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
Abstract
As the growing deployment towards transportation electrification, a critical focus has emerged on quantifying the reduction contribution of greenhouse gas emissions from electric vehicles towards achieving carbon neutrality under diverse policy scenarios in the future. This necessitates a dynamic model that captures the evolving composition of the vehicle fleet and accurately forecasts the penetration and developmental trajectory of the electric vehicles in the car market. However, previous studies have largely overlooked the heterogeneity in user usage attributes, rendering them less effective in evaluating the impact of usage-based incentives on electric vehicle market penetration. To bridge this research gap, this study introduces an innovative, data-driven framework that integrates system dynamics and agent-based model. The proposed model can predict levels of electric vehicle penetration and corresponding greenhouse gas emission reductions within the private passenger vehicle sector, under a variety of policy scenarios. Our findings indicate that usage-based incentives, when implemented with optimal intensity, yield more significant emission reduction impacts and long-term economic benefits compared to conventional purchase-based subsidy. These insights not only furnish actionable policy suggestions to expedite the electric vehicle industry's growth in China but also offer valuable implications for other countries seeking to implement effective strategies for combating climate change and fostering sustainable transportation initiatives.
Metadata
Item Type: | Article |
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Authors/Creators: |
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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: |
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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: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:224170 |
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Filename: Integrating System Dynamics and Agent-Based Modeling.pdf
Licence: CC-BY-NC-ND 4.0
