FORECASTING AND PROSPECTS RESEARCH REPORT

Geopolitical turbulence and rapid technological iteration are reshaping the global energy landscape, increasing external uncertainties in supply chains. However, existing energy transition assessment frameworks predominantly focus on internal national factors, neglecting dynamic spillover effects arising from the evolution of global trade networks. This report introduces complex network theory and machine learning methods to construct a comprehensive assessment framework that integrates internal five-dimensional drivers with external network influences, systematically quantifying the energy transition performance of 115 countries globally from 2015 to 2024. The results show that in 2024, the global energy trade network exhibited high efficiency and high polarization, elevating systemic vulnerability. While the overall global transition level in 2024 was better than in 2015, energy equity was at a historical low, constrained by shortfalls in funding and institutional support, leading to a rebound in transition disparities among countries. China ranked 13th globally, with a 21% improvement over 2015, benefiting from technology cost advantages and policy drivers, yet it still holds potential for improvement in the sustainability dimension. Countries need to coordinate internal development with external network positions to ensure the robustness and security of their energy transitions.

Special Statement: This report is one of a series of research reports completed by the research team at the Center for Energy and Environmental Policy Research, Beijing Institute of Technology. If reproduction is required, prior permission from the Center must be obtained, and the reprint must bear the note "Reprinted from the Series of Research Reports of the Center for Energy and Environmental Policy Research, Beijing Institute of Technology."