Wind power projects are a crucial step towards achieving the objectives of “carbon neutrality” and “carbon peak” because they can improve the energy crisis and contribute towards environmental pollution reduction. However, the risks of wind power projects cannot be ignored, and the success of the design phase can affect the risks and benefits of wind power projects throughout their life cycle. This paper first proposes causality hypotheses for four types of risk factors in wind power projects: policy, economy, technology, and construction. It constructs a structural equation model for wind power project risk factors and then tests and modifies the model. Then, based on the latent variables of policy, economy, technology, and construction, and the relevant explicit variables, the risk index evaluation system of the wind power project design phase is constructed. The risk assessment catastrophe model of wind power projects is further established, and it is used to evaluate the risk of the K wind power project in the design phase. The risk assessment can identify the overall risk and main risk sources in wind power projects in the design phase and provide countermeasures for effectively controlling risks in wind power projects in China.

The original variables were 14 statistics in 31 provinces and cities in mainland China (excluding Hong Kong, Macao and Taiwan) in 2019, including forest area, forest tending area, afforestation area and timber production. Factor analysis was used to study the factors affecting development potential of forest carbon sinks in mainland China. The results show that the total forest resources factor extracted from the variables related to forest stock and forest land use area was the most important affecting this potential, followed by the forest climate and output value factor extracted from variables related to climate and output. Third was the forest ecological construction factor, which was extracted from forestry afforestation area related variables and fire-damaged areas. In last place was the forest disaster prevention factor extracted from forest nurturing and pest and rodent control area variables. According to systematic clustering of the comprehensive score, development potential of forest carbon sinks in 31 provinces and municipalities across the country was divided into five categories and, based on this, targeted suggestions were put forward for improvement of the above potential in various regions.