Improving the energy efficiency of China: An analysis considering clean energy and fossil energy resources

Improving energy efficiency can simultaneously contribute to reducing energy shortages while achieving sustainable economic development. With the expansion of the renewable energy sector, improving energy efficiency requires further investigation. This study used the data envelopment analysis (DEA) game cross-efficiency model to calculate the clean energy efficiency (CEE) and fossil energy efficiency (FEE) of China at the provincial level; it identified the key factors affecting energy efficiency using an elastic network model, and clustered the 31 regions. The results show that: (1) the average level of CEE is 0.77, which is higher than the overall FEE; (2) in the geographical distribution, clean energy sources show a high trend in the middle and low trend in the east and west, while FEE shows a low trend in the west and high trend in the east; and (3) the main influencing factors influencing CEE are urbanization levels and secondary industry shares, while the main factors influencing FEE are electrification levels and urbanization level. Finally, suggestions on how to improve energy efficiency were proposed based on the clustering results.

Automated summary

This study used the data envelopment analysis game cross-efficiency model to analyze the energy efficiency in Chinese provinces and identified key factors affecting energy efficiency. The results provide insights into the clean energy and fossil energy efficiency levels, as well as geographical distribution trends. Suggestions for improving energy efficiency are also proposed based on the findings.