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Estimating plug-in electric vehicle demand flexibility through an agent-based simulation model

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Title: Estimating plug-in electric vehicle demand flexibility through an agent-based simulation model
Authors: Bustos-Turu, G
Van Dam, KH
Acha, S
Shah, N
Item Type: Conference Paper
Abstract: In the future context of smart grids, plug-in electric vehicles (PEVs) can be seen not only as a new spatial and temporal distributed load, but also as an electricity storage system. In this sense, the storage capacity can be aggregated and made an active participant in the power market to provide ancillary services. The estimation of this capacity over time and space is challenging as it depends on many factors such as vehicle owner driving profiles, charging behavior, and charging infrastructure features, etc. In this paper the demand flexibility potential of a PEV fleet is estimated using an agent-based modelling approach in which different scenarios of participation in flexible charging mechanisms are evaluated. The case study depicted in this work is based on current technology and demographic data from an urban area in London (UK).
Issue Date: 1-Jan-2015
URI: http://hdl.handle.net/10044/1/38867
DOI: https://dx.doi.org/10.1109/ISGTEurope.2014.7028889
Published Proceedings: IEEE PES Innovative Smart Grid Technologies, Europe
Copyright Statement: © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor/Funder: Commission of the European Communities
Funder's Grant Number: 314441 (CELSIUS)
Conference Name: ISGT-Europe 2014
Conference Location: Istanbul, Turkey
Publication Status: Published
Start Date: 2014-10-12
Finish Date: 2014-10-15
Appears in Collections:Faculty of Engineering
Centre for Environmental Policy
Chemical Engineering



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