Integrating Conductor Health into Dynamic Line Rating and Unit Commitment under Wind Uncertainty
For power system operators, this work provides a method to safely increase transmission utilization under uncertainty while accounting for conductor aging, reducing costs and renewable curtailment.
This paper proposes a Conductor Health-Aware Unit Commitment (CHA-UC) model that internalizes risk-based depreciation costs from elevated temperature operation under dynamic line rating and wind uncertainty. On the Texas 123-bus system, CHA-UC reduces total cost by 0.75% and renewable curtailment by 82% compared to static line rating, outperforming quantile regression forest-based methods.
Dynamic line rating (DLR) enables greater utilization of existing transmission lines by leveraging real-time weather data. However, the elevated temperature operation (ETO) of conductors under DLR, particularly in the presence of uncertainty, is often overlooked, despite its long-term impact on conductor health. This paper addresses ETO under DLR and wind power uncertainty by 1) quantifying risk-based depreciation costs associated with ETO, 2) characterizing correlation-driven ETO risk from wind power and DLR forecast errors, and 3) proposing a Conductor Health-Aware Unit Commitment (CHA-UC) that internalizes these costs in operational decisions. CHA-UC incorporates a robust linear approximation of conductor temperature and integrates expected depreciation costs due to hourly ETO into the objective function. Case studies on the Texas 123-bus backbone test system demonstrate that the proposed CHA-UC model reduces the total cost by 0.75\% and renewable curtailment by 82\% compared to static line rating (SLR) and outperforms quantile regression forest-based methods, while conventional DLR operation without risk consideration resulted in higher costs due to excessive ETO. Further analysis shows that CHA-UC achieves safer line utilization by shifting generator commitments and endogenously adapting to uncertainty correlation, relaxing flows under risk-hedging conditions and tightening flows under risk-amplifying conditions.