Affiliations: [a] School of Business, Hohai University, China
| [b] School of Public Administration, Hohai University, China
Correspondence:
[*]
Corresponding author. Bo Shang, School of Business, Hohai University, Nanjing, 211100, China.
E-mail: boshang@hhu.edu.cn.
Abstract: In a significant period of Chinese energy reformation to the point of expediting revolution in energy production and consumption, and promoting green low-carbon upgrading transformation of energy electricity, Chinese government has to implement the obligatory policy of renewable portfolio standards (RPS) with specific institutional provisions sternly. The renewable energy quotas in thermal power industry with carbon emission abatement constraints particularly have a latent impact on the behavior of thermal electricity producers, which is ineluctably involved in electricity connection of grid companies. To make clear the positive role in boosting investment in renewable energy generation in thermal power industry under mandatory quotas requirements, we will utilize evolutionary game based on system dynamics (SD) to tackle with the sophisticated nexus among the government, thermal power producers and grid companies. We begin analysis of general evolutionary strategy stability in scenario ll by dynamically adjusting values of external variables of SD model to uncover pivotal variables affecting evolutionary strategy stability. Then in scenario I, the dynamic punishment structure consisting of cost elements to spark off the emulation of optimal manoeuvre selections of tripartite game agents is amended based on the simulation of vital variables affecting evolutionary strategy stability in scenario II. The significant conclusions provide decision-making support and management enlightenment for Chinese government to edge renewable energy generation capacity of thermal power producers and constrained degree of dynamic penalty for grid companies.
Keywords: Renewable portfolio standards (RPS), China’s power market, Carbon abatement, Government regulation, evolutionary strategy stability, system dynamics
