Regional disparities and variation sources decomposition of energy system resilience in China

Tie Wei, Tuerhong Yalikun, Zhicheng Duan and Xiao Yao

Energy, 2025, vol. 330, issue C

Abstract: Strengthening energy system resilience is essential for national energy security amid global uncertainties, particularly in nations with uneven resources, economies, and technologies, like China. Yet, research often focuses on uniform systems, and neglects regional variations and their underlying drivers, despite mounting evidence of their pivotal role in shaping vulnerability and adaptation within complex energy networks. This oversight hampers a comprehensive understanding of systemic weaknesses, leaving critical disparities unaddressed. This study evaluates energy system resilience across 30 Chinese provinces from 2006 to 2021 using a novel, scalable indicator system, while analyzing regional disparities and their underlying sources. Results reveal that China's energy system resilience increased from 0.389 to 1.116, with widening disparities (Dagum Gini: 0.12 to 0.24), as Dagum's Gini coefficient highlights a growing gap primarily driven by differences between southeastern coastal and northern/northwestern regions. Variance decomposition highlights shifting contributions of key factors to these disparities, with energy endowment (−16 %), economic development (−10 %), and transportation (−15 %) declining, while technology (+36 %) and informatization (+5 %) become more influential. K-Means clustering uncovers polarization, with Northwest and Northeast lagging behind the resilient of South, East, North, and Central regions. By exploring this overlooked spatial heterogeneity, the study illuminates China's energy resilience weaknesses due to regional imbalances, addressing a gap in relevant research. Linking factors such as economic and technological advancements to regional disparities clarifies China's uneven resilience and ties it to broader developmental imbalances. Moreover, this integrated framework, blending Dagum's Gini, variance decomposition, and K-Means clustering, effectively analyzes disparities, drivers, and trends. Our findings propose promoting renewables in Northwest and Northeast, technology in lagging areas, and digitalization with smart grids in order to improve energy system resilience.

Keywords: Energy system resilience; Regional disparities; Combined dynamic evaluation; Source decomposition (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:330:y:2025:i:c:s0360544225022868

DOI: 10.1016/j.energy.2025.136644

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