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Carbon emission trading market construction is an important policy tool to promote the realization of China’s “double carbon” goal. However, problems still exist, such as the lack of market trading vitality, the large difference in carbon trading prices between the eight pilot markets and the instability of the prices. In order to explore the key influencing factors on carbon trading prices, 15 factors were selected to study in detail according to the policy, green industry, economy and environment. Taking China’s eight pilot carbon trading markets as research subjects, we explored the correlation degree of each factor by using the improved gray relational analysis model (GRAM) from the two dimensions of space and time. The research results show that from the space dimension,the industrial development level, development degree of low-carbon industries, air pollution degree and green technology maturity are the main factors that affect the carbon trading price in the eight pilot areas. Meanwhile, from the time dimension, the correlation degree between various factors and carbon trading price both showed a downward trend as a whole, and the fluctuation of the correlation degree of individual factors was different from the overall trend. In conclusion, we can put forward recommendations on the pricing mechanism of the carbon trading market after this comprehensive study.

China’s FIT policies for PV and wind power are leading policies to promote the low-carbon transformation of the power system. We design composite models based on real options and the cost–benefit analysis, using the Evaluation Model of Implementation Effects and the Optimization Model for Policy Design to evaluate the design and implementation effects of FIT policies for PV and wind power. The results of the Evaluation Model of Implementation Effects are the following: (1) The economic and environmental competitiveness of developing PV and wind power projects under the parity policy raised significantly (2.524 to 3.136 times increase). (2) The last two-phase FIT policies fail to encourage power generation enterprises to carry out R&D activities, and supporting policies can be considered to offer incentives for R&D activities in upstream industries of power generation. (3) The substitution effect of green certificates on government subsidies is limited, and new market compensation mechanisms such as CCER can be introduced nationwide. The results of the Optimization Model for Policy Design are the following: (1) There is still space for a 10.306% to 22.981% reduction in feed-in tariffs during the parity policy. (2) Due to the risk of the mismatch in the cost attribute and uneven investment across regions, the parity policy is not suitable for long-term implementation, so the feed-in tariffs for PV and wind power should progressively be disconnected from feed-in tariffs for thermal power.

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