This research aims to investigate the requirements of the future Electric Vehicle Infrastructure in residential areas with the application of public street charging in an urban environment such as Cardiff where the predominant residential houses are arranged as high-density terraced layout.

The model has been designed very scalable to offer easy application for alternative future scenarios of the charging infrastructure (e.g. wireless charging). Energy and power required by each car and the aggregated values indicate the impact on the local transformer.

• The research work proposes a model of charging infrastructure using a multi-agent approach developed in AnyLogic software. This approach models the agent representing electric vehicles in a very general way and it can be applied to a wide range of studies.

  • charging and discharging processes have been described considering electrical constraints and allowing fine tuning of parameters to represent a wide range of vehicle types with different characteristics.
  • the model allows for testing different topologies of charging stations, e.g. a fast or slow charging facility, wired or wireless and its associated charging cost.
  • the overall model is a hybrid model combining agent-based modelling, system dynamics, and discrete-event modelling to optimally represent a small urban district such the ones present Cardiff for a feasibility study on streetlight charging and its economic impact assessment.
  • “Daylight charging only” approach as applied to the first streetlight charging in Chicago, US.

Thanks to the multi-agent approach, a wide range of car owner behavior can be statistically generated and introduced in the model using different types of cars (EV, ICE and Plug-in hybrid). The graphical interface provides an animation of cars looking for a parking spot, where ICE cars select only the normal parking slots; EV or hybrid cars select parking with street charging if needed.
Technical and economic evaluations can be estimated from future scenario results to select the optimal technical and socio-economic solution for the local area.

[1] Maurizio Albano, Luca Mantese, Liana Cipcigan and Fabio Bignucolo, Future Cardiff Electric Vehicle Infrastructure: usage metrics, impact on electrical distribution networks, equality and socio-economic impact and economic performances in local community, Proceedings of SRI-Congress 2025, June 16-20, 2025, Chicago, Illinois, US.

[2] Luca Mantese, Fabio Bignucolo, Maurizio Albano and Liana Cipcigan, Electrical and Economic Model of Electric Vehicle Charging Stations in a Multi-Agent Environment, Proc. of 60th International Universities Power Engineering Conference (UPEC2025), London, United Kingdom, 2025.

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