Exploring policy support for efficiency improvement of wind power from an environmental perspective: Evidence from wind farms in Qinghai, China

Abstract

Intermittent renewable energy is characterized by a high degree of randomness and unpredictability with environmental fluctuations. As support policy in China shifted from the feed-in tariff subsidy (FIT) to the renewable portfolio standard (RPS) and the renewable energy credit (REC), environmental heterogeneity has led to complexity and uncertainty in policy implementation. Employing a stochastic data envelopment analysis (DEA) based on a non-radial directional distance function, this paper evaluates the generation efficiency of 47 wind farms in Qinghai Province from 2019 to 2021, to explore the effectiveness of policy support from an environmental perspective. Subsequently, we calculate the dynamic power generation efficiency by the Malmquist productivity index (MPI) method, which is further decomposed into efficiency change (EC) and technological progress (TP). System generalized moment estimation (SGMM) is then used to analyze the influencing factors of wind farm generation efficiency. The results show that during the study period, the generation efficiency initially experienced a decrease followed by an increase, with an overall upward trend. The generation efficiency reaches a trough during the peak electricity consumption period in summer and winter every year. Dynamic generation efficiency is generally on the rise, and its variations mainly come from TP, with a minimal catch-up effect observed. There is a significant negative correlation between FIT policy and generation efficiency, and the influence of REC is limited. In addition, per capita GDP, wind speed variations, temperature variations, and UHV delivery projects all affect wind farm power generation performance.