Moving Beyond Pilots: Why Grid Enhancing Technologies Are Ready for Enterprise-Scale Deployment

The U.S. electric grid is entering an era in which demand for transmission capacity is growing faster than the infrastructure needed to deliver it. Explosive load growth from data centers, electrification, domestic manufacturing, and renewable energy development is converging with aging transmission assets, heightened reliability expectations, and the decade-long timelines often required to permit and construct new transmission facilities. 

At the same time, utilities and regulators face mounting pressure to maintain affordable electric service as customers shoulder the costs of an increasingly complex energy transition. According to the Columbia Center on Global Energy Policy, improving the utilization of existing transmission infrastructure represents one of the fastest and lowest-cost opportunities to expand grid capacity, often delivering benefits in months rather than the years — or even decades — required to develop new transmission corridors. 

Rather than viewing grid expansion and affordability as competing priorities, utilities increasingly have an opportunity to advance both simultaneously by extracting more value from the transmission assets already in service.

Among the most promising approaches are Grid Enhancing Technologies (GETs) — technologies that increase the capacity, flexibility, and utilization of existing transmission infrastructure without requiring new transmission corridors. Dynamic Line Ratings (DLR), Transmission Topology Optimization (TO), and Advanced Power Flow Controllers (APFCs) each accomplish this through different mechanisms, yet all share a common objective: enabling utilities to move more electricity across existing infrastructure safely, efficiently, and cost-effectively.

Until recently, pilot projects and limited deployments were both appropriate and necessary. Utilities needed to validate technical performance, demonstrate operational value, and build confidence that these technologies could reliably support critical transmission operations. Today, the conversation has shifted.

The Bipartisan Policy Center concludes that GETs have matured significantly since FERC Order No. 881 was under consideration, with successful utility deployments demonstrating their ability to deliver low-cost, high-value increases in transmission capability.

Yet despite this growing technical maturity, deployment across North American transmission systems remains concentrated in pilots, targeted congestion corridors, and isolated implementations rather than enterprise-scale programs. This distinction matters because the greatest value of GETs is realized not when they are deployed as individual projects, but when they become enterprise capabilities.

The transmission industry has spent the past decade proving that GETs can work. The next decade will determine whether it can deploy them at the scale necessary to transform the grid.

The Deployment Gap

If technical maturity alone determined adoption, GETs would already be commonplace across North American transmission systems. DLR, TO, and APFCs have each progressed well beyond proof-of-concept demonstrations, and numerous utility deployments have demonstrated their ability to increase transmission capability while reducing congestion and improving utilization of existing infrastructure. Yet enterprise-scale deployments remain the exception rather than the rule.

This apparent contradiction reflects what we refer to as the Deployment Gap — the growing disconnect between technologies that are technically ready for widespread use and the industry’s ability to deploy them at the scale necessary to realize their full value. The principal challenge facing GETs is no longer demonstrating technical feasibility. It is deploying these technologies as enterprise capabilities capable of delivering system-wide value.

GETs differ fundamentally from traditional transmission investments because they improve performance by changing how the transmission system is operated. Their greatest value is realized not through the installation of a single device or software application, but by embedding new operational capabilities across planning processes, control-room operations, market interactions, and asset management practices. 

The transition required is not simply from individual projects to new technologies — it is from individual projects to enterprise capabilities. More importantly, the deployment challenge is different for every GET — not because the technologies themselves are fundamentally different, but because each technology creates value in a different way as deployment scales.

Closing the Deployment Gap: Dynamic Line Ratings

Among today’s GETs, DLR best illustrates how the industry’s challenge has shifted from technology development to enterprise deployment. Commercial systems are now available from multiple providers using line-mounted sensors, distributed fiber-optic sensing, weather modeling, or hybrid approaches, and successful deployments have demonstrated that DLR can safely increase transmission capability while reducing congestion and deferring capital-intensive infrastructure investments.

The value proposition for DLR changes with scale. Combining fiber-sensing technology, which harnesses existing optical ground wire (OPGW) atop transmission lines, with AI-driven wind modeling software, Prisma Photonics “turns a single strand of fiber-optic cable into a continuous, span-level sensor running the full length of a transmission line, detecting minute changes in wind speed and attack angle to unlock latent capacity on a line.” 

Given the variability of wind across different spans at any given moment, the value of DLR scales dramatically with the ability to simultaneously measure wind across every span — intermittent deployment of discrete sensors creates blind spots, leaving valuable headroom unutilized.

While a single DLR installation unlocks additional thermal capacity on one corridor, enterprise deployment creates a dynamic view of transmission capability across an entire network — a step change in value creation. Most DLR implementations remain focused on targeted congestion corridors, however, because utilities must overcome multiple dimensions of the Deployment Gap: organizational confidence, operational integration into EMS and control-room workflows, and regulatory questions surrounding cost recovery.

There are examples in the U.S. of transmission owners moving toward system-wide deployment of DLR. Utilities including Great River Energy, Puget Sound Energy, and Entergy are demonstrating the transition from pilot projects toward enterprise operational capabilities.

According to Eran Inbar, CEO of Prisma Photonics, deployment across an entire transmission network “creates a dynamic central nervous system for the grid, delivering benefits far beyond those achievable through any single line.” A critical step toward unlocking the technology’s full potential will be establishing DLR as a standard, cost-recoverable investment at grid-scale, on par with reconductoring and other traditional infrastructure investments.

Closing the Deployment Gap: Advanced Power Flow Controllers

In a similar fashion to DLR, APFCs have reached a level of technical maturity that shifts the industry’s attention away from engineering feasibility and toward enterprise deployment. Modular controllers and distributed FACTS technologies have demonstrated the ability to redirect power away from congested facilities and toward underutilized transmission paths.

As with DLR, most implementations to date are pilots of limited-scale deployments on specific corridors — despite the fact that their value proposition improves with scale. A single APFC may relieve one congestion constraint, but the greatest benefits emerge when multiple devices are deployed strategically across a transmission network. APFCs create increasing value by working collectively as a coordinated network.

Ted Bloch-Rubin, Smart Wires’ Director of Business Development, Americas, describes the key barrier to widescale adoption as a structural one, embedded in traditional systems planning approaches: “When planners study a problem, they find the best solution from a cost perspective, from a reliability perspective — and the utility goes and installs that solution. Nine times out of ten, it’s used for that one type of need. Our technology fundamentally is a different way of looking at that problem.”

In other words, traditional approaches to system planning will consistently overlook APFCs because their value is distributed across multiple value streams and not accounted for in single problem-solution scenarios.

Bloch-Rubin explains an additional aspect of APFCs that defies traditional planning and investment theses — the technology lends itself to solving out-of-the-box challenges and presents use cases that may not be readily apparent during the investment planning process. “Once installed, you start learning about how to dispatch it in different ways — in scenarios that were a ten percent probability, but now for some reason are happening 80 percent of the time.” This distinction makes the regulatory dimension of the Deployment Gap particularly visible.

Traditional planning and investment frameworks were designed around discrete capital projects devised to solve individual constraints. Because the grid will not behave as forecast in either the near term or over the asset life, each device’s optionality is worth more the more of the network it can influence. 

In other words, cost recovery and investment incentives insufficiently capture the value of managing uncertainty. According to Bloch-Rubin, “It will be increasingly important to find ways to quantify that value of managing uncertainty, because — to their defense — most utilities have not been asked to value uncertainty. So why would they?”

Clearly, to incentivize adoption of GETs like APFCs with the potential to manage uncertainty while extracting more value from existing grid assets, utilities and regulators will have to rethink traditional investment and cost recovery paradigms.

Closing the Deployment Gap: Transmission Topology Optimization

Topology optimization is another class of GETs for which the greatest barrier to adoption is no longer technical, but organizational and structural. Modern topology optimization algorithms dynamically evaluate thousands of possible network configurations, identifying switching actions to reduce congestion, improve reliability, and increase utilization of existing infrastructure through activation of circuit breakers on high voltage lines. 

The technology is relatively mature (TRL 8-9), and yet deployment is limited relative to its potential to transform the grid. While system operators are making progress toward building the organizational confidence required to routinely act on switching recommendations while integrating TO into EMS, outage management, operator workflows, and market operations, the Deployment Gap persists.

According to Richard Tabors, Co-Founder and Executive VP of NewGrid, “At this point all of it works. There’s nothing in our topology optimization solution that doesn’t do what it’s supposed to do. The question is — can you get enough investment to drive system-level implementation?”

In other words, the main barrier to widescale adoption of TO is a misalignment of incentives. Because investments in TO are heavily skewed toward OpEx rather than CapEx, it does not fit cleanly into the traditional paradigm for transmission owner cost recovery — large capital infrastructure expenditures that expand the rate base, earning a regulated rate of return for investors. 

“The impediment is inertia...The ISOs don’t have the money; they don’t have the time. And the transmission owners have no incentive to do anything other than operate in the economic best interest of shareholders — and that best interest is to build...not to make the existing wires more efficient,” says Tabors.

Like DLR, the value proposition for TO increases with scale. While individual switching actions relieve isolated constraints, the greatest benefits emerge when TO evolves into a continuously available operational capability embedded across the transmission system.

Clearly at the local level, the more circuits available for load to switch to, the larger the number of possible permutations, and the greater the potential gains from topology optimization. This holds true even more so at the system and regional levels — hence the natural economic scale for deployment of TO is at the transmission owner and system operator level.

More than any other GET discussed in this article, TO illustrates that the Deployment Gap is fundamentally a human challenge rather than a mathematical one. Optimization algorithms have become remarkably sophisticated.

The remaining challenge is building the organizational confidence and ultimately architecting better alignment between market incentives faced by transmission owners and solutions that drive the greatest benefits for consumers and the grid as a whole.

Closing the Deployment Gap

The three technologies discussed in this article illustrate a common reality: the challenge facing GETs is no longer one of technical innovation, but of enterprise transformation. They also demonstrate that there is no single pathway to widespread deployment. 

Each technology creates value differently as deployment scales, and each therefore encounters a different manifestation of the Deployment Gap necessitating changes to operations, planning, investment, and cost-recovery mechanisms to enable system-wide deployment.

Taken together, these technologies suggest that accelerating GET deployment will require more than continued innovation by technology providers.  Industry organizations such as EPRI, IEEE, CIGRE, and NERC can accelerate adoption through implementation guidance, best-practice sharing, and collaborative validation. 

Utilities must continue working to integrate new operational capabilities into everyday transmission operations. Regulators must continue to evolve planning, cost recovery, and incentive frameworks to better align returns to shareholders with societal benefits.

Perhaps the most important lesson is that the value proposition of GETs changes with scale. A successful pilot demonstrates that a technology can work. An enterprise deployment demonstrates how the transmission system itself can work differently. The greatest opportunity no longer lies in building a better mouse trap — it lies in building the organizational and structural capacity to implement the suite of transformative technologies already available to the grid.