A Diagnostics Framework for Underground Power Cables Lifetime Estimation Under Uncertainty

Power cables are critical assets for the reliable operation of grid. The cable lifetime is generally estimated from conductor temperature, and associated reduction. However, these tasks intricate due to complex physics-of-failure (PoF) degradation mechanism cable. This further complicated with different sources uncertainty that affect estimation. Generally, simplified or deterministic PoF models adopted resulting in non-accurate decision-making under uncertainty. In contrast, integration uncertainties leads a probabilistic process impacting directly on flexibility adopt decisions. Accordingly, this paper presents novel estimation framework connects data-driven PoF-based operation, through Bayesian state-estimation techniques. estimates health state, infers confidence intervals aid proposed approach validated case study configuration parameters, effect measurement errors evaluated sensitivity analysis. Results demonstrate ambient temperature influence more than load errors, greater estimate.