关键词: 能源供应网络韧性, 复杂网络, Dagum基尼系数, 核密度估计, 多情景扰动模拟

Abstract: Against the backdrop of global intensifying geopolitical uncertainty and increasingly frequent extreme climate events, the stability and security of energy systems have gradually become a central concern of national strategic security. Based on the energy supply and demand data from 2013 to 2023, this study focuses on the energy supply network covering coal-fired power, wind power, and photovoltaic power generation. It comprehensively uses complex network models, Dagum Gini coefficient decomposition, and kernel density estimation methods to conduct in-depth analysis around the three dimensions: multiple disturbance response simulation, regional heterogeneity analysis, and structural evolution. The results show that there are significant differences in the system function retention rate and resilience index of different regions under different types of disturbances. Traditional energy production areas are more likely to exhibit high-frequency disturbance characteristics in multiple scenarios, while regions with a high proportion of renewable energy show stronger anti-interference ability. The overall Gini coefficient of the resilience of the national energy supply network has significantly decreased, and regional differences remain the main source of spatial imbalance in the resilience of the energy supply network. The energy structure presents a dynamic evolution feature of“decreasing coal and increasing wind and solar energy”. Based on this, it is suggested to accelerate the construction of a“coal-wind-solar”collaborative multi energy regulation mechanism, promote complementary interconnection of infrastructure between regions, and optimize the transformation path of energy structure, so as to promote the evolution of China’s energy supply network towards a more resilient and orderly high-quality development direction.

Key words: energy supply network resilience, complex networks, Dagum Gini coefficient, kernel density estimation, multi scenario disturbance simulation