Towards climate-resilient cities: assessing and planning urban energy demand under extreme climate events

The accelerating intensification of extreme climate events necessitates a paradigm shift from reliability-based to resilience-oriented urban energy planning. However, existing methodologies often lack the spatial resolution and structural representation needed to capture localized grid bottlenecks driven by climate-induced demand surges. This paper proposes an integrated, demand-centered framework that identifies representative extreme events using threshold-based climate criteria, constructs node-level climate-stressed demand through demand amplification, quantifies Energy Not Supplied (ENS) under distribution-level grid-connection capacity constraints, and evaluates resilience-oriented capacity planning through cost–constrained optimization. Applied to a dense urban district in Wuxi, China, the framework reveals a pronounced vulnerability asymmetry: significant ENS emerges only under heatwave conditions, whereas cold spells do not trigger capacity violations. ENS is also highly concentrated in both time and space, with a limited subset of high-risk nodes accounting for most system-wide shortfalls. The planning analysis further shows a strongly nonlinear cost–resilience relationship: targeted reinforcement of critical nodes is associated with substantial ENS reduction at relatively low modeled cost, while further expansion yields diminishing returns. These findings demonstrate the value of integrating climate-event identification, spatially explicit demand modeling, and infrastructure constraints within a unified framework for planning-oriented analytical screening of urban resilience interventions. © 2026 Elsevier B.V.