The occurrence of multiple coupled extreme weather disasters leads to complex operational mechanisms and resilience characteristics in ADN. Considering the fault evolution mechanism under multiple extreme weather disasters, a comprehensive resilience evaluation method of ADN is proposed. Firstly, the spatiotemporal evolution patterns of typical extreme weather events such as typhoon, rainstorms, and lightning are analyzed. Based on the material properties of components and the structural characteristics of distribution lines, a mathematical model is developed to quantify the fault probability of ADN under compound extreme weather conditions.Secondly, the post-fault dynamic response characteristics of ADN are investigated. A unified fault modeling approach is established using Monte Carlo sampling combined with Shannon entropy theory to extract the operational and load features of ADN at different stages. Then, a full-stage resilience evaluation metric system is constructed, covering pre-disaster prevention, in-disaster adaptation, and post-disaster recovery. Load performance curves are analyzed from both temporal and power dimensions, and Metric weights for each stage are determined using a hybrid subjective-objective weighting method. The overall system resilience score is calculated using the Euclidean weighted distance method.Finally, a feasible ADN model was constructed for simulation experiments.The simulation results indicate that, the proposed approach can precisely evaluate the overall performance loss of the system subjected to extreme weather events while successfully detecting its resilience-critical segments. With demonstrated accuracy, this framework provides a reliable reference for disaster resilience planning and weak link identification in ADN.
Wen et al. (Thu,) studied this question.