The development of renewable energy power is a critical driving force for China’s energy structure’s reform. Formulating a scientific renewable portfolio standard (RPS) quota allocation scheme is a crucial guarantee for achieving the 2030 carbon peak and the 2060 carbon neutrality goal. Based on the complex dynamics of China's RPS quota allocation game process and the current industry management system, and considering the heterogeneity of the benefits between the central government and local governments, a new provincial non-hydro renewable portfolio standard (NHRPS) quota allocation model based on bi-level multi-objective nonlinear programming is required. Based on data from 30 provinces in China, an optimal distribution scheme that considers cost, environment, and fairness were obtained. The results show that because of the differences in energy substitution costs and emission reduction costs between provinces, the implementation intentions of various provinces show great differences in the implementation of the indicator tasks assigned by the central government. The comparative analysis results show that compared with the government’s current distribution scheme, the bi-level optimized distribution scheme saves 4.222 billion yuan in subsidy costs, 259.512 billion yuan in energy substitution costs, and 79.139 billion yuan in emission reduction costs. Meanwhile, the Gini coefficient of the bi-level optimal distribution scheme is less than 0.2, which indicates absolute fairness. The NHRPS quota allocation model proposed in this research reflects the complex dynamics of China’s RPS quota allocation scheme and formulates a more effective and reasonable decision-making tool and reference for the government to formulate an NHRPS quota scheme.

renewable portfolio standard,bi-level multi-objective programming,quota allocation