Combining Grid Enhancing Technologies with Advanced Transmission Technologies: Dynamic Line Rating and Static Line Uprating

By Dr Niall Coogan - CEO & Co-Founder, AssetCool

This article demonstrates how combining Dynamic Line Ratings (DLR) with heat-dissipating conductor coatings (Static Line Uprating) significantly boosts average overhead transmission capacity while mitigating weather-induced rating shortfalls below static baselines. It was written Based on research published by the AssetCool team and presented in a CIGRE paper written by Dr Oliver Higbee and Ernest Khong.

Executive Summary

DLR has demonstrated substantial average capacity uplifts on overhead transmission and distribution circuits. By recalculating each line’s thermal rating hourly using local weather conditions, DLR provides a more representative estimate of its weather-dependent current-carrying capability than a fixed static rating. However, during a non-negligible number of operating hours, actual conditions may be less favorable than those assumed in the base Static Line Rating (SLR), resulting in a lower DLR rating.

This is a logical consequence of how SLRs are set. Utilities balance network utilisation and risk by adopting conservative, but not absolute worst-case, environmental assumptions, supported by operational headroom. Designing around the worst conditions conceivable would drastically constrain network capacity. Localised sensing and DLR simply reveal when actual conditions are more adverse than the assumptions underpinning the SLR.

Relatedly, AssetCool is operationalising Static Line Uprating: the robotic application of capacity-enhancing coatings to thermally constrained overhead lines. This addresses a different part of the thermal equation by increasing the conductor’s underlying ampacity through improved radiative cooling. DLR captures changes in weather-dependent cooling, primarily wind based convective cooling; SLU changes the conductor’s surface properties so it can carry more current under the same conditions relative to an uncoated conductor, permanently.

Deploying SLU and DLR on the same circuits, conceptually, is very powerful. This article summarises and expands a research paper presented at the CIGRE Paris Session 2026 - In this article AssetCool simulated the California Test System using assumed conductor ratings and hourly reanalysis weather for 2024. Three cases were compared:

• Static Line Ratings

• Dynamic Line Ratings

• Coated Dynamic Line Ratings (C-DLR): DLR calculated for statically uprated conductors following modelled system-wide coating deployment.

  
  

The model indicates that combining SLU with DLR can raise average dynamic ratings while materially reducing the frequency, duration and severity of below-SLR conditions:

• Higher average rating: Mean uplift relative to legacy SLR increased from 58.8% with DLR to 66.8% with C-DLR.

• Fewer affected lines: The proportion of modelled lines experiencing at least one continuous below-SLR period of four hours or more fell from 71% with DLR to 5% with C-DLR.

• Far fewer below-SLR line-hours: Across the network and year, below-SLR conditions fell from 408,730 line-hours (0.47%) with DLR to 6,800 line-hours (0.008%) with C-DLR, a 98.3% reduction. In the DLR scenario, below-SLR line-hours, 404,595 (98.99%) occurred within events lasting at least four hours.

• Severe downside mitigation: The maximum annual below-SLR exposure recorded by any single circuit fell from 728 hours (8.3% of the year) with DLR to 79 hours (0.9%) with C-DLR, an 89.1% reduction.

• Less severe derating: The greatest modelled shortfall relative to SLR improved from 35.8% below SLR with DLR to 13.5% below SLR with C-DLR.

  
  

Table 1 summarises these figures.

Metric	DLR	C-DLR	Delta/Change
Mean uplift over SLR	58.8%	66.8%	+8.0 percentage points (+13.6% relative)
Lines experiencing a ≥4-hour below-SLR event	71%	5%	93.0% relative reduction
Below-SLR line-hours	0.47%	0.008%	98.3% relative reduction
Maximum annual below-SLR hours for any circuit	728 hours (8.3%)	79 hours (0.9%)	89.1% relative reduction
Greatest shortfall below SLR	35.8%	13.5%	62.3% reduction in magnitude

Table 1: Summary of Results

The most unfavourable modelled weather combined 0.05 m/s wind with a 50°C ambient temperature, substantially more adverse than the SLR assumptions of 0.61 m/s wind and 40°C. Rating every line for this outlier throughout the year would unnecessarily suppress usable capacity.

DLR identifies such conditions when they occur; in the model, C-DLR reduced, but did not eliminate, the associated downside while adding capacity under more favourable conditions.

AssetCool has developed a range of proprietary coatings, high voltage aerial robotics, QA/QC systems and field deployment infrastructure for upgrading existing overhead lines. DLR can likewise be deployed on existing circuits, without an outage.

The modelled combination is promising and now requires circuit-level empirical validation. We look forward to evidencing C-DLR empirically in the near future.

Figure 1: CapacityAir-1 applying AssetCool’s SE02 coating to an overhead power line, the platform is specifically adapted to apply coating to power lines with obstacles, including various types of on-line DLR sensors.

Introduction

In April 2026, California alone curtailed 1.46 million MWh of renewable output, equivalent to approximately 18% of its grid-scale wind and solar generation that month [1]. Congestion is an important contributor to curtailment, although individual constraints can be thermal, voltage, stability, contingency-related or operational [2].

Thermal ratings for overhead conductors are often the hardest to address. These conductors are suspended tens of meters in the air, spatially diffuse across tens of miles of variable properties, roads and sensitive environments. Physical interventions to upgrade these require paramount safety considerations, significant site crews, access and heavy machinery. It is inherently difficult. Further, de-energising the line for prolonged periods for physical upgrades is often preclusive operationally or economically.

This is reflected in the data: the United States completed 888 miles of new high-voltage transmission in 2024, including 322 miles at 345 kV and above [3]. Drawing on the Department of Energy’s National Transmission Planning Study [4], Grid Strategies estimates that roughly 5,000 miles of high-capacity transmission are needed each year [3]. The gap points to a structural delivery challenge for major infrastructure and strengthens the case for approaches that extract more capacity from existing corridors.

In CAISO, the 32 renewable and storage projects reaching commercial operation in 2024 had spent an average of 9.2 years in the interconnection queue [5]. California nevertheless needs substantial transmission capacity sooner. CAISO’s approved 2025–2026 transmission plan recommends 38 projects at an estimated $6.7 billion over the next decade; more than half of both the projects and cost are driven by forecast load growth. Its underlying projections show load rising by 15 GW by 2035 and 20 GW by 2040, alongside a need for more than 74 GW and 107 GW of additional installed resource capacity, respectively [6].

The market has delivered alternative solutions to address this thermal rating problem. Reconductoring with advanced conductors can transmit ~2x the capacity whilst utilising the same towers, due to the higher ampacity-to-weight ratio. Dynamic Line Rating (DLR) works to provide the actual thermal capacity of the network by providing circuit specific near-real time ratings, reflective of the actual rating of the line. This offers substantial potential uplifts over the inherently conservative Static Line Ratings, historically adopted by transmission network operators.

However, there are tradeoffs. Reconductoring physically upgrades the electrical and mechanical asset, providing ~2x in fixed firm capacity, but may bring extended outages and a longer delivery programme. DLR can be deployed in months, changing the operating envelope using measured or forecast conditions, but there are known constraints, which are reviewed in this article.

At AssetCool, we are driving forward a third solution: Static Line Uprating or in short, SLU. Robotically upgrading the grid with capacity enhancing coatings. Capacity enhancing coatings work to radiatively cool lines by maximising solar reflectivity and thermal emissivity/heat dissipation. It therefore changes two terms in the conductor heat balance while conductor geometry, maximum allowable temperature and the rating methodology remain fixed. The same current produces a lower equilibrium temperature; alternatively, up to 30% higher current can be carried within the same temperature limit. Over the past 5 years, we have developed the (extensive, deep, incredible) technology stack to permit physical upgrades, providing fixed increases in firm capacity, over spatially diffuse, live, overhead lines. Deployable in weeks, with a minimal site crew, limited access requirements, and no outages required.

Critically, this solution is inherently synergistic with both existing market solutions. Capacity enhancing coatings can be applied in the factory to advanced conductors, such as via our partnership with one of the world’s largest conductor manufacturers — APAR Industries. Data-centre-scale capacity additions can be added to circuits as an optional manufacturing extra, with no implications on weight or the structural design of the line.

The same complementarity applies to DLR deployments. DLR is a mature operational technology with substantial evidence of capacity uplift, but two constraints remain. First, its weather-dependent variability can complicate the connection of continuous large loads such as data centres. Second, field monitoring can reveal hours when a static or seasonal rating is higher than the line’s weather-dependent capability. That information improves operational awareness, but it can also require temporary derating.

Published utility studies illustrate the range. LineVision and AES reported [7] a 43% average uplift on a monitored 345 kV line, with DLR above SLR 97% of the time . Great River Energy reported [8] 48.9% more summer capacity and 63% more during peak-demand hours, while DLR was below the seasonal baseline for 2–3% of the period . A 110 kV demonstration found SLR above DLR for 4.14% of the study period despite a 26.6% average uplift [9]. A National Grid and LineVision study found DLR above SLR 93% of the time in summer and 77% in winter, with average uplifts of 33.8% and 19.3%, respectively [10]. Elia reported gains across 35 Belgian lines for 98% of the observed time [11]. The trade off between a circuit getting 20–60% average capacity uplifts, with typically 2–3% reductions in operating hours below SLR is one for a utility to analyse. However, through the targeted deployment of Static Line Uprating, this could be nearly-completely mitigated.

Capacity enhancing coatings radiatively cool conductors. Radiation’s share of total heat dissipation is greatest in low-wind conditions, precisely where the DLR converges with the conservative SLR assumed by utilities, and the DLR goes below the SLR. With SLU, the physical conductor properties are changed and therefore the benefit appears in both the static and dynamic calculations. DLR continues to capture variation in convective cooling, while the coating shifts the baseline from which the dynamic rating is calculated. Therefore there is an opportunity to utilise Static Line Uprating (SLU) “to lift the baseline”, adding fixed, firm capacity to overhead circuits, in addition to DLR, which provides peak ratings uplifts during periods of more favourable weather.

A research paper exploring the SLU–DLR combination was presented at the CIGRE Paris Session 2026 [12]. This article extends the discussion and reflects the updated analysis reported below.

Figure 2: Swarm of Capacity-1 robots applying coating on overhead power lines, United Kingdom, 2025.

CAISO Scale Modelling of C-DLR

The study builds on previous work by Luffman and Desai [13] and uses the California Test System (CATS) developed by Taylor et al. [14]: 8,870 buses, 9,861 retained transmission lines and 2,149 generators. It applies 8,784 hourly weather intervals for 2024, sourced from ERA5 and mapped to network buses, then calculates ratings under IEEE 738. In practical terms, the model estimates how much power each line could safely carry in every hour of the leap year using local weather. As a simplifying assumption, all investigated lines are represented as ACSR Drake with an 80°C maximum conductor temperature, split among four voltage levels of 66, 115, 230 and 500 kV. The static case uses 40°C ambient temperature, 1,000 W/m² solar irradiance and 0.61 m/s perpendicular wind.

Three cases are compared:

1. Standard/legacy SLR

2. DLR

3. “Coating-DLR” — C-DLR. Dynamic line ratings with network wide coated conductors.

Figure 3: Transmission grid managed by SCE part of CAISO, Los-Angeles, CA, Photo by Will Goodman on Unsplash

Results

SLR versus SLU (static comparison). Under the fixed static weather assumptions, the uncoated ACSR Drake circuit has a legacy SLR of 275 MW power carrying capacity, in a 115kV operation. Changing only the conductor’s surface properties produces an SLU rating of 332 MW at the same 80°C temperature limit. The 57 MW difference is a 20.9% uplift. The following table shows the actual capacity uplifts under different voltage settings:

Voltage Level	Net Power (MW)	Coated Net Power (MW)	Uplift Achieved By Coating
66kV	156	189	32 MW (20.6%)
115kV	275	332	57 MW (20.9%)
230kV	553	669	116 MW (21%)
500kV	1205	1459	254 MW (21.1%)

Table 2: Static Line Ratings VS Static Line Uprating of ASCR Drake, under varying voltages levels

SLU at the original SLR loading. If the additional capacity is not used, the coating instead creates operating margin. Holding current at the original SLR value reduces the modelled conductor temperature from 80°C to 67.4°C, in turn reducing AC resistance by approximately 4%. The same intervention can therefore provide either additional ampacity or lower temperature and resistance at the original loading.

DLR versus C-DLR (dynamic comparison). Across the full network and year, both dynamic cases are reported relative to the uncoated legacy SLR baseline. Uncoated DLR produces a mean uplift of 58.8%; C-DLR produces a mean uplift of 66.8%. The coating therefore adds additional 8.0 percentage points of additional average capacity.

Figure 4: Modelled annual-average uplift from DLR and coated DLR across the California Test System.

Adverse-weather performance of DLR and CDLR relative to SLR. Under the most unfavourable modelled weather (0.05 m/s wind and 50°C ambient temperature), in the uncoated DLR scenario, the maximum shortfall is 35.8% below legacy SLR. This is 13.5% below legacy SLR for C-DLR - significantly less shortfall. N.B. These conditions are substantially more adverse than the SLR assumptions of 0.61 m/s wind and 40°C.

In the DLR scenario, 408,730 line-hours were below SLR (0.47%). Of these, 404,595 line-hours (98.99%) occurred within events lasting at least four hours. The most exposed circuit accumulated 728 below-SLR hours, equivalent to 8.3% of the year.

In the C-DLR scenario, 6,800 line-hours were below SLR (0.008%). The maximum annual exposure for any single circuit was 79 below-SLR hours, or 0.9% of the year.

Four-hour emergency-rating assessment. In the DLR case, 71% of modelled lines experienced at least one continuous event of four hours or more below legacy SLR; in the C-DLR case, the share was 5%.

Figure 5: Share of modelled DLR and C-DLR lines falling below the legacy SLR within a four-hour emergency-rating assessment.

Discussions and Future Outlook

The published case studies reviewed above show that the share of time DLR falls below SLR varies materially with the static baseline, season, route and weather [7]–[11]. In this model, below-SLR conditions account for 0.47% of DLR line-hours, which is lower than the 2–3% reported across the reviewed case studies. This is likely due to the assumptions adopted in the model (40°C ambient temperature, 1,000 W/m² solar irradiance and 0.61 m/s perpendicular wind) being suitably conservative.

These periods are infrequent at network level, but their operational importance depends on duration, severity and concentration, the next limiting constraint on each circuit, and the timing of congestion - These factors are interdependent. Optimising conductor surface properties can nevertheless reduce the frequency, duration and severity of below-SLR exposure, changing the downside distribution. The share of modelled lines experiencing at least one continuous below-SLR period of four hours or more falls from 71% with DLR to 5% with C-DLR, a 93.0% relative reduction. Across the network and year, total below-SLR exposure falls by 98.3%. These reductions could provide material operational value, although that value is not quantified by the present screening analysis.

Beyond this, the 35.8% below-SLR result has physical implications, but only if loading reaches the legacy static rating during the adverse conditions. Under the most unfavourable modelled weather, DLR is 35.8% below SLR, so the contemporaneous weather-adjusted ampacity is 64.2% of SLR. If the circuit were loaded to the legacy SLR at that time, the current would exceed the weather-adjusted ampacity and could drive the conductor above its assumed 80°C limit. Based on IEEE-738, with the SLR, in the most unfavourable conditions, this conductor would have operated at 109°C instead of the maximal 80°C limit in these conditions.

The relationship between conductor temperature and physical ageing has been well studied [15]. Physical ageing becomes a concern when the true temperature–time history approaches or exceeds the limits of the conductor, connectors or clearances. Overhead conductor systems are coupled electro-mechanical assets: temperature changes sag, tension and load-sharing among strands and the core, while fixtures, fittings, aeolian vibration and environmental reactions add interacting stresses. Sustained or repeated high-temperature exposure can accelerate metallurgical creep and permanent elongation, reduce clearance and, in conventional hard-drawn aluminium, reduce tensile strength through annealing [15]–[18]. At material level, this can involve microstructural recovery, texture evolution, subgrain growth and recrystallisation; in age-hardenable aluminium alloys, precipitate growth or over-ageing can also reduce strength [16]. ACSR strength loss depends on cumulative temperature–time exposure as well as manufacturing route and prior condition [17]. These effects also depend on conductor technology, for example, HTLS designs use annealed aluminium, thermally resistant alloys or low-expansion cores specifically to tolerate operating regimes that would be limiting for conventional ACSR [15], [17], [18]. Excessive thermal sag is therefore primarily a clearance risk; permanent deformation arises from creep and other inelastic mechanisms, not from sag alone.

Ageing is similarly asset- and environment-specific. Field studies of conductors in service for decades identify corrosion pitting, oxidation or loss of galvanising, grease degradation, fretting/fatigue and measurable changes in structural, microstructural and elastoplastic properties [19]–[21]. Moisture, salt and pollutants, galvanic coupling, protective systems and local mechanical damage are usually the primary controls for corrosion, although elevated temperature can accelerate oxidation and the ageing of connectors and accessories [15], [19].

Put simply, operating without adequate information about actual conductor temperature can drive assets harder, but ageing is governed by a temperature–time–environment relationship that evolves over decades and depends on asset condition. Historically, conservative rating headroom reduced exposure to these uncertainties; as utilisation rises, explicit thermal limits, asset condition and operating history become more important. DLR can provide the situational awareness needed to keep operation within actual thermal and clearance constraints, while SLU lowers conductor temperature for a given current. This study does not calculate material degradation or life extension; it identifies a physically plausible risk pathway and a monitoring and mitigation opportunity.

An open question remains: is the residual downside under C-DLR — a maximum 79 hours of annual below-SLR exposure for any single circuit and a separate maximum instantaneous shortfall of 13.5% — an acceptable operational trade-off for a 66.8% mean network-wide rating uplift over legacy SLR? These maxima need not occur on the same circuit or at the same time.

Figure 6: Close-up of a Capacity-1 robot operating on an overhead power line.

Practically speaking, network-wide deployment could use a more targeted strategy. A span-aware operational DLR system can reveal recurrently limiting spans, such as sheltered, low-wind or tree-covered sections, that constrain the rating of an otherwise higher-performing circuit.

The present bus-mapped screening model does not resolve actual span-level microclimates, so this is a proposed deployment application rather than a demonstrated output of the study. Applying SLU selectively at these locations could offer a lower-intervention route to improving the performance of the combined deployment. In this role, DLR can help determine both the safe dynamic rating and where a permanent physical intervention is most valuable.

In terms of limitations, the present study remains a screening analysis. It does not simulate actual circuit loading, fixed-current conductor temperatures or degradation histories, and therefore does not quantify ageing or life extension. It also does not calculate avoided curtailment, congestion rent, interconnection deliverability or investment deferral. Quantifying these outcomes would require production-cost and security-constrained power-flow studies incorporating actual asset ratings, conductor types, outage states and dispatch. Similarly, although CATS is geographically representative, the use of a common ACSR Drake conductor and bus-mapped reanalysis weather does not reproduce the actual conductor mix, span-level microclimates or operating constraints of the CAISO system. The relative changes in rating and below-SLR exposure are therefore more informative than estimates of absolute transferable megawatts.

The next stage should progressively replace these screening assumptions with asset-specific ratings and conductor data, span-level weather validation, live or representative power flows, outage and contingency states, and production-cost analysis. A jointly governed field trial on a circuit with operational DLR would then provide the decisive test: whether the modelled improvements in average uplift and the reductions in below-SLR frequency, duration, severity and circuit-level exposure are realised in service. The trial should also record actual current and conductor temperature, sag or clearance, thermal cycling, connector and splice hot spots, limiting-span weather, coating condition, and baseline and follow-up inspection or NDT results. This would test whether the rating improvements translate into lower thermal stress without assuming life extension in advance.

Work with AssetCool to Verify this Empirically!

AssetCool is inviting transmission owners and system operators with operational DLR deployments to nominate a thermally constrained circuit for a jointly governed field-verification programme. We are also interested in talking with DLR suppliers, who unveil regularly constrained circuits or spans, for targeted uprating approaches.

AssetCool combines remotely operated robotic deployment on energized overhead conductors with in-field QA/QC and traceability. Utilities can review full coating technical data rooms covering material performance, engineering, safety and application controls, alongside independent thermal performance data from transmission-line deployments. More than 200 km of robotic work has been completed globally, providing a substantial operational base for the next stage of utility qualification.

Let’s get to work.

Contact AssetCool at info@assetcool.com.

Figure 7: The AssetCool team after completing a field deployment in the United States, 2026.

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