Jake Gentle / Senior Power Engineer / Idaho National Laboratory

Jake Gentle
Believe it or not, sunny skies and calm summer days can negatively impact the ability of the electric grid to transfer power. The naturally occurring heat surrounding transmission lines limits its capacity. A windy or cold day, however, has a cooling effect that allows transmitting more power. That means monitoring the weather lets a utility safely unlock additional grid capacity, which enables more reliability and resilience for the energy infrastructure.

Power lines are heated by the sun and when transmitting power. They are also cooled by the wind and weather.
Utilities across the nation are weighing the trade-offs in providing additional power for homes, industry, and critical services through traditional transmission expansion planning. Overhead transmission lines (TLs) are thermally limited to the amount of electrical current they can carry due to the physical properties of the conductor. Conventionally, the current-carrying capacity of TLs is set to static or seasonally varying values based on a conservative assumption of the environmental conditions (e.g., low wind speed and high ambient air temperature) over the year or season.
However, this approach typically underuses existing transmission assets because these conditions are present only for short periods. In fact, conductor cooling by local weather often provides additional ampacity headroom. Ampacity is a capacity for amperage.
Dynamic line rating (DLR) is a technology that dynamically computes ratings of the TLs based on the heat-energy balance between the total amount of energy absorbed and dissipated in the conductor, as shown in the heat transfer model. (The full heat balance equation appears at the bottom of the image.)

Power lines can sag in low wind conditions.
Real-time monitoring of electrical and environmental parameters can maximize the line capacity use of critical overhead TLs. DLR significantly increases the wind energy hosting capacity of existing TLs because of the natural synergy between wind generation and increased conductor capacity at times of high local wind,.
As utilities consider the cost for updating aging infrastructure to better connect resources to loads, unlocking extra capacity within existing transmission lines becomes attractive. So-called “non-wire” alternatives offer similar advantages in efficiency and reliability of system operations without large investments.
The WindSim Power Line Optimization Solution identifies opportunities for additional power capacity, helping utilities fully use existing transmission and distribution lines throughout their power grid. The software improves system reliability and increases its resilience by monitoring power capacity in real time. This lets the utility better manage existing infrastructure, and provides planners more leeway and flexibility as they prioritize the timing of conductor replacements, line rebuilds, and new construction to meet transmission and distribution expansion plans. It also allows costs to be spread over longer periods.

The illustration of terrain (in orange) shows the large scale often under consideration. The gray boxes along the power lines are more discrete CFD models that consider the local terrain.

The black-line plot shows an improvement in amps for the weather-based ampacity calculation versus a normalized static line rating (SLR – blue line). The terms with (t) are functions of time.
Providing advanced data directly to operations and control centers lets utilities make better decisions based on more accurate and reliable data with less uncertainty and better situational awareness. For example, if a transmission line connects a wind farm to the grid, the same wind that generates power also cools the transmission line. Such a condition allows installing more wind turbines without the cost of transmission enhancements.
In addition, the cost of electricity can be set at a premium because of the limits or congestion in the connection of generation and loads. When tracking weather conditions or, more importantly, weather forecasts, the utility may raise limits to provide additional capacity and alleviate transmission congestion, freeing up access to lower cost generation. Dynamic line rating integrates real-time weather station data with terrain-dependent, computational fluid dynamics, wind-flow modeling, and weather forecasting for determining a real-time line rating and accurately forecasting line ratings. Real-time ratings are available in increments of minutes to hours, and forecast ratings are available in increments of minutes, hours, and even days. The dynamic line rating may extend cost savings for energy consumers because of the additional power transmission.
Static line ratings are based on a fixed set of conservative environmental conditions to establish a limit on the amount of current a line can safely carry without overheating. The innovation uses commercially available weather stations and requires no hardware devices on the actual lines. The data from these stations, in combination with a weather analysis enhanced by computational fluid dynamics, lets utilities safely and confidently use dynamic line ratings instead of the often overly conservative static-line ratings that have been the norm.
The Idaho National Laboratory-WindSim approach allows for the complete coverage of all structure-to-structure spans of the transmission line instead of single-locational measurements.
For more than five years, Idaho National Laboratory has led the development of this weather-based dynamic line rating methodology. It uses computational fluid dynamics and forecasting innovation funded by the U.S. Department of Energy’s Wind Energy Technologies Office, in partnership with WindSim through joint collaboration on the research and development of this tool. The relationship has now advanced the technology for the electricity sector by improving the capability of modeling and transferring weather conditions to every span on the line to accurately perform dynamic line ratings, across a large geographic area with high reliability and certainty.
Weather-based dynamic line rating has been validated by three industry pilots to ensure it provides a smart-grid energy solution for removing artificial or systematic power flow constraints. This is done by informing system planners and grid operators of available transmission and distribution capacity that was previously restricted by static line ratings. The WindSim Power Line Optimization Solution is currently deployed and validated in partnership with other electric utility partners and commercial meteorological solution providers, which includes the U.S. National Oceanic and Atmospheric Administration. WindSim is looking for additional partners to further deploy this solution.
THE VALUE OF COMPUTATIONAL FLUID DYNAMICS
Almost every country has created wind resource maps to find potential windy places suitable for building new wind plants. Modelers use a wide range of methods to create these wind resource maps. Yet new methods are needed to capture the detail required to enable dynamic line rating, which could boost transmission and distribution line capacity by 10 to 40%.
WindSim has developed a wind atlas method using specialized software. The approach enables dynamic line rating modeling and simulation that can expand over hundreds of miles. To be as accurate as possible, the method combines wind speed and wind direction data from smaller simulation areas and is based on scaling against measurements where available.
To create these wind resource maps, scientists have many modeling options to choose from, including mesoscale modeling, linear methods and computational fluid dynamics (CFD).
Using mesoscale models has the advantage that the entire area of interest can be fully covered by one model, while other approaches require combining several simulation areas afterward. However, mesoscale modeling does not reach the horizontal resolution necessary for a reliable wind resource map.
For example, mesoscale models reach their limits in rough terrain because the roughly 1-km resolution is too coarse and forces over-simplified mountainous terrain. By comparison, CFD can simulate the wind flow with a horizontal resolution of 10 m, or even 1 m with specialized data collection. As a result, the CFD approach can better predict the flow pattern within smaller valleys and in very difficult terrain.
For that reason, it has become common to use CFD to generate wind resource maps of smaller areas, and then combine the different simulation areas in the end to see the big picture.
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