How Dynamic Line Rating (DLR) Works to Reduce Curtailment

In many power grids around the world, energy curtailment is a big problem. Renewable sources like wind and solar may produce more electricity than static transmission lines can safely carry under worst case assumptions (Renewable and Sustainable Energy Reviews).

That means grid operators must curtail or shut off some generation even though it could have been delivered.

Power grid curtailment not only wastes clean energy it also costs utilities and consumers. However, Dynamic Line Rating (DLR) is a technology that uses real environmental conductors and operational data to adapt line capacity in real time.

In this post we epxlore what DLR is, how it works and importantly how real time dynamic line rating helps reduce curtailment.

Dynamic Line Rating Technology

Dynamic Line Rating refers to a set of technologies and methods used to determine in near real time or adaptively how much electrical current a transmission line can carry safely given the actual environmental and conductor conditions.

Unlike static ratings which assume worst case ambient temperature, wind speed, solar radiation and assume fixed conductor properties such as sag tension ageing etc DLR takes many more variables into account and updates line ampacity as conditions change. 

This gives operators a more accurate, often higher safe line capacity. Interestingly, Enline DLR Solutions offers a robust sensorless approach powered by digital twin and AI techniques achieving high accuracy (over 95%) compared to conductor mounted sensors (Eurelectric - Powering People)

There are two broad types of the Dynamic Line Rating.  These are the sensor based and sensorless DLR. 

Sensor based DLR uses measurements directly on the line for example, conductor temperature sag tension plus nearby weather sensors.

Sensorless DLR uses weather station data, remote sensing modelling or digital twins to estimate what the conductor behavior is likely to be without putting sensors on many sections of the line. Interestingly, this is what we do at Enline. 

Enline combines multiple meteorological sources virtual or physical weather stations plus known physical models for its digital twin (Eurelectric - Powering People)

Dynamic Line Rating Benefits

Dynamic Line Rating delivers multiple benefits to utilities grid operators and society. One of the clearest is the ability to reduce curtailment of renewable energy because when ambient conditions are favorable. 

For example, cooler temperatures, good wind and lower solar heating lines can carry more current safely than static ratings would allow. That means more wind and solar generation can be dispatched.

Other benefits include:

• Increased transmission capacity without building new lines or reconductoring existing ones. Studies and field deployments show that DLR often unlocks 30-50% more capacity over static or Ambient Adjusted Ratings AAR.

• Reduced congestion and bottlenecks on the power grid meaning less cost associated with grid inefficiencies less risk of overloads.

• Better integration of renewables like wind and solar which are intermittent DLR allows the grid to adapt to when generation is high and environmental conditions allow safe transmission.

• Cost savings avoiding or postponing expensive capital projects such as new lines reconductor work lowering losses lowering risk of regulatory penalties (The Department of Energy's Energy.gov)

How Does Dynamic Line Rating Work?

To understand how real-time dynamic line rating works, which is critical to reducing grid curtailment, you need to look at its components and workflow.

Here are the key steps:

Data Inputs: Meteorological data, including ambient temperature, wind speed and direction, solar radiation; conductor properties such as material, cross-section, age, emissivity, absorptivity, electrical loading, sag, tension, line geometry. Enline’s digital twin ingests these (Eurelectric - Powering People).

Model Simulation Digital Twin: A physics-based model—thermal, mechanical, sometimes electromagnetic, simulates conductor behavior such as heating, cooling, sag, etc. The digital twin is updated continuously as environmental data come in. Enline’s system uses AI plus physics models via its digital twin to predict conductor behavior and forecast ampacity.

Rating Calculation: Based on current and forecasted conditions, compute ampacity—that is, how much current can flow safely, given constraints such as thermal limits and clearance sag. The operator then determines what safe maximum line load is, given conductor constraints. Real-time dynamic line rating process is continuous or frequent (minutes, hourly, etc.) (ENTSOE).

Operational Integration: The new dynamic rating must feed into dispatch decisions, grid control systems, and energy management systems. When ratings go up, grid operators can allow more flow; when conditions worsen, they reduce. This helps avoid energy curtailment when renewable generation is available.

Forecasting Predictive Module: It is not just real-time; forecasting matters for planning. For example, knowing that in coming hours a hot midday will reduce capacity means dispatch planning can adapt. Enline offers 7-day ahead forecasting via weather models and their digital twin (Eurelectric - Powering People).

Types of Dynamic Line Rating (DLR) Methods 

Dynamic Line Rating (DLR) methods are generally classified based on how they are implemented and the type of data they rely on. 

1. Dynamic Line Rating Sensors
 

Sensor-based DLR relies on physical devices installed on or near transmission lines to capture data that models might not estimate perfectly. The types include:

• Conductor temperature sensors: Measure how hot a conductor is in real time. Heat comes from both current flow (I²R losses) and external heat (ambient temperature, sun). If too hot, the conductor expands, sag increases. Safe operating limits are based on maximum conductor temperature.
  
  
  

• Sag tension sensors: Measure droop and mechanical tension, because sag is affected by temperature, current, tension, and wind. Tall sag can violate clearance rules above ground or over obstacles, which is a safety issue (ENTSOE).
  
  
  

• Ambient sensors: Weather stations measuring ambient temperature, wind speed, direction, solar radiation. These are often co-located or nearby. They help feed the models that determine cooling of conductors.
  
  
  

These sensors give detailed, accurate data. But installing many such sensors can be expensive, maintenance-intensive, and in many grids coverage is uneven. That is where sensorless or hybrid systems have advantages.

2. Sensorless Dynamic Line Rating

Sensorless DLR refers to techniques and systems that estimate dynamic line rating without or with very few physical sensors on the conductor spans Key aspects include:

• Weather modelling, using remote weather data sources, satellites, weather stations and meteorological providers to get ambient temperature, wind speed & direction and solar radiation. Enline combines multiple meteorological sources virtual and physical weather stations for its sensorless DLR.

• Digital twin simulation using calibrated physics based and electromechanical models to simulate conductor temperature, sag tension etc., without needing sensors everywhere.

• Hybrid approaches sometimes use some sensors plus modelling to validate the estimates and calibrate. This can reduce cost while maintaining accuracy.

Sensorless DLR is very attractive where sensor deployment is difficult or for fast scaling across many lines. It reduces hardware cost avoids outages for sensor installation simplifies maintenance But good modelling and data quality are essential

Real Time Dynamic Line Rating

Real time dynamic line rating means updating line capacity frequently, for example, every few minutes to hourly intervals, based on current environmental and loading conditions rather than relying on conservative static ratings or occasional adjustments. 

Real time dynamic line rating is the most powerful dimension of DLR when the goal is to reduce curtailment. Because renewable generation such as solar wind varies by hour or minute, real time dynamic line rating allows grid operators to capture moments when lines could safely carry extra power. 

Without real time adjustment static ratings force operators to assume worst case all the time resulting in unused capacity.

Real time updates also help prevent overloads or thermal damage when ambient conditions worsen the line rating is reduced to maintain safety. This protects safety and reliability.

Enline’s platform offers real time monitoring and forecasting giving dispatch centers visibility into current and near future line capacity. This lets operators plan dispatch of renewable energy so as to reduce curtailment aligning generation with transmission capacity rather than curtailing generation because of static line constraints 

How DLR Works to Reduce Curtailment

Putting it all together here is how Dynamic Line Rating actually helps reduce energy curtailment and make grids more efficient

• Matching transmission capacity to actual conditions: Rather than assuming the worst case always, DLR allows grid operators to use real time dynamic line rating to identify moments when more power, especially from variable renewables can be transmitted. So, instead of curtailment shutting off generation you dispatch fully when possible.

• Avoiding bottlenecks: Static line ratings often lead to congestion in certain corridors so even if generation is ready, it cannot reach load or grid connection points. DLR helps relieve those bottlenecks periodically allowing renewable energy to flow when lines are not thermally constrained

• Better forecasting and planning: With forecasting, Enline provides 7-day ahead via digital twin plus weather data. Operators can schedule generation, storage, dispatch, or demand management in ways that anticipate when curtailment would otherwise occur and avoid it.

• Flexible grid operation: DLR supports flexible dispatch, allowing for more aggressive use of clean generation when conditions allow and backing off when necessary without risking line damage. This flexibility reduces overall renewable curtailment.

• Cost and sustainability benefits: Reducing curtailment means more clean energy gets used, reducing fossil backup, improving economics of renewable investment, and helping meet emissions net-zero goals. Enline’s DLR solution explicitly cites reducing power grid curtailment and unlocking renewable integration as key use cases.

In a comparison Germany’s system modelling found that using DLR extensively in a high renewable scenario about 80% saved several percent of total system cost largely by reducing storage and curtailment needs (arXiv)

Because Enline’s solution is largely software modelling, it has minimal hardware cost, lower maintenance, fast rollout and is highly scalable These characteristics help reduce curtailment risk in many grids.

FAQs

How to mitigate curtailment risk?

Curtailment risk can be mitigated by improved grid planning, better forecasting of generation and load demand, demand-side management, energy storage, and enhanced transmission capacity. 

What is a DLR system?
A DLR (Dynamic Line Rating) system is a setup combining environmental monitoring (such as weather data), physical electromechanical modelling, optionally sensors, and computational modules to compute the safe current capacity (ampacity) of transmission lines in real time or near real time. 

How do you calculate DLR?

You calculate DLR by gathering inputs: ambient temperature, wind speed and direction, solar radiation, conductor properties (type, cross section, emissivity, absorptivity), electrical loading, sag, tension, etc. Then, use a thermal-mechanical model or digital twin simulation to estimate conductor temperature and capacity. 

How to avoid curtailment?
Avoiding curtailment involves multiple strategies, such as improving transmission capacity through DLR, enhancing grid flexibility, storage, and demand response, improving forecasting of renewable generation and demand, and aligning generation dispatch with periods of available capacity.

How does wind curtailment work?

Wind curtailment happens when wind turbines are shut down or scaled back because the grid cannot accept more power due to transmission limits, stability constraints, or oversupply. Even when wind is blowing strongly, if the line rating is too low, often due to static rating assumptions or if the grid is congested, the output must be curtailed.