气候变化领域集成服务门户(CCPortal): Optimal dynamic regulation in retail electricity market with consumer feedback and social learning

CCPortal

DOI	10.1016/j.enpol.2022.113148
	Optimal dynamic regulation in retail electricity market with consumer feedback and social learning
	Wang, Pengyu; Fang, Debin; Wang, Shuyi
发表日期	2022
ISSN	0301-4215
EISSN	1873-6777
卷号	168 页码:16
英文摘要	Effective regulation is critical to advancing electricity retail market reforms to incentivize electricity quality improvements of retail electricity suppliers (REPs) and promote consumer market participation. In addition, with the development of social media, consumer feedback (CF) and social learning (SL) have become more accessible and frequent. However, there is still a research gap on how regulator can use these feedbacks as an aid to optimize dynamic regulation. Therefore, we construct dynamic Stackelberg game and consumer social network models with incomplete information, where the regulator optimizes its strategy to improve regulatory efficiency, and REPs determine electricity product quality to maximize profits. Customers integrate information in social networks to update purchase decisions and provide information feedback, affecting the profits and regulatory, respectively. This paper analyzes the optimal strategy and equilibrium in a variety of scenarios through simulation, and the main conclusions are as follows:(i) CF and SL motivate regulator to play an extremely active role and REPs to focus on continuous improvement of electricity quality. (ii) CF and SL can effectively increase market dynamics, improve regulatory efficiency, enhance social welfare, and curb market blindness. This paper provides decision support for regulator on how to improve regulatory efficiency and use consumer regulation.
英文关键词	Retail electricity market supervision; Consumer feedback; Social learning; Dynamic stackelberg game; Reinforcement learning
学科领域	Economics; Energy & Fuels; Environmental Sciences; Environmental Studies
语种	英语
WOS研究方向	Business & Economics ; Energy & Fuels ; Environmental Sciences & Ecology
WOS记录号	WOS:000828204900008
来源期刊	ENERGY POLICY
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/272251
作者单位	Wuhan University; Wuhan University
推荐引用方式 GB/T 7714	Wang, Pengyu,Fang, Debin,Wang, Shuyi. Optimal dynamic regulation in retail electricity market with consumer feedback and social learning[J],2022,168:16.
APA	Wang, Pengyu,Fang, Debin,&Wang, Shuyi.(2022).Optimal dynamic regulation in retail electricity market with consumer feedback and social learning.ENERGY POLICY,168,16.
MLA	Wang, Pengyu,et al."Optimal dynamic regulation in retail electricity market with consumer feedback and social learning".ENERGY POLICY 168(2022):16.