| Issue |
E3S Web Conf.
Volume 441, 2023
2023 International Conference on Clean Energy and Low Carbon Technologies (CELCT 2023)
|
|
|---|---|---|
| Article Number | 03017 | |
| Number of page(s) | 9 | |
| Section | Intelligent Ecological Management and Green Service | |
| DOI | https://doi.org/10.1051/e3sconf/202344103017 | |
| Published online | 07 November 2023 | |
How does carbon emissions trading scheme affect emission reduction decisions of coal-fired power plants? An evolutionary game theoretic perspective
1 School of Business Administration, Northeastern University, Shenyang 110167, China
2 Institute of Economics, Tsinghua University, Beijing 100084, China
* Corresponding author: wang-jx22@mails.tsinghua.edu.cn
Carbon emissions trading scheme (CETS) is widely regarded as a cost-effective marketbased regulation for carbon abatement. In the context of CETS, this study develops an evolutionary game model that incorporates two representative coal-fired power plants and a government. Our model captures the interplay of emission reduction strategies between coal-fired power plants and endogenously incorporates government regulatory decisions. We analyze the strategic decisions of coal-fired power plants by discussing the dynamics and equilibrium of the game. Our findings demonstrate that in the absence of government implementation of CETS, coal-fired power plants refrain from investing in carbon abatement. However, with the enforcement of CETS, along with sufficient penalties for excessive carbon emissions, coal-fired power plants become inclined to invest in emission reduction. Furthermore, the willingness of coal-fired power plants to invest in carbon abatement exhibits a negative relationship with both the quota and the cost of emission reduction.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.