Analysis of wind turbine micrositing efficiency: An application of two-subprocess data envelopment analysis method

China has encountered a huge challenge in the process of wind development due to serious wind curtailment and lower generation efficiency. Inferior wind turbines micrositing is the main reason leading to such problems. In order to better assess the wind turbines micrositing of wind farms (WF) in China, two-subprocess data envelopment analysis (DEA) model is proposed. The improved DEA model divides the complicated system of wind turbines micrositing into two subprocesses: wind turbines arrangement subprocess and power production optimization subprocess, and then the efficiencies of the two subprocesses are assessed respectively. The superiority of the proposed model is proved by a case study. Then, the efficiency scores obtained by two-subprocess DEA are taken as the dependent variables, and Tobit regression model is employed to explore the relationship between the efficiency scores and the environment variables. The study result reveals that: two-subprocess DEA can find out in which subprocess the low efficiency exits; Tobit model can find if the environmental factors are significant or not, and further justify in which subprocess the environmental factors play significant roles. In addition, the environmental factors of the integrity and rationality of data exerts positive and significant influence on micrositing efficiency, but terrain roughness is proven to adversely affect the micrositing effect of wind farms.