The feed-in tariff policy is widely used to promote the development of renewable energy. China also adopts feed-in tariff policy to attract greater investment in solar photovoltaic power generation. This study employs real options method to assess the optimal levels of feed-in tariffs in 30 provinces of China. The uncertainties in CO2 price and investment cost are considered. A method that integrates the backward dynamic programming algorithm and Least-Squares Monte Carlo method is used to solve the model. The results demonstrate that the feed-in tariffs of 30 provinces range from 0.68 RMB/kWh to 1.71 RMB/kWh, and the average level is 1.01 RMB/kWh. On this basis, we find that the levels of sub-regional feed-in tariff announced in 2013 are no longer appropriate and should be adjusted as soon as possible. We have also identified the implications of technological progress and carbon emission trading schemes, as well as the importance of strengthening electricity transmission. It has been suggested that the Chinese government takes diverse measures, including increasing research and development investment, establishing and improving a nationwide carbon emission trading scheme and accelerating the construction of electricity-transmission infrastructure, to reduce the required feed-in tariff and promote the development of solar photovoltaic power generation. •We estimate the optimal levels of feed-in tariffs for 30 provinces in China by using real options method.•The uncertainties in CO2 price and investment cost are considered.•The feed-in tariffs of 30 provinces range from 0.68 RMB/kWh to 1.71 RMB/kWh, and the average level is 1.01 RMB/kWh.