The U.S. energy sector is at a crossroads, grappling with a stark reality: the grid’s untapped potential is costing us billions. The demand for energy is surging, and utilities are scrambling to keep up. Yet, the heart of the issue isn’t a lack of physical capacity but rather a failure to maximize the existing grid. This is where grid-enhancing technologies (GETs) come into play, offering a swift and effective solution to our congestion woes.
The recent spike in congestion costs, from $8 billion in 2021 to over $11 billion in 2023, underscores the urgency of the situation. Wild price swings, like the recent ERCOT instance where power prices hit $28,000 per megawatt-hour, highlight the severity of the problem. The average time to complete new transmission lines is a decade, a timeline we simply can’t afford. The Duke University study revealed that nearly 100 GW of large new loads could be handled by U.S. power plants, but transmission constraints are threatening to wipe out this additional capacity.
The solution lies in GETs, which can boost transmission capacity by a third nationwide—quickly. These technologies reduce congestion by re-routing power through less congested lines or by increasing the “speed limit” in any particular line. Dynamic Line Rating (DLR) solutions, for instance, account for the varying capacity of transmission lines based on weather conditions. When it’s cold or windy, a transmission line can transmit up to twice the amount of power due to being cooled, which over the course of a year would add up to 40% more capacity. However, precise weather forecasting specific to individual power line sections has only recently become possible, and utilities have had to make worst-case assumptions for wind, calculating ratings for the cooling conditions of a hot summer day with no wind across the entire network, which leaves significant capacity unused.
The adoption of GETs in the U.S. has been slow, primarily because utilities are not rewarded for reducing congestion. The system operator, not the utility, pays congestion costs. As a result, utilities are not economically motivated to install DLR. In Europe, where transmission owners often act as system operators and directly shoulder congestion costs, the economic benefits of DLR are clear. Multiple European transmission networks have implemented DLR in their full grids without regulatory mandates; Finland is a recent example. Adoption of GETs could similarly help serve load growth and alleviate congestion costs in America.
The Federal Energy Regulatory Commission (FERC) has tried to move the industry in the right direction with Order 881, mandating utilities to adopt Ambient Adjusted Ratings (AAR) by July 2025. However, AAR still leaves a lot of untapped capacity on the table, because wind has a much greater cooling effect on line capacity than cold temperatures. FERC has already issued an Advance Notice of Proposed Rulemaking (ANOPR) on DLR. Despite the potential capacity gains, many utilities are resisting it, pointing primarily to concerns over the undemonstrated benefit of DLR, particularly as the hardware required to scale the solution is very expensive.
The ROI debate over any new grid solution becomes more complicated when hardware is involved. With DLR, large fleets of sensors are inherently slow and expensive to roll out, and difficult to maintain. But software-driven grid solutions are easier to justify, pricing at a fraction of the cost of hardware with the ability to scale immediately to entire grids. European utilities have opted for software-based DLR with minimal hardware support. Finland is covering its entire grid with sensorless DLR with the only piece of hardware being the server in a basement. Until recently, that no-hardware freedom has been the missing piece to scaling DLR. Now, purely software-based DLR solutions have entered the market. Precision weather forecasting is now possible, since the location of every tree, building and hill in America has been scanned by airborne LiDAR and satellites. Machine learning enables weather predictions with confidence intervals that are learned from measurement histories from tens of thousands of weather stations. With an accurate and reliable forecast, utilities can increase power flow for day-ahead energy markets, reducing congestion and dispatching the lowest-cost power plants. Utilities are then able to serve load growth and make higher profits while keeping consumer energy prices under control. This turns the DLR debate on its head. Rather than a cost-benefit risk, DLR is a way for utilities to make more money here and now by serving load growth. Instead of requiring expensive and time-consuming sensor installations, it is available immediately and can simply be turned on in the entire network. There’s a public, real-time tool that shows the enormous untapped capacity of the U.S. grid with DLR.
This news should spark a significant shift in how utilities approach
