1 / 2020-07-26 20:15:28

Data-Driven Assessing of Renewable Energy Cooperation Potential in Countries Along the Belt and Road Initiative Using an Improved PROMETHEE

data-driven assessment; renewable energy cooperation potential; Belt and Road Initiative; improved PROMETHEE

With the worldwide raise awareness of environmental protection and low-carbon development, renewable energy has become a critical transnational cooperation area under the background of China’s Belt and Road Initiative (BRI). This paper quantitatively assesses the potential for renewable energy cooperation in 25 major countries along the BRI. An evaluation indicator system which comprises five dimensions and 18 indicators is designed. The five dimensions include economic factors, social factors, environmental factors, political factors as well as Chinese factors. Then, the original data of these indicators are collected from official websites or authoritative reports. Later, the Entropy method is adopted to determine the subjective weights of these indicators. Considering the shortcoming of parameter determination in traditional PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluations)-II method, a unsupervised machine learning algorithm namely K-means clustering algorithm is utilized to optimize the parameters of PROMETHEE-II, and thus an improved PROMETHEE-II is proposed to obtain the renewable energy cooperation potential index of each evaluated country. Our results show that the indicator of gross domestic product owns the largest weight. Moreover, the countries in East Asia has better cooperation potential than other regions. Specifically, the highest ranked country is Singapore, and followed by Laos and Malaysia.