Static Line Uprating: In-situ Modification of Overhead Conductor Properties for Continuous Capacity Enhancements and Synergy with Dynamic Line Ratings

(SLR), assuming conservative weather conditions. While reliable, SLR underutilises real conductor capacity most of the time. Dynamic Line Ratings (DLR), an operational approach adjusting ratings based on real-time weather and line measurements, has emerged to address this. However, DLR’s benefits are variable because they depend on prevailing weather conditions, and its deployment is constrained to locations where the SLR assumption is sufficiently conservative relative to actual conditions - such as areas where wind speeds may be greater than the fixed SLR assumption. In some cases, the DLR rating can fall below that

SLR based on a difference between wind speed, solar intensity and ambient temperature assumptions used in setting the SLR.

This paper presents Static Line Uprating (SLU) as a distinct yet complementary field technology. SLU involves applying engineered coatings to overhead conductors that reduce solar absorptivity (α) and increase thermal emissivity (ε). This amounts to a physical modification of the line to result in a 15–30% higher continuous current-carrying capacity, when utilising the SLR assumptions. SLU thus increases baseline reliability, particularly in low-wind, high-irradiance periods when DLR shows there is no room to increase circuit current beyond the SLR.

In this paper SLU is outlined conceptually, the components involved including spectrally selective coatings, and in-situ power line coating robotics are presented [7,8,9,10]. Distinctions and synergies with DLR in a system wide analysis of DLR impact on the California Independent

System Operator are explored. The analysis builds on prior work by Luffman & Desai (2025), who modelled DLR adoption in the CAISO grid and found it increased average line ratings by

~24%, enabling ~22% more solar and ~10% more wind interconnection capacity [11].

This California Test System (CATS) model, a geographically accurate, high-fidelity dataset of the CAISO grid comprising 8,870 buses, 10,162 transmission lines, and 2,149 generators, is extended to incorporate SLU-modified conductor properties. Using the same bus-level weather, load, and generation profiles, we assess how SLU shifts both SLR and DLR distributions.

Results show that applying SLU meaningfully increases the average capacity uplift by 18% and when combined with DLR (C-DLR) critically reduces the instances where DLR is below the

SLR by over 80%. This ensures higher minimum guaranteed capacity while preserving the operational flexibility of DLR when favourable conditions occur.

This paper concludes by recommending a hybrid deployment strategy: SLU to improve baseline capacity and reliability, combined with DLR to capture real-time favourable conditions.

By demonstrating the complementary roles of SLU and DLR in CAISO’s high-fidelity model, this study provides a rapidly deployable, low-cost, robust, data-driven pathway to increase renewable integration, enhance grid reliability, and defer costly transmission upgrades.