Charging infrastructure roll-out strategies for large scale introduction of electric vehicles in urban areas: An agent-based simulation study. (June 2021)

• Record Type: Journal Article
• Authors: Wolbertus, Rick; van den Hoed, Robert; Kroesen, Maarten; Chorus, Caspar
• Is Part Of: Transportation research. Volume 148(2021)
• Page Start: 262
• Page End: 285
• Publication Date: 2021-06
• Subjects: Charging behaviour -- Agent-based simulation -- Policy -- Business case -- Infrastructure utilization; Transportation -- Research -- Periodicals; 388.011
• DOI: 10.1016/j.tra.2021.04.010
• Languages: English
• ISSNs: 0965-8564

Abstract

Highlights: A data-driven agent-based model compared charging station roll-out strategies. Increasing size, due to return to scale effects result in utilisation efficiency. Policy makers face a trade-off between providing accessibility & convenience. Mixed roll-out strategies (Level 2, hubs, Fast) satisfies EV driver demand best. Abstract: On the eve of the large-scale introduction of electric vehicles, policy makers have to decide on how to organise a significant growth in charging infrastructure to meet demand. There is uncertainty about which charging deployment tactic to follow. The main issue is how many of charging stations, of which type, should be installed and where. Early roll-out has been successful in many places, but knowledge on how to plan a large-scale charging network in urban areas is missing. Little is known about return to scale effects, reciprocal effects of charger availability on sales, and the impact of fast charging or more clustered charging hubs on charging preferences of EV owners. This paper explores the effects of various roll-out strategies for charging infrastructure that facilitate the large-scale introduction of EVs, using agent-based simulation. In contrast to previously proposed models, our model is rooted in empirically observed charging patterns from EVs instead of travel patterns of fossil fuelled cars. In addition, the simulation incorporates different user types (inhabitants, visitors, taxis and shared vehicles) to model the diversity of charging behaviours in an urban environment. Different scenarios are explored along the lines of the type of charging infrastructure (level 2, clustered level 2, fast charging) and the intensity of rollout (EV to charging point ratio). The simulation predicts both the success rate of charging attempts and the additional discomfort when searching for a charging station. Results suggest that return to scale and reciprocal effects in charging infrastructure are considerable, resulting in a lower EV to charging station ratio on the longer term.