A multi-agent system with a percolation approach to simulate the driving pattern of Plug-In ELectric Vehicles

Detalhes bibliográficos
Autor(a) principal: Melo, J. D. [UNESP]
Data de Publicação: 2012
Outros Autores: Carreno, E. M. [UNESP], Padilha-Feltrin, A. [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/TDC.2012.6281613
http://hdl.handle.net/11449/73708
Resumo: A multi-agent system with a percolation approach to simulate the driving pattern of Plug-In Electric Vehicle (PEV), especially suited to simulate the PEVs behavior on any distribution systems, is presented. This tool intends to complement information about the driving patterns database on systems where that kind of information is not available. So, this paper aims to provide a framework that is able to work with any kind of technology and load generated of PEVs. The service zone is divided into several sub-zones, each subzone is considered as an independent agent identified with corresponding load level, and their relationships with the neighboring zones are represented as network probabilities. A percolation approach is used to characterize the autonomy of the battery of the PVEs to move through the city. The methodology is tested with data from a mid-size city real distribution system. The result shows the sub-area where the battery of PEVs will need to be recharge and gives the planners of distribution systems the necessary input for a medium to long term network planning in a smart grid environment. © 2012 IEEE.
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spelling A multi-agent system with a percolation approach to simulate the driving pattern of Plug-In ELectric VehiclesAgentdistribution planningmulti-agentpercolation theoryplugin electric vehicleDistribution planningDistribution systemsDriving patternIndependent agentsLoad levelsLong-term network planningMulti agent system (MAS)Percolation theoryPlug-insReal distributionSmart gridAgentsExhibitionsLocal area networksMulti agent systemsSolventsElectric vehiclesA multi-agent system with a percolation approach to simulate the driving pattern of Plug-In Electric Vehicle (PEV), especially suited to simulate the PEVs behavior on any distribution systems, is presented. This tool intends to complement information about the driving patterns database on systems where that kind of information is not available. So, this paper aims to provide a framework that is able to work with any kind of technology and load generated of PEVs. The service zone is divided into several sub-zones, each subzone is considered as an independent agent identified with corresponding load level, and their relationships with the neighboring zones are represented as network probabilities. A percolation approach is used to characterize the autonomy of the battery of the PVEs to move through the city. The methodology is tested with data from a mid-size city real distribution system. The result shows the sub-area where the battery of PEVs will need to be recharge and gives the planners of distribution systems the necessary input for a medium to long term network planning in a smart grid environment. © 2012 IEEE.Faculdade de Engenharia de Ilha Solteira Universidade Estadual Paulista (UNESP) Departamento de Engenharia Elétrica, Ilha Solteira 15385-000, SPCECEUNIOESTE, Foz de Iguaçu-PRFaculdade de Engenharia de Ilha Solteira Universidade Estadual Paulista (UNESP) Departamento de Engenharia Elétrica, Ilha Solteira 15385-000, SPUniversidade Estadual Paulista (Unesp)Universidade Estadual do Oeste do Paraná (UNIOESTE)Melo, J. D. [UNESP]Carreno, E. M. [UNESP]Padilha-Feltrin, A. [UNESP]2014-05-27T11:27:08Z2014-05-27T11:27:08Z2012-11-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1109/TDC.2012.6281613Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference.2160-85552160-8563http://hdl.handle.net/11449/7370810.1109/TDC.2012.6281613WOS:0003170011001992-s2.0-84867969910Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings of the IEEE Power Engineering Society Transmission and Distribution Conferenceinfo:eu-repo/semantics/openAccess2024-07-04T19:11:39Zoai:repositorio.unesp.br:11449/73708Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T18:49:28.469754Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A multi-agent system with a percolation approach to simulate the driving pattern of Plug-In ELectric Vehicles
title A multi-agent system with a percolation approach to simulate the driving pattern of Plug-In ELectric Vehicles
spellingShingle A multi-agent system with a percolation approach to simulate the driving pattern of Plug-In ELectric Vehicles
Melo, J. D. [UNESP]
Agent
distribution planning
multi-agent
percolation theory
plugin electric vehicle
Distribution planning
Distribution systems
Driving pattern
Independent agents
Load levels
Long-term network planning
Multi agent system (MAS)
Percolation theory
Plug-ins
Real distribution
Smart grid
Agents
Exhibitions
Local area networks
Multi agent systems
Solvents
Electric vehicles
title_short A multi-agent system with a percolation approach to simulate the driving pattern of Plug-In ELectric Vehicles
title_full A multi-agent system with a percolation approach to simulate the driving pattern of Plug-In ELectric Vehicles
title_fullStr A multi-agent system with a percolation approach to simulate the driving pattern of Plug-In ELectric Vehicles
title_full_unstemmed A multi-agent system with a percolation approach to simulate the driving pattern of Plug-In ELectric Vehicles
title_sort A multi-agent system with a percolation approach to simulate the driving pattern of Plug-In ELectric Vehicles
author Melo, J. D. [UNESP]
author_facet Melo, J. D. [UNESP]
Carreno, E. M. [UNESP]
Padilha-Feltrin, A. [UNESP]
author_role author
author2 Carreno, E. M. [UNESP]
Padilha-Feltrin, A. [UNESP]
author2_role author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Universidade Estadual do Oeste do Paraná (UNIOESTE)
dc.contributor.author.fl_str_mv Melo, J. D. [UNESP]
Carreno, E. M. [UNESP]
Padilha-Feltrin, A. [UNESP]
dc.subject.por.fl_str_mv Agent
distribution planning
multi-agent
percolation theory
plugin electric vehicle
Distribution planning
Distribution systems
Driving pattern
Independent agents
Load levels
Long-term network planning
Multi agent system (MAS)
Percolation theory
Plug-ins
Real distribution
Smart grid
Agents
Exhibitions
Local area networks
Multi agent systems
Solvents
Electric vehicles
topic Agent
distribution planning
multi-agent
percolation theory
plugin electric vehicle
Distribution planning
Distribution systems
Driving pattern
Independent agents
Load levels
Long-term network planning
Multi agent system (MAS)
Percolation theory
Plug-ins
Real distribution
Smart grid
Agents
Exhibitions
Local area networks
Multi agent systems
Solvents
Electric vehicles
description A multi-agent system with a percolation approach to simulate the driving pattern of Plug-In Electric Vehicle (PEV), especially suited to simulate the PEVs behavior on any distribution systems, is presented. This tool intends to complement information about the driving patterns database on systems where that kind of information is not available. So, this paper aims to provide a framework that is able to work with any kind of technology and load generated of PEVs. The service zone is divided into several sub-zones, each subzone is considered as an independent agent identified with corresponding load level, and their relationships with the neighboring zones are represented as network probabilities. A percolation approach is used to characterize the autonomy of the battery of the PVEs to move through the city. The methodology is tested with data from a mid-size city real distribution system. The result shows the sub-area where the battery of PEVs will need to be recharge and gives the planners of distribution systems the necessary input for a medium to long term network planning in a smart grid environment. © 2012 IEEE.
publishDate 2012
dc.date.none.fl_str_mv 2012-11-01
2014-05-27T11:27:08Z
2014-05-27T11:27:08Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/TDC.2012.6281613
Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference.
2160-8555
2160-8563
http://hdl.handle.net/11449/73708
10.1109/TDC.2012.6281613
WOS:000317001100199
2-s2.0-84867969910
url http://dx.doi.org/10.1109/TDC.2012.6281613
http://hdl.handle.net/11449/73708
identifier_str_mv Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference.
2160-8555
2160-8563
10.1109/TDC.2012.6281613
WOS:000317001100199
2-s2.0-84867969910
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
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
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