Evaluation of provincial renewable energy generation efficiency and spatio-temporal heterogeneity of influencing factors in China

The structure of renewable energy (RE) development varies substantially across China's provinces, and the spatio-temporal pattern evolution is too pronounced to allow direct comparisons. Therefore, a reasonable method for RE efficiency estimation is important. Markov and spatial Markov chains can be used to analyze the evolution of the temporal and spatial patterns of provincial RE. Simultaneously, data envelopment analysis game cross-efficiency evaluation can quantify the RE generation efficiency of each province from the perspective of competition. Nine factors were selected to identify the key influencing factors the RE generation efficiency. From the perspective of spatio-temporal heterogeneity, a geographically and temporally weighted regression model was combined for spatial modeling. Results show a significant change in the categories of wind and solar power installations, a medium change in biomass installations, and a small change in hydropower installations. Twothirds of the provincial RE generation efficiency increased from 2015 to 2020. There is spatio-temporal heterogeneity regarding the impact of various factors on the RE generation efficiency: The impact of technology market transactions exhibits the greatest inter-provincial variation and the impact of electricity industry investment exhibits the smallest inter-provincial variation.