可再生能源投资的政企随机演化博弈研究——基于动态碳价视角

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Abstract An evolutionary game model with stochastic payment matrix was constructed by introducing a geometric Brownian motion model to define the dynamic carbon price parameters. We took power generation enterprises in the context of the national carbon market as an example and explored influences of different factors on the evolutionary equilibrium and the decision-making of both government and enterprises. The results showed that the carbon price is an important factor influencing the decision-making of the government and enterprises. When the carbon price is low, the optimal decision of government is to implement rewarding and punitive policies; and the optimal decisions of enterprises are not to make investment; at a high carbon price, the best choice is to refrain from implementing rewarding and punitive policies for government and to implement investment strategies for enterprises. The costs, benefits and carbon emissions of thermal power generation, as well as the costs, benefits and construction costs of renewable power generation, are key factors influencing the strategic choices of governments and power producers. The willingness to invest power generation enterprises has a positive correlation with the strength of rewarding and punitive policy implemented by government. Government's willingness to implement policies has a negative correlation with the strength of rewarding and punitive policies. Short-term increases in the strength of rewarding and punitive policies may encourage the investment of power generation enterprises, but will shorten the time of implementation.

Key words： carbon trading mechanism renewable energy investment geometric Brownian motion model evolutionary game stochastic payment

Received: 17 May 2023

PACS:	X32
	F062.4

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	LI Yan-mei
	YANG Chong
	REN Heng-jun
	NIU Dan-dan

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LI Yan-mei,YANG Chong,REN Heng-jun等. Stochastic evolutionary game between governments and enterprises in renewable energy investment in view of dynamic carbon price perspective[J]. CHINA ENVIRONMENTAL SCIENCECE, 2024, 44(1): 567-580.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2024/V44/I1/567

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