Global renewable energy power generation efficiency evaluation and influencing factors analysis

The progress of renewable energy development varies around the world, and it's necessary to quantitatively measure the power generation efficiency (PGE) of each country. This study considers five types of renewable en-ergy installed capacity as input indicators and renewable energy power generation as an output indicator. Based on panel data of 36 countries from 2009 to 2018, renewable energy PGE is calculated based on the super -efficiency data envelopment analysis model and is decomposed annually using the Malmquist index. Finally, a random forest regression model was used to evaluate the influencing factors of renewable energy PGE in each country. The results show that the global renewable energy development space pattern has formed. The differ-ences in PGEs between countries are evident, and the correlation between the ranking of renewable energy installed capacity and the average ranking of PGE is weak. The reverse effect of technological progress hinders the growth of renewable energy PGE. Only 41.67 % of all countries are improving PGE, and renewable energy power generation technology is in urgent need of improvement. Among the eleven influencing factors, carbon emissions level and industrial structure have the greatest impact on PGE, followed by electricity structure, tech-nology level, and economic level.(c) 2022 Institution of Chemical Engineers. Published by Elsevier Ltd. All rights reserved.