This paper presents a lightweight method for assessing the resilience of power distribution systems that integrates climate and infrastructure data through impact chains and a probabilistic approach, while minimizing data integration and implementation complexity. The method is demonstrated for heatwave hazards by combining network characteristics, failure probabilities of heat-sensitive components (e.g., medium-voltage cable joints), and location-specific climate projections to generate spatial maps of failure risk and network resilience. These maps support the identification and prioritization of critical components requiring intervention. Critical segments are then further analyzed using probabilistic resilience metrics to compare alternative adaptation strategies. Overall, this work contributes a practically applicable, low-complexity methodology for identifying the weakest portions of distribution networks, along with a more in-depth probabilistic approach for assessing their climate resilience. The com-prehensive framework is illustrated through a case study of a representative portion of the Italian electricity distribution system in the urban area of Rome. It is implemented in a test environment that reflects realistic distribution network data structures and automatically integrates climate data from established online repositories.
Calcara et al. (Fri,) studied this question.