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An Agent-Based Approach for Automating the Process of Charging Plug-in Electric Vehicles
Blekinge Institute of Technology, School of Computing.
2010 (English)Independent thesis Advanced level (degree of Master (Two Years))Student thesis
Abstract [en]

The study of Power TAC is a Multi-Agent competitive simulation test-bed, providing opportunity to simulate research and developments of electronic agents which can manage the tasks of the consumers and energy resources in a virtual energy infrastructure. According to the Power TAC scenario, Plug-in Electrical Vehicles are a special type of consumers that interact with this infrastructure and sometimes with the producers through aggregators. The aim of this study is modeling an intelligent Plug-in Electric vehicle agent for Power TAC that acts as an intermediary between Power TAC grid and vehicle owners. The proposed agent acts autonomously and is capable of making decisions about its energy needs by learning the driving behaviors and other preferences of these vehicle owners in a specified time interval. These agents will be able to make decisions about buying energy from the grid when the charging process is necessary or sell their energy back to the grid when the conditions of the electricity market are sufficiently attractive. The objective of this study is to model a Multi-Agent system for automating the process of charging the plug-in Vehicle Agents in Power TAC scenario by determining the necessary agents and the simulation environment where the agents constructed and simulated. Аs results of this study, different strategies are defined by considering the preferences of the vehicle owners and the conditions of the vehicle; thereby the agents autonomously bid behalf of their user in order to automate the process of charging.

Place, publisher, year, edition, pages
2010. , 69 p.
Keyword [en]
Power TAC, Vehicle Agent, Multi-Agent Systems, Electric Vehicle Agent.
National Category
Computer Science
URN: urn:nbn:se:bth-5771Local ID: diva2:833173
Available from: 2015-04-22 Created: 2011-11-04 Last updated: 2015-06-30Bibliographically approved

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