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Simulation of electric vehicle driver behaviour in road transport and electric power networks

Marmaras, Charalampos, Xydas, Erotokritos and Cipcigan, Liana 2017. Simulation of electric vehicle driver behaviour in road transport and electric power networks. Transportation Research Part C: Emerging Technologies 80 , pp. 239-256. 10.1016/j.trc.2017.05.004

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Abstract

The integration of electric vehicles (EVs) will affect both electricity and transport systems and research is needed on finding possible ways to make a smooth transition to the electrification of the road transport. To fully understand the EV integration consequences, the behaviour of the EV drivers and its impact on these two systems should be studied. This paper describes an integrated simulation-based approach, modelling the EV and its interactions in both road transport and electric power systems. The main components of both systems have been considered, and the EV driver behaviour was modelled using a multi-agent simulation platform. Considering a fleet of 1000 EV agents, two behavioural profiles were studied (Unaware/Aware) to model EV driver behaviour. The two behavioural profiles represent the EV driver in different stages of EV adoption starting with Unaware EV drivers when the public acceptance of EVs is limited, and developing to Aware EV drivers as the electrification of road transport is promoted in an overall context. The EV agents were modelled to follow a realistic activity-based trip pattern, and the impact of EV driver behaviour was simulated on a road transport and electricity grid. It was found that the EV agents’ behaviour has direct and indirect impact on both the road transport network and the electricity grid, affecting the traffic of the roads, the stress of the distribution network and the utilization of the charging infrastructure.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Engineering
Publisher: Elsevier
ISSN: 0968-090X
Funders: EPSRC
Date of First Compliant Deposit: 1 August 2017
Date of Acceptance: 8 May 2017
Last Modified: 24 Jan 2018 09:54
URI: http://orca.cf.ac.uk/id/eprint/103135

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