Issue |
E3S Web Conf.
Volume 520, 2024
4th International Conference on Environment Resources and Energy Engineering (ICEREE 2024)
|
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Article Number | 04030 | |
Number of page(s) | 5 | |
Section | Research on Energy Planning and Management and Energy Economy Strategy | |
DOI | https://doi.org/10.1051/e3sconf/202452004030 | |
Published online | 03 May 2024 |
Research on Subsidy Policies to Promote China’s Low-Carbon Development: Taking the Promotion of Electric Vehicles as an Example
1 Planning and Finance Department, Guangdong Power Grid Company, Guangzhou, Guangdong, China
2 School of economics, Jinan University, Guangzhou, Guangdong, China
a* Corresponding author’s email: zhangli09221@126.com
b Co-primary author: jnwy2012@126.com
c Co-primary author: 498552343@qq.com
The large-scale promotion of electric vehicles is China’s strategic measure to alleviate the energy crisis, deal with climate change and promote green development. Taking 19 large and medium-sized cities in China as samples, this thesis constructs a quantitative model of policy subsidies and a gray correlation model to evaluate the subsidies of the main demand-side policies of electric vehicles and their impact on the demand for electric vehicles. The study found that the subsidy intensity (varies from 34,000 to 129,000 yuan per year) of the “direct” policy is stronger than that of the “indirect” policy (ranges from 5,000-104,000 yuan per year). The subsidy intensity of the “indirect” policy varies greatly among cities. Thanks to the convenience of the use link, the gray correlations between the intensity of the “direct” and “indirect” policies and the promotion of electric vehicles are 0.61 and 0.92, respectively, indicating that the influence of the “indirect” policy on consumer behaviour is greater than that of the “direct” policy significantly. Based on the research conclusions, in order to further expand the electric vehicle market, this thesis intends to put forward relevant policy suggestions.
© The Authors, published by EDP Sciences, 2024
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.
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