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3393. Exploring the trade-off between efficiency and equity of urban public charging investment: an agent-based simulation study
Invited abstract in session TC-43: Simulation in transportation and logistics, stream Agent-based Models in Management, Economic and Organisation Sciences.
Tuesday, 12:30-14:00Room: 99 (building: 306)
Authors (first author is the speaker)
| 1. | Tanxiaosi Luo
|
| Business School, Central South University | |
| 2. | Yanqiu Song
|
| School of Management Science and Engineering, Central university of finance and economics | |
| 3. | Junlin Chen
|
| Management Science and Engineering, Central University of Finance and Economics |
Abstract
The allocation of urban public charging resources plays a crucial role in facilitating EV diffusion. As a public resource, electric vehicle charging infrastructure (EVCI) also faces the conflict between equity and efficiency for its distribution, necessitating consideration of how to balance these two allocation principles. However, current research lacks in-depth exploration of the trade-off between equity and efficiency in the EVCI layout. Therefore, this paper uses an agent-based model (ABM) to depict the complex dynamic relationship between EVCI investment and EV diffusion, aiming to capture the evolution of EV uptake under different EVCI distribution principles. Empirical data from Beijing is further applied to calibrate and validate the model before conducting simulation experiments to analyze which principles should be prioritized with limited resources to fully realize the role of EVCI in promoting transportation electrification. Findings suggest the efficiency-oriented allocation strategy is clearly superior to the equity-oriented allocation strategy at the innovation and growth stage of EVs, and both are better than the baseline scenario. It is indicated that efficiency should be prioritized for EVCI allocation at the beginning stage of EV diffusion, which can eventually achieve a trade-off between efficiency and equity when the EV market maturates.
Keywords
- Transportation
- Agent Systems
- Energy Policy and Planning
Status: accepted
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