Assessing dynamic China's energy security: Based on functional data analysis

In this paper, the entropy weight method is applied to quantitatively measure the energy security levels of 30 provinces in China from 2004 to 2017. Then, functional data analysis is used to investigate the changes in energy security from a dynamic perspective. Results show that the energy security level of Inner Mongolia (0.7080), Shanxi (0.6713), and Shaanxi (0.5878) ranked in the top three in 2017. From 2004 to 2017, China's energy security experienced five stages: Increasing-decreasing-increasing-decreasing-increasing. Until now, energy security is in the recovery period. According to the similarity of the energy security function curve, the 30 provinces can be divided into three categories: Leading area, Medium area, and Backward area. These findings have great significance in ensuring regional energy security. (C) 2020 Elsevier Ltd. All rights reserved.

Automated summary

This paper quantitatively measures the energy security levels of 30 provinces in China from 2004 to 2017 using the entropy weight method and functional data analysis. The provinces are classified into three categories based on the similarity of their energy security function curve, which is of great significance for ensuring regional energy security.