| Issue |
E3S Web Conf.
Volume 118, 2019
2019 4th International Conference on Advances in Energy and Environment Research (ICAEER 2019)
|
|
|---|---|---|
| Article Number | 01061 | |
| Number of page(s) | 4 | |
| Section | Energy Engineering, Materials and Technology | |
| DOI | https://doi.org/10.1051/e3sconf/201911801061 | |
| Published online | 04 October 2019 | |
The behavior strategies between the government and power generation enterprises considering the learning mechanism based on evolutionary game
1
School of Management, Hefei University of Technology, Hefei, 230009, PR China
2
Research Center of Industrial Transfer and Innovation Development, Hefei University of Technology, Hefei, Anhui 230009, PR China
* Corresponding author: sun1070435290@qq.com
The Renewable Portfolio Standard (RPS) as a policy tool to promote renewable energy development has gone through more than ten years in China. In order to research the strategic interaction between governments and power generation enterprises under the background of energy system transformation and upgrading, a learning mechanism was introduced based on the dynamic reward and punishment mechanism, and an evolutionary game model between the government and power generation enterprises was established. The results showed that the evolutionary stability strategy depended on the dynamic reward and punishment mechanism, which is conducive to the gradual stability of the system. The existence of learning mechanism not only reduced the cost of wind power, but also reduced the probability of government supervision.
© The Authors, published by EDP Sciences, 2019
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.