System‐Level Risk Quantification for Distribution Networks Based on Stage‐Aware Degradation Modelling of Cable Joints

ABSTRACT

Cable joints are among the most failure‐prone components in distribution cable systems, making their condition monitoring essential for reliable operation and maintenance in distribution networks. Existing discharge‐based monitoring methods typically provide binary defect identification, leaving degradation‐stage information in discharge observations underexploited and limiting their support for fine‐grained risk‐informed maintenance under system‐level impacts. To address this gap, this paper proposes a stage‐aware degradation modelling paradigm for cable joints based on ordered degradation discharge event sequences. A forward‐labelling strategy is introduced to formulate degradation evolution as a supervised learning problem, and a conditional degradation‐to‐failure propensity model (CDPM) is developed to map ordered degradation discharge event sequences to a probability‐related failure‐tendency score for the next degradation event. The failure‐tendency score is further integrated with post‐fault consequence severity to quantify system‐level risk and support maintenance prioritisation in distribution networks. The proposed CDPM and risk quantification framework are evaluated using full‐scale cable‐joint degradation experiments and an improved 62‐bus distribution network.