provide a quality service. The future increase in electric vehicles (EVs) represents a challenge for the planning of the EDS due to the corresponding increase in the load. Therefore, methods to support the planning of the EDS, considering the uncertainties of conventional loads and EV demand, should be developed. This paper proposes a mixed-integer linear programming (MILP) model to solve the robust multistage joint expansion planning of EDSs and the allocation of EV charging stations (EVCSs). Chance constraints are used in the proposed robust formulation to deal with load uncertainties, guaranteeing the fulfillment of the substation capacity within a specified confidence level. The expansion planning method considers the construction/reinforcement of substations, EVCSs, and circuits, as well as the allocation of distributed generation units and capacitor banks along the different stages in which the planning horizon is divided. The proposed MILP model guarantees optimality by applying classical optimization techniques. The effectiveness and robustness of the proposed method is verified via two distribution systems with 18 and 54 nodes. Additionally, Monte Carlo simulations are carried out, aiming to verify the compliance of the proposed chance constraint.-
Formato: dc.format884-894-
Idioma: dc.languageen-
Relação: dc.relationIEEE Transactions on Sustainable Energy-
Relação: dc.relation2,318-
Direitos: dc.rightsopenAccess-
Palavras-chave: dc.subjectChance constraint-
Palavras-chave: dc.subjectelectric vehicle charging stations-
Palavras-chave: dc.subjectelectrical distribution systems-
Palavras-chave: dc.subjectmixed-integer linear programming-
Palavras-chave: dc.subjectmultistage expansion planning-
Título: dc.titleRobust Joint Expansion Planning of Electrical Distribution Systems and EV Charging Stations-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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