Earthquake disasters severely disrupt energy systems through direct damage and cascading effects. However, existing assessment frameworks are often static or focus on single energy types, lacking dynamic and diagnostic capabilities. To address this gap, this study develops an integrated DPSIR-TOPSIS–Barrier model that combines causal analysis with quantitative diagnostics. The model is applied to the seismically active Sichuan Province in China using panel data from 2018 to 2023. Results show that Sichuan’s energy emergency capability progressed through three distinct phases: Rapid Growth, Stress Test, and Resilience Enhancement. The composite score increased from 0.360 in 2018 to 0.735 in 2023. More importantly, the Response subsystem is identified as the primary bottleneck with an average obstacle degree of 0.33, driven mainly by insufficient funding and low infrastructure redundancy. Unlike conventional static or single-energy evaluations, our approach provides a potentially replicable framework that links policy completeness and smart monitoring to measurable resilience outcomes. The study offers evidence-based policy insights for enhancing energy resilience in disaster-prone regions, including a synergistic institution–funding mechanism.
Gao et al. (Sun,) studied this question.