![]() The framework estimates the cable health state and infers confidence intervals to aid decision-making under uncertainty. Accordingly, this paper presents a novel cable lifetime estimation framework that connects data-driven probabilistic uncertainty models with PoF-based operation and degradation models through Bayesian state-estimation techniques. In contrast, the integration of uncertainties leads to a probabilistic decision-making process impacting directly on the flexibility to adopt decisions. Generally, simplified or deterministic PoF models are adopted resulting in non-accurate decision-making under uncertainty. This is further complicated with the different sources of uncertainty that affect the cable lifetime estimation. However, these tasks are intricate due to the complex physicsof-failure (PoF) degradation mechanism of the cable. The cable lifetime is generally estimated from the conductor temperature and associated lifetime reduction. Power cables are critical assets for the reliable operation of the grid.
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