Decoding energy security trends: A machine learning-driven composite indicator for advancing Iran's energy sustainability

Despite Iran's significant energy advantages, the issue of energy security and its quantification has not received much attention from researchers. In this study, the trend of Iran's energy security in five dimensions—availability, affordability, acceptability, technology and efficiency, and accessibility—has been quantified using composite indicators methodology based on an Unsupervised Machine Learning Approach. The results of this research indicate that the trends of Iran's energy security from 1999 to 2019 has experienced numerous fluctuations. The best energy security status in the studied period was in 2019, while the worst was in 2012, which did not have a good situation in terms of acceptability, technology and efficiency, and affordability. Finally, policy recommendations based on indicators of energy security trends are offered to assist in paving the road for a more sustainable and yet secure future.