dc.contributor | Universidade Estadual Paulista (Unesp) | |
dc.contributor | Universidade Estadual do Oeste do Paraná (UNIOESTE) | |
dc.date.accessioned | 2014-05-27T11:27:08Z | |
dc.date.available | 2014-05-27T11:27:08Z | |
dc.date.created | 2014-05-27T11:27:08Z | |
dc.date.issued | 2012-11-01 | |
dc.identifier | Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference. | |
dc.identifier | 2160-8555 | |
dc.identifier | 2160-8563 | |
dc.identifier | http://hdl.handle.net/11449/73708 | |
dc.identifier | 10.1109/TDC.2012.6281613 | |
dc.identifier | WOS:000317001100199 | |
dc.identifier | 2-s2.0-84867969910 | |
dc.description.abstract | 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. | |
dc.language | eng | |
dc.relation | Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference | |
dc.rights | Acesso aberto | |
dc.source | Scopus | |
dc.subject | Agent | |
dc.subject | distribution planning | |
dc.subject | multi-agent | |
dc.subject | percolation theory | |
dc.subject | plugin electric vehicle | |
dc.subject | Distribution planning | |
dc.subject | Distribution systems | |
dc.subject | Driving pattern | |
dc.subject | Independent agents | |
dc.subject | Load levels | |
dc.subject | Long-term network planning | |
dc.subject | Multi agent system (MAS) | |
dc.subject | Percolation theory | |
dc.subject | Plug-ins | |
dc.subject | Real distribution | |
dc.subject | Smart grid | |
dc.subject | Agents | |
dc.subject | Exhibitions | |
dc.subject | Local area networks | |
dc.subject | Multi agent systems | |
dc.subject | Solvents | |
dc.subject | Electric vehicles | |
dc.title | A multi-agent system with a percolation approach to simulate the driving pattern of Plug-In ELectric Vehicles | |
dc.type | Actas de congresos | |