China has implemented both quantitative and policy incentives for renewable energy development since 2019 and is currently in the policy transition stage. The implementation of renewable portfolio standards (RPSs) is difficult due to the interests of multiple stakeholders, including power generation enterprises, power grid companies, power users, local governments, and the central government. Based on China's RPS policy and power system reform documents, this research sorted out the core game decision problems of China's renewable energy industry and established a conceptual game decision model of the renewable energy industry from the perspective of local governments, power generation enterprises and power grid companies. The results reveal that for local governments, the probability of meeting the earnings quota or punishments for not reaching quota completion are the major determinants for active participation in quota supervision. For power grid firms, the willingness to accept renewable electricity quotas depends on the additional cost of receiving renewable electricity and governmental incentives. It is reasonable, from the theoretical perspective, to implement the RPS policy on the power generation side. Electricity reform will help clarify the electricity price system and increase the transparency of the quota implementation process. Policy implications are suggested to achieve sustainable development of the renewable energy industry from price incentives and quantity delivery.

The goal of carbon neutrality is an extensive and profound economic and social change, which will have far-reaching impacts on industrial structure, energy structure, and social consumption structure. Energy sectors will face in-depth adjustment, and it is essential to optimize major structures consequently due to the foresight of talent training. This research first employs Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis, Analytic Network Process (ANP), and the weighted fuzzy Technique for Order Performance by Similarity to Ideal Solutions (TOPSIS) to formulate and analyze the structure optimization of academic disciplines, and finally, the universities featuring mining are taken as an example to verify the feasibility of the method. Results reveal that the integration of ANP, SWOT, and the fuzzy TOPSIS evaluation method is able to qualify the assessment for academic discipline optimization. The specialty structure optimization results should focus on clean, intelligent, and sustainable development of the coal industry. The first priority is to increase relevant research on sustainable development of the mining industry, with a priority value of 0.0435. The modern coal chemistry and intelligent coal mining are also highly valued as the options for achieving carbon neutrality. Adding natural gas-related majors is underestimated as the least recognized priority, with a priority value of 0.0133. Suggestions and implications are provided for structure optimization of academic disciplines in universities featuring energy.