Latest revision as of 14:55, 5 March 2021

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.

Document type: Article

Original document

The different versions of the original document can be found in:

• http://orca.cf.ac.uk/103135/1/1-s2.0-S0968090X17301341-main.pdf under the license http://creativecommons.org/licenses/by/4.0, Start_date:

• https://doi.org/10.1016/j.trc.2017.05.004 under the license http://creativecommons.org/licenses/by/4.0, Start_date:

• https://api.elsevier.com/content/article/PII:S0968090X17301341?httpAccept=text/xml,

https://api.elsevier.com/content/article/PII:S0968090X17301341?httpAccept=text/plain,

http://dx.doi.org/10.1016/j.trc.2017.05.004 under the license cc-by

• https://www.sciencedirect.com/science/article/pii/S0968090X17301341,

http://orca.cf.ac.uk/103135,

https://academic.microsoft.com/#/detail/2612363927 under the license https://www.elsevier.com/tdm/userlicense/1.0/