EconPapers    
Economics at your fingertips  
 

Evolutionary Game and Simulation Analysis of Power Plant and Government Behavior Strategies in the Coupled Power Generation Industry of Agricultural and Forestry Biomass and Coal

Dan Yu, Caihong Zhang (), Siyi Wang () and Lan Zhang
Additional contact information
Dan Yu: School of Economics and Management, Beijing Forestry University, Beijing 100083, China
Caihong Zhang: School of Economics and Management, Beijing Forestry University, Beijing 100083, China
Siyi Wang: Chinese Research Academy of Environmental Sciences, Beijing 100012, China
Lan Zhang: School of Economics and Management, Beijing Forestry University, Beijing 100083, China

Energies, 2023, vol. 16, issue 3, 1-19

Abstract: Under the background of “dual carbon”, the coupled power generation of agricultural and forestry biomass (AFB) and coal, as a new path of coal-power transformation, is key to achieving energy conservation and reducing emissions in the power sector. Timely and effective government subsidies as well as regulation policies will play important roles in the development of the coupled power generation industry. Previous studies usually assumed government policy as singular and static, rarely considering the dynamic changes in government policies. In this study, evolutionary game theory and systematic dynamics research methods were combined. The game relationship and the dynamic evolution process of the behavioral strategies of both sides are analyzed through the construction of a mixed-strategies game model of the government and power plants. A system dynamics model is built for simulations based on the results of the dynamic game evolution, and the influence paths of key factors on the behavioral strategies of the government and power plants were further demonstrated. The results indicated the following: (1) The behavioral strategies of the government and power plants were not stable for a long period of time, but fluctuated during their mutual influence. The dynamic policies and measures formulated by the government according to changes in the behavioral strategies of power plants will promote industrial development more effectively. (2) Increasing subsidization and the strengthening of supervision caused by government policy can increase the enthusiasm of power plants to choose the coupled power generation of AFB and coal. (3) If the government improves the benefits or reduces the transformation costs caused by coupled power generation the industry will be fundamentally improved. The results clearly show the interactions as well as adjustment processes of the behavioral strategies of power plants and the government in the coupled power generation industry of AFB and coal, and the specific effects of key factors on the behavioral strategies of power plants and the government were investigated. This study can provide a theoretical basis for the government to formulate reasonable industrial policies and measures for the coupled power generation of AFB and coal, in addition to being a valuable reference for other countries to develop a coupled power generation industry.

Keywords: agricultural and forestry biomass; coupled power generation; evolutionary game; system dynamics; behavioral strategy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/16/3/1553/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/3/1553/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:16:y:2023:i:3:p:1553-:d:1057560

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jeners:v:16:y:2023:i:3:p:1553-:d:1057560