Globally, electricity distribution systems are significantly underutilized. Since the numbers are not widely or consistently reported, it’s hard to ascertain the extent of this.
Better utilizing the grid we already have, rather than simply building more of it, could reduce consumer bills by $110 to 170 billion over the next decade. That’s the central claim of “The Untapped Grid”, a recent report from the Brattle Group, prepared for GridLab and the Utilize Coalition.
Grid expansion and affordability are at the top of the priority list for every country in the world. The tension between them, at a time when we’re also trying to electrify and decarbonize, is what makes this topic so critical right now.
The report is starting exactly the right conversation at the right time.
What it doesn’t address is the economic layer: how to determine where grid utilization will and will not create value for customers, and how you design incentives that reward that outcome rather than the metric itself. Without that economic lens, there’s no guarantee the savings reach customers.
Let’s start to unpick that.
What the report sets in motion
Grid utilization as a starting point
Tracking grid utilization is a key step on the path towards better visibility. The report establishes it as a way to identify where there is headroom on the grid to connect new load. Better visibility also helps utilities manage risk better and more cost effectively: think upgrade deferral; construction coordination; congestion and outage management, resilience etc.
But utilization is also, over time, a measure of how effectively we have served more customer MWh on the infrastructure we already have. That’s the lens that unlocks its full societal and economic value.
Making that transparent and accessible is a way to allow third-party DER developers, aggregators, and operators to come and offer their asset services (alongside, or instead of, grid capacity) where it’s valuable.
Utilization is a meaningful step forwards, and the precursor to seeing that value at a regional level, which is an important piece of the calculation for determining value across the whole system.
The direction towards shared benefits
The report’s modelling includes a shared savings model: the idea that a portion of net avoided cost from distributed flexibility and efficiency is returned to utility shareholders. This is the right direction. It’s what puts utilities, DER operators, and customers on the same side.
This type of thinking, adopted more broadly, could be an important step towards outcomes based incentives thinking: something policy makers and regulators in UK, EU and US alike are all currently grappling with on the path to designing the grid this transition needs. Spoiler alert: this means affordable, reliable, timely, (sustainable!!) growth.
Transparency of opportunity as a prerequisite
Open ecosystems of data and transparency matter. Publishing data on where capacity exists and where constraints are is critical to unlocking third-party solutions as well as utility solutions, and you need to see both in order to determine where the most value comes from.
The report’s acknowledgement that data availability will influence the level of geographic granularity that’s possible is an important observation. Making that data visible is the enabling condition for everything else.
The key to this is industry working closely with utilities to create the right framework for data sharing so it provides value in improving utilization without being overly burdensome on one party to maintain.
Why haven’t utilities prioritized grid utilization until now?
The reason this conversation hasn’t happened before – or, rather, why it hasn’t happened at scale – is structural.
The traditional utility business model ties earnings to capital investment. You build assets, you earn a regulated return on them. The more you build, the larger the asset base, the larger the return. Selling more kilowatt hours generates revenue too, but it has historically been the secondary mechanism.
There has simply been no strong financial incentive to get more out of what already exists, and meaningful regulatory incentive to do so has been largely absent in the US.
The Brattle Group report acknowledges this. Its section on business model innovation notes that maximizing utilization opportunities “may require regulatory or business model innovation, because traditional utility incentives are tied to capital investment, not to getting more value from existing assets.” That is a way of saying the current model points in the wrong direction.
What’s changing is the scale of the challenge. The incoming load is large enough that building everything conventionally would require capital deployment so enormous that rates would rise sharply for existing customers regardless of the new revenue.
A new study from PowerLines from a review of 51 investor-owned utilities found that utility capex spending could hit $1.4 trillion by 2030, up from a projected $1.1 trillion reported in 2025.
At that point the efficient utilization argument starts being a financial necessity. Which makes the next question all the more important: how do you know where utilization actually creates value, and how do you capture it?
The gap the report leaves open
The Brattle Group report explicitly says it “quantifies the impact of increased system utilization but does not propose specific policies or programs” – and that leaves a gap.
The gap is the economic layer.
The report is technically rigorous, but it treats utilization as a goal in itself.
Utilization on its own could simply be a ratio. e.g. Energy delivered (MWh) divided by available capacity over the same period (MW × hours).
This gives a dimensionless ratio expressed as a percentage. A feeder rated at 20MW that delivers 87,600 MWh over a year, for example, is running at 50% utilization (87,600 ÷ (20 × 8,760)).
It’s worth noting that distribution feeders are typically sized for peak load, not average load. That same feeder running at 50% average utilization over the year might be hitting 95-100% on a summer peak day. The average masks the peak, and it’s the peak that determines where the grid needs attention.
And even where you can see the local picture clearly, a higher utilization number doesn’t automatically mean a better outcome. Moving that number up is not the same thing as creating customer value.
In fact, as you load a system up further, power losses increase, which could mean that you’d have to produce more power to serve the same load. This is unlikely to expand the capacity or the improve the affordability of the system for consumers.
Maximising utilization without an economic lens is not an unambiguously good thing.
We shouldn’t just be asking “are we using more of the grid?” We should be asking: “are we serving more customer value per dollar of infrastructure cost?”
The metric that actually matters for affordability is this: Cost to serve divided by customer megawatt hours served.
If you increase the megawatt hours served without proportionally increasing the cost, you improve affordability. That’s the outcome.
Utilization data is a valuable input to finding where that’s possible. It tells you where headroom exists, where constraints are emerging, and where coordinated action can create net value. But it’s an input, not the output.
And incentives anchored to the utilization number itself risk creating the wrong behaviors, chasing a metric rather than the underlying outcome.
The risk, especially in a regulatory system that’s used to define measurement frameworks, is that we jump from “we can measure this” to “we should incentivize movement in that number”. That would miss the point.
What about those two magic words?
Data centres – or AI factories, as Vladimir Troy would have it – are where this debate becomes very real. Utilities and the communities they serve are right to be anxious about hyperscaler load consuming scarce grid capacity.
Not every hyperscaler has been forward-leaning about paying its fair share of system costs. But data centres also represent one of the few near-term opportunities to materially increase the number of customer megawatt hours served by the system.
That matters because the affordability equation is not just total grid cost. It is total cost to serve divided by customer megawatt hours served. If data centres can be connected in a way that increases the denominator without disproportionately increasing the numerator, they can help reduce the relative cost of the grid for everyone.
But only if it is done properly.
The opportunity is not to give large loads cheap access to constrained infrastructure. It is to be explicit about the system cost target we are trying to hit, the additional customer megawatt hours new load would add, and the contribution required from that load to keep the cost-to-serve equation moving in the right direction.
The good news is that there is a willingness to pay. The missing piece is a transparent, locational economic framework that makes clear what needs to be paid, where, and why.
The answer should not be “no data centres.” It should be to connect economically valuable new load in a way that makes the whole system more affordable.
The point of the electricity system is to power work that creates societal and economic value – and to make sure the costs and benefits of doing so are shared fairly.
What do incentives need to look like?
Incentives NEED to be built on top of utilization data and not just tied to the utilization number itself. They should be tied to outcomes that reflect what customers pay, whether the lights stay on, and whether the system protects them from risk.
And we need a shared benefits-type incentive to get there; one that puts utilities, DER operators, and customers on the same side. I.e. tie the incentive to the outcome, not the proxy.
The specific shape of a shared benefits model will vary by state and by utility, and we’re not here to design regulatory frameworks. What we can say is that the direction of travel is clear regardless of how any individual regime resolves: regulators will always be under pressure to protect customers on affordability, and distributed energy resources (DERs) will continue to grow at a rate that utilities don’t control.
Drawing from the UK’s experience
The UK’s experience is a good example here. The UK started with economic optimization: a clear mandate for a flexibility-first approach.
In 2024 alone, the UK’s flexibility markets contracted 9GW of capacity and delivered £300M of network savings through using flexibility to reduce infrastructure costs and connection charges, and making more use of low-carbon energy sources. The UK’s next regulatory period, ED3, is now building on that foundation with a “build and flex” framework – grid expansion and flexibility working together.
The US has approached it from the other end, already ahead in its technical optimization with the adoption of DERMS, ADMS etc, already well underway (albeit this is slow and costly and won’t be the path that every utility takes).
But both the UK and US are now arriving at the same place: the need to bring technical and economic optimization together, prove the value of distributed decisions, and operationalize it at scale.
That is what the shared benefits conversation is about. And what we know from running flexibility markets in the UK is that the foundations needed to succeed are the same regardless of the model: you need to be able to see where your grid has headroom, where DERs create net value, and whether the decisions you are making are actually reducing cost to serve.
Transparency is the enabler
One other thing worth emphasizing: the report is right that data transparency is important, but I’d go further than framing it as a measurement consideration.
Publishing granular, location-specific temporal data on where capacity exists and where constraints are forming is what lets third-party solution providers (flex, build, grid-enhancing technology) propose solutions on economic terms.
It’s what allows a DER operator to offer their asset where it creates net value, and allows you to compare utility and third-party options on a level playing field. Without that basis, you choose the most visible solution rather than the right one: you can’t optimize what you can’t see.
This matters because the report references a wide range of tools for improving utilization – batteries, HVAC controls, time-varying rates, flexible interconnection, virtual power plants – but doesn’t fully address the question of how you coordinate all of those things together, or how you determine where each one creates the most value.
The data layer that makes location-specific economic assessment possible is the foundation of an optimized system.
What does this mean in practice?
There are three things that need to happen in parallel to turn the Brattle Group report’s vision into reality.
- First, measurement needs to go deeper. System-level averages are a starting point, but the value and the constraints are local. You need geographically granular, locationally specific data to identify where additional loads can be served cost-effectively, and where the grid is approaching its limits. A utilization figure at the system level obscures as much as it reveals.
- Second, incentives need to be redesigned around outcomes. Shared benefits models that reward delivery of real customer value on the affordability, reliability, or risk axis are the right structure. But they need to be anchored to the right metrics, and those metrics need to be the ones that reflect what customers actually experience.
- Third, the tools to find, mobilize and measure that value need to exist. Identifying where loads can be served effectively, coordinating DER deployment where it creates net value, and then continuously measuring results rather than inputs. Those are the practical requirements for making this work.
This is part of what we are building towards at Electron:
- ElectronCompass turns AMI data into practical insight on where DERs are connected, and where distribution grid capacity is available or tightening; and
- ElectronConnect helps utilities coordinate DERs and flexible capacity – across virtual power plants, retailers, aggregators, batteries, front-of-meter assets, and utility-owned resources – (through programs, markets, managed interconnection options etc) so they can be used where they create real system value.
The opportunity we can’t afford to miss
The Brattle Group report – and the great work that the Utilize Coalition and Grid Labs are advancing around this – feels like a genuine inflection point.
Based on Brattle’s illustrative analysis, US consumers could save somewhere between $110 and $170 billion over the next decade if the utilization opportunity is captured effectively. That’s a structural shift in how the grid is valued and operated.
But the prize is only available if we go further than the metric. The next step is to anchor incentives and shared benefits to the delivery of real economic value to customers, and to build the transparency of opportunity – whether that’s utility capacity or DER capacity – that allows the right solutions to find the right places.
Now, let’s get building the policy, the coalitions, and the incentives for the energy system we want: one that delivers more customer megawatt hours at lower or proportionally lower cost, without compromising reliability.
