Electric vehicle charging station diffusion: an agent-based evolutionary game model in complex networks

Huang, X., Lin, Y., Lim, M. K. , Zhou, F. and Liu, F. (2022) Electric vehicle charging station diffusion: an agent-based evolutionary game model in complex networks. Energy, 257, 124700. (doi: 10.1016/j.energy.2022.124700)

Abstract

The “chicken-and-egg” link between charging infrastructure and electric vehicle adoption complicates charging station investment, yet existing research lacks significant understanding of this relationship, particularly in complex network settings. To this end, our research designs a novel agent-based evolutionary game model that incorporates consumers' microscopic behavior into the dynamics of charging station diffusion. Based on a case study, the diffusion of charging stations and electric vehicles under current market conditions is simulated and the impact of the network topology is investigated. Results show that: (1) combined with existing policies, the carbon tax policy could increase the charging station proportion by 17.06%; (2) there is an inverted U-shaped effect between electricity prices and the proliferation of charging stations and electric vehicles; (3) the negative impact of electric vehicle social networks can be transferred to charging station proliferation; (4) there are two priorities for the proliferation of the two industries: prioritizing increasing the clustering coefficient, followed by decreasing the average path length, and increasing the clustering coefficient is better than increasing the individual degree; (5) relevant factors (e.g., construction subsidies, carbon taxes, early high electricity prices, high clustering factor networks) contribute to the conversion of plug-in electric vehicles to battery electric vehicles.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Lim, Professor Ming

Creator Roles

Lim, M. K.: Investigation, Conceptualization, Writing – review and editing

• Authors: Huang, X., Lin, Y., Lim, M. K., Zhou, F., and Liu, F.
• College/School: College of Social Sciences > Adam Smith Business School > Management
• Journal Name: Energy
• Publisher: Elsevier
• ISSN: 0360-5442
• ISSN (Online): 1873-6785
• Published Online: 10 July 2022
• Copyright Holders: Copyright © 2022 Elsevier Ltd.
• First Published: First published in Energy 257: 124700
• Publisher Policy: Reproduced in accordance with the publisher copyright policy