Optimal Delivery Scheduling and Charging of EVs in the Navigation of a City Map
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/TSG.2017.2672801 http://hdl.handle.net/11449/164588 |
Resumo: | This paper presents a mixed integer linear programming model to optimize the costs of maintenance and extra hours tits scheduling a fleet of battery electric vehicles (BEVs) so that the products arc delivered to prespecified delivery points along a route. On this route, each BEV must have an efficient charging strategy at the prespecified charging points. The proposed model considers the average speed of the BEVs, the battery states of charge, and a set of deliveries allocated to each BEV. The charging points are located on urban roads and differ according to their charging rate (fast or ultra-fast). Constraints that guarantee the performance of the fleet's batteries are also taken into consideration. Uncertainties in the navigation of urban roads are modeled using the probability of delay due to the presence of traffic signals, schools, and public works. The routes and the intersections of these routes are modeled as a predefined graph. The results and the evaluation of the model, with and without considering the extra hours, show the effectiveness of this type of transport technology. The models were implemented in AMPI, and solved using the commercial solver CPLEX. |
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Repositório Institucional da UNESP |
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Optimal Delivery Scheduling and Charging of EVs in the Navigation of a City MapBattery electric vehiclescharging pointschaing ratesmixed integer linear programmingThis paper presents a mixed integer linear programming model to optimize the costs of maintenance and extra hours tits scheduling a fleet of battery electric vehicles (BEVs) so that the products arc delivered to prespecified delivery points along a route. On this route, each BEV must have an efficient charging strategy at the prespecified charging points. The proposed model considers the average speed of the BEVs, the battery states of charge, and a set of deliveries allocated to each BEV. The charging points are located on urban roads and differ according to their charging rate (fast or ultra-fast). Constraints that guarantee the performance of the fleet's batteries are also taken into consideration. Uncertainties in the navigation of urban roads are modeled using the probability of delay due to the presence of traffic signals, schools, and public works. The routes and the intersections of these routes are modeled as a predefined graph. The results and the evaluation of the model, with and without considering the extra hours, show the effectiveness of this type of transport technology. The models were implemented in AMPI, and solved using the commercial solver CPLEX.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Univ Estadual Paulista, Fac Engn Ilha Solteira, Dept Engn Eletr, BR-15385000 Ilha Solteira, BrazilUniv Estadual Campinas, Sch Elect & Comp Engn, Dept Syst & Energy, BR-13083852 Campinas, SP, BrazilUniv Estadual Paulista, Fac Engn Ilha Solteira, Dept Engn Eletr, BR-15385000 Ilha Solteira, BrazilCNPq: 141462/2013-2FAPESP: 2014/22828-3FAPESP: 2016/14319-7Ieee-inst Electrical Electronics Engineers IncUniversidade Estadual Paulista (Unesp)Universidade Estadual de Campinas (UNICAMP)Cerna, Fernando V. [UNESP]Pourakbari-Kasmaei, Mahdi [UNESP]Romero, Ruben A. [UNESP]Rider, Marcos J.2018-11-26T17:55:12Z2018-11-26T17:55:12Z2018-09-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article4815-4827application/pdfhttp://dx.doi.org/10.1109/TSG.2017.2672801Ieee Transactions On Smart Grid. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 9, n. 5, p. 4815-4827, 2018.1949-3053http://hdl.handle.net/11449/16458810.1109/TSG.2017.2672801WOS:000443200700080WOS000443200700080.pdfWeb of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengIeee Transactions On Smart Grid2,854info:eu-repo/semantics/openAccess2024-07-04T19:06:57Zoai:repositorio.unesp.br:11449/164588Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-06T00:02:15.644755Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Optimal Delivery Scheduling and Charging of EVs in the Navigation of a City Map |
title |
Optimal Delivery Scheduling and Charging of EVs in the Navigation of a City Map |
spellingShingle |
Optimal Delivery Scheduling and Charging of EVs in the Navigation of a City Map Cerna, Fernando V. [UNESP] Battery electric vehicles charging points chaing rates mixed integer linear programming |
title_short |
Optimal Delivery Scheduling and Charging of EVs in the Navigation of a City Map |
title_full |
Optimal Delivery Scheduling and Charging of EVs in the Navigation of a City Map |
title_fullStr |
Optimal Delivery Scheduling and Charging of EVs in the Navigation of a City Map |
title_full_unstemmed |
Optimal Delivery Scheduling and Charging of EVs in the Navigation of a City Map |
title_sort |
Optimal Delivery Scheduling and Charging of EVs in the Navigation of a City Map |
author |
Cerna, Fernando V. [UNESP] |
author_facet |
Cerna, Fernando V. [UNESP] Pourakbari-Kasmaei, Mahdi [UNESP] Romero, Ruben A. [UNESP] Rider, Marcos J. |
author_role |
author |
author2 |
Pourakbari-Kasmaei, Mahdi [UNESP] Romero, Ruben A. [UNESP] Rider, Marcos J. |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) Universidade Estadual de Campinas (UNICAMP) |
dc.contributor.author.fl_str_mv |
Cerna, Fernando V. [UNESP] Pourakbari-Kasmaei, Mahdi [UNESP] Romero, Ruben A. [UNESP] Rider, Marcos J. |
dc.subject.por.fl_str_mv |
Battery electric vehicles charging points chaing rates mixed integer linear programming |
topic |
Battery electric vehicles charging points chaing rates mixed integer linear programming |
description |
This paper presents a mixed integer linear programming model to optimize the costs of maintenance and extra hours tits scheduling a fleet of battery electric vehicles (BEVs) so that the products arc delivered to prespecified delivery points along a route. On this route, each BEV must have an efficient charging strategy at the prespecified charging points. The proposed model considers the average speed of the BEVs, the battery states of charge, and a set of deliveries allocated to each BEV. The charging points are located on urban roads and differ according to their charging rate (fast or ultra-fast). Constraints that guarantee the performance of the fleet's batteries are also taken into consideration. Uncertainties in the navigation of urban roads are modeled using the probability of delay due to the presence of traffic signals, schools, and public works. The routes and the intersections of these routes are modeled as a predefined graph. The results and the evaluation of the model, with and without considering the extra hours, show the effectiveness of this type of transport technology. The models were implemented in AMPI, and solved using the commercial solver CPLEX. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-11-26T17:55:12Z 2018-11-26T17:55:12Z 2018-09-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1109/TSG.2017.2672801 Ieee Transactions On Smart Grid. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 9, n. 5, p. 4815-4827, 2018. 1949-3053 http://hdl.handle.net/11449/164588 10.1109/TSG.2017.2672801 WOS:000443200700080 WOS000443200700080.pdf |
url |
http://dx.doi.org/10.1109/TSG.2017.2672801 http://hdl.handle.net/11449/164588 |
identifier_str_mv |
Ieee Transactions On Smart Grid. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 9, n. 5, p. 4815-4827, 2018. 1949-3053 10.1109/TSG.2017.2672801 WOS:000443200700080 WOS000443200700080.pdf |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Ieee Transactions On Smart Grid 2,854 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
4815-4827 application/pdf |
dc.publisher.none.fl_str_mv |
Ieee-inst Electrical Electronics Engineers Inc |
publisher.none.fl_str_mv |
Ieee-inst Electrical Electronics Engineers Inc |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129574929694720 |