Integrating system dynamics and agent-based modeling: A data-driven framework for predicting electric vehicle market penetration and GHG emissions reduction under various incentives scenarios

Zhan, W., Wang, Z., Deng, J. et al. (2 more authors) (2024) Integrating system dynamics and agent-based modeling: A data-driven framework for predicting electric vehicle market penetration and GHG emissions reduction under various incentives scenarios. Applied Energy, 372. 123749. ISSN 0306-2619

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Item Type: Article
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Copyright, Publisher and Additional Information:

© 2024 Elsevier Ltd. This is an author produced version of an article published in Applied Energy. Uploaded in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.

Keywords: Electric vehicles, GHG emission, System dynamics, Agent-based model, Usage-based incentives
Dates:
  • Published: 15 October 2024
  • Published (online): 27 June 2024
  • Accepted: 15 June 2024
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 07 Mar 2025 09:28
Last Modified: 07 Mar 2025 09:28
Status: Published
Publisher: Elsevier
Identification Number: 10.1016/j.apenergy.2024.123749
Related URLs:
Sustainable Development Goals:
  • Sustainable Development Goals: Goal 7: Affordable and Clean Energy
  • Sustainable Development Goals: Goal 13: Climate Action
Open Archives Initiative ID (OAI ID):

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