The $5.5 Billion-Dollar Case for Enabling Data Center Load Flexibility

Key Takeaways

• Batteries have competed away the revenue that financed their first wave. In Texas, ancillary prices have fallen about 90% since 2023, and price spikes driving arbitrage revenue are becoming ever less frequent.
• The business has moved from trading energy to selling capacity. In Texas, tolls work as private capacity contracts, and resource adequacy payments make up roughly 70% of battery revenue in California. Project economics increasingly pencil on a fixed $/kW-month basis rather than price spikes.
• Long-term contracts help shift the risk, but they don’t fully close the gap. Under a 15-year toll, a new battery needs about 22% less revenue, but that is still nearly three times what Texas batteries earned in the market in 2025.
• Buildout now depends on who will pay for capacity. Merchant revenue alone no longer covers a new battery, so growth hinges on how many buyers will sign capacity contracts worth nearly three times what Texas batteries earn in the market. 

Battery Revenues Are Falling While Deployments Keep Rising

US developers are expected to install about 24 GW of utility-scale battery storage energy systems (BESS) in 2026, about 60% more than the record 15 GW added in 2025, according to the EIA. Yet in Texas, where batteries earn most of their money in the market, a typical battery earned roughly 85% less in 2025 than in 2023. 

Is this unjustified overbuilding by an industry that has grown too fast? Some battery executives argue this is not overbuilding, because merchant revenue earned in wholesale markets is no longer the business. In their view, falling merchant revenue matters less because longer-term offtake contracts, such as 15-year tolls with utilities and large power buyers, make lower revenue financeable. As a result, today’s installations bank on batteries being paid as capacity assets rather than as pure energy arbitrageurs. 

We tested those claims against market data from Texas (ERCOT) and California (CAISO) between 2022 and 2026. Our core finding is that project economics in both markets are increasingly reliant on fixed $/kW-month earnings rather than arbitrage revenue.

How Does a Grid Battery Make Money?

A battery has three ways to earn:

1. Energy arbitrage (merchant: paid per MWh traded, hour-by-hour): charging when power is cheap and discharging when it is expensive. Its value depends on the daily spread between the highest- and lowest- priced hours.
2. Ancillary services (merchant: paid per MW held in reserve, bought a day ahead): payments for standing ready to keep the grid stable, such as frequency regulation and reserves, whether or not the battery is called on to deliver energy.
3. Capacity contracts (contracted: fixed $/kW-month for many years): a utility or large buyer pays a fixed monthly fee, often called a toll, for the right to use the battery, and takes on the market risk itself. It is the most stable of the three.

Texas batteries earned almost entirely from the first two. California batteries have earned from all three, and as market revenue has fallen, resource adequacy (RA) contracts–the mechanism through which load-serving entities meet the state’s capacity requirements–have become their main source of income. 

That additional revenue stream is crucial in CAISO, making up roughly 70% of battery revenue by 2025, as net market revenue declined from $103/kW-year in 2022 to under $40/kW-year in 2025. Outcomes differ, too: California still curtails large amounts of midday solar despite its growing battery fleet, while ERCOT’s batteries have flattened price peaks. 

How Texas Batteries Lost Their Merchant Revenue

Ancillary services filled up first. In 2022-23, ancillary services supplied more than 80% of Texas batteries’ revenue. But these markets are small and fixed in size. ERCOT buys about 3 GW of the fast reserves batteries excel at, and 6–8 GW of ancillary services in total. 

The battery fleet passed the first mark in mid-2023 and the second in spring 2024; it is now about 19 GW of registered capacity. Average ancillary services prices fell 85-95% between 2023 and 2025, and ERCOT's day-ahead ancillary services spending fell from about $1.5 billion to $174 million. California’s ancillary markets saturated even earlier: batteries already won about 70% of its regulation-up procurement in 2022, and about 90% since 2024. Its ancillary services spending, much smaller than ERCOT’s to begin with, fell by about 60%, from $237 million in 2022 to $95 million in 2025.

Price spikes disappeared, too. ERCOT's average daily spread between its four highest- and four lowest-priced hours fell from $163/MWh in 2023 to $48/MWh in 2025, even as natural gas prices rose. Yet the typical day, adjusted for gas prices, looks much as it did in 2022. What vanished is scarcity: hours when real-time prices topped $1,000/MWh fell from about 60 in 2023 to 2 in 2025. 

Batteries discharge into exactly those hours, and there are now enough of them to flatten the peaks. Controlling for gas prices, renewables, and demand, each additional gigawatt of batteries is associated with a 9% narrower daily spread. 

Merchant revenue collapsed. Texas batteries earned about $193 per kW-year in 2023 and only about $29 in 2025, according to Modo Energy’s fleet index. California batteries’ market revenue fell from about $80 to under $40 per kW-year, before resource adequacy payments. Merchant revenue alone is no longer enough to finance a new battery in either market. 

Costs fell too, but not by as much: NLR’s benchmark installed cost for a four-hour system fell about a third from its 2022 peak to 2024, from roughly $517 to $334 per kWh in 2024 dollars. Costs then turned up again: Lazard’s levelized cost of storage rose in 2026, to near the top of its range since 2020, as tariffs cut access to cheaper Chinese cells and new foreign-entity-of-concern (FEOC) rules pushed buyers toward other suppliers.

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The Battery Business Has Moved From Energy to Capacity

As merchant revenue declines, storage developers are increasingly turning to capacity contracts to support revenue requirements. This has an important advantage: contracted cash flow can carry more debt at a lower cost. Under illustrative financing assumptions, moving a battery coming online in 2028 from merchant to a 15-year toll lowers its cost of capital from about 12.6% to 7.2%. 

Using NLR’s projected installed capital costs for 2028, that cuts the annual revenue a two-hour system needs to break even by about 22%, from $105 to $82 per kW-year ($64-101 across NLR’s low- and high- cost cases). However, that is still nearly three times what Texas batteries earned in the market in 2025. Given this gap, new BESS installations might appear to be uneconomic.

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Why Are Developers Still Building BESS? 

However, new BESS installations continue to be built. This is partly because many battery storage projects coming online now were financed on 2022-23 revenue (the average project can take over four years from entering the interconnection queue to operation), and partly because new contracts, such as tolls, are priced on capacity, not energy: the supplier is obligated to keep certain amounts of capacity available over a given time period, independent of energy delivery. 

In Texas (which has no capacity market), such tolls are, in effect, private capacity contracts. In California, resource adequacy already plays that role: batteries’ RA contracts averaged about $9 per kW-month in early 2025. 

An owner needs roughly $7 per kW-month for a two-hour battery (about $11 for four hours) to break even, in line with the roughly $7 per kW-month cap on a 20-year battery storage agreement Austin Energy approved in May 2026. By contrast, the energy and ancillary revenue an offtaker could capture by dispatching it is about $2.50–3.50 per kW-month. The difference is what buyers pay for firm capacity: insurance against scarcity events like Winter Storm Uri, capacity to meet their own load obligations, or a hedge against scarcity returning as demand grows. 

The Next Battery Wave Depends on Who Pays for Reliability

Batteries have done what they were built to do: absorb volatility and steady the grid. In doing so, they competed away the revenue that financed the first wave. At today’s prices, merchant revenue no longer covers a new battery. The build continues on projects financed in 2022–23 and on capacity contracts worth nearly three times what Texas batteries earn in the market. Whether the buildout continues depends on how many buyers will pay that premium. 

Deployment continues to grow in both markets. ERCOT registered about 4.2 GW of new batteries in January to July 2026, against 2.8 GW a year earlier. But the pace is slowing: Texas’s fleet grew about 50% in 2025 after nearly doubling in 2024, and interconnection queues are thinning: ERCOT battery applications fell by half in the second half of 2025. 

Wholesale markets financed the first boom. The next wave depends on buyers who value reliability, including utilities, retailers, and large loads such as data centers, and on how cheaply that risk can be priced and capitalized. Data centers in particular put a high value on firm power: research inferring their willingness to pay from cloud computing prices puts it at up to $13,600 per MWh for frontier AI chips on guaranteed service, far above ERCOT’s $5,000 per MWh price cap. 

For developers and investors, the question is no longer how much the market will pay, but who will sign, and for how long. For more on how interconnection queues shape how many storage projects get built and how queue wait times vary by technology, see Relae’s interconnection research.

Relae’s Power & Energy advisory team helps developers, investors, and large energy buyers understand and price the value of storage. This includes behind-the-meter modeling, resource portfolio optimization, and interconnection queue analysis. 

Frequently Asked Questions

Why are battery storage revenues falling if deployment keeps growing? 

Batteries have become victims of their own success. They earned most of their early revenue from two sources: ancillary services and high wholesale market prices. Texas now has more batteries than ancillary services the grid needs, so those prices have collapsed. And because batteries discharge during the most expensive hours, there are now enough of them to flatten the price spikes that used to pay the most.

What is a battery tolling agreement? 

A toll is a long-term contract in which a utility or large buyer pays a battery owner a fixed monthly fee for the right to direct how the battery is used. The buyer keeps whatever the battery earns in the market and takes on the risk if that falls short. The owner gets a steady income it can borrow against.

Who is signing these contracts? 

Mostly utilities, retailers and power traders, who need capacity to serve their customers or want protection against price spikes. In California, utilities sign capacity contracts with batteries to meet the state’s resource adequacy requirements. Large loads such as data centers place a high value on reliable power, but few have signed contracts with grid batteries so far; most of their battery deals are for on-site power.

Will battery storage buildout slow down? 

Not yet. Texas is still adding more batteries each year, largely projects that were planned and financed when revenues were higher. But the pipeline behind them is thinning: new battery applications in ERCOT’s interconnection queue halved in the second half of 2025. Whether buildout holds up depends on how many buyers will pay for capacity at a premium to what the market pays today.

Key Takeaways

• Accurate load forecasting is needed to distinguish and prioritize real demand, align capital deployment, and reduce delays in bringing new power capacity online. Traditional load forecasting was built for predictable, gradual demand growth, not for the scale, uncertainty, and dynamic behavior of data centers. 
• The system-level fix to data-center load forecasting requires probabilistic, more frequent, category-specific methods paired with mandatory data standards and policy alignment. Together, these give planners visibility into the range of possible futures and the likelihood of each. 
• Without that fix, today's forecasts conflate real demand with speculative submissions, reducing accuracy. Inaccurate forecasting in either direction is expensive: underbuild adds friction to economic development; overbuild risks raising retail rates. Both can erode public trust in planning.
• Behind-the-meter generation (BTM) and load flexibility can help achieve speed-to-power in the near term. Just 1% data-center flexibility could unlock 100 GW—more than the entire US nuclear fleet.

Load Growth Is Increasing, Uncertain, and Concentrated

For two decades, US electricity demand was flat. Utilities, transmission planners, and corporate buyers built their planning models around that reality. Then AI workloads changed it.

AI load growth is large, uncertain, and concentrated in major power markets. While load forecasting projections vary across studies, the trajectory is clear: electricity demand is scaling faster than the bulk power grid was designed to handle. Accurate load forecasting is needed to distinguish and prioritize real demand, align capital deployment, and reduce delays in bringing new power capacity online.

On April 30, 2026, Relae (formerly Carbon Direct) hosted a Trellis Group panel on load forecasting in the AI era. Panelists included Derya Eryilmaz, PhD, Vice President of Power Commercialization at Relae; John Miller, Director of Transmission Policy at the Corporate Energy Buyers Association (CEBA); Daniel Padilla, Strategy and Business Development Lead at Emerald AI; and Sam Hodas, Head of US Government Affairs at National Grid. Jake Mitchell, Director of Climate Tech Innovation at Trellis Group, moderated.

The conversation explored where load forecasts fail, what they cost, how to fix them, and near-term solutions to overcome grid constraints. Here is what the panel found.

What Is Load Forecasting?

Load forecasting is the practice of predicting how much electricity will be consumed across a region, at what times, and under what conditions. It informs the major capital and procurement decisions on the grid: where to build transmission, how much generation to procure, what capacity to bid into wholesale markets, and how corporate buyers secure clean, firm power.

Long-term forecasts inform multi-year decisions about transmission and generation. Short-term operational forecasts inform real-time grid operations and trading. The two often sit in separate workflows, but short-term operational forecasts should feed into long-term system planning to improve accuracy as demand patterns shift.

The Bulk Power Grid Is Under Strain

Large power users face constraints on clean, firm power, transmission capacity, multi-year interconnection queues, and aging infrastructure. The strain is most acute in PJM Interconnection (PJM) and the Electric Reliability Council of Texas (ERCOT), the two US markets expected to see the most significant load growth. Each constraint raises the cost of getting load forecasts wrong.

Hodas from National Grid describes the operational reality on the utility side: aging infrastructure inherited from a different demand era. “We’ve got transmission lines that are 70 to 100 years old in New York and Massachusetts, some of the oldest in the country, still in operation.” Replacing or upgrading that infrastructure requires investment, and ratepayers are already pressed. 

Why Today’s Load Forecasts Fail

Traditional load forecasting was built for predictable, gradual demand growth, not for the scale, uncertainty, and dynamic behavior of data centers. 

Most utilities and Independent System Operators (ISOs) produce load forecasts on annual or biannual cycles. They aggregate submissions from individual customers, run that data through a deterministic single-peak load estimate against a single capacity scenario, and pass the consolidated forecast up to regional planners. Regional Transmission Organizations (RTOs) roll those bottom-up utility forecasts into a regional view. 

This worked when demand was flat and predictable. It no longer works with nonlinear growth driven by data centers. Eryilmaz from Relae identifies key structural limitations. 

Four Structural Limitations to Traditional Forecasting Methods

• Over-stating and double-counting. Data centers bid into multiple regions while shopping for power, inflating regional forecasts and blurring the line between real and hypothetical demand—the speculative-load problem.
• Deterministic models (vs probabilistic models). Most planning runs a single peak load estimate against a single capacity scenario, missing the geographic concentration and uncertainty inherent in integrating large loads into the system.
• Aggregated submissions. Utilities report large loads as a single block of gigawatts, with no resolution into workload type, ramp schedule, or operational shape. Planners reverse-engineer peak-demand assumptions rather than measure them.
• Infrequent cadence. Annual or biannual forecasts cannot catch an 80% queue reduction or a multi-gigawatt addition between cycles.

The Speculative-Load Problem

The core challenge in load forecasting is distinguishing real versus hypothetical load. While data center electricity demand is projected to grow by 13-27% annually through 2028, the majority of the projects in the data center queue may not materialize, inflating regional load forecasts.

American Electric Power's Ohio utility (AEP Ohio) introduced a tariff requiring data centers to put up firm financial commitments before getting in line for grid connection. Its interconnection queue dropped from 30 gigawatts to 5.6 gigawatts. More than 80% of the submitted load was speculative: projects that disappeared once commitment became required.

ERCOT shows the same overstatement problem on a larger scale. Roughly 225 gigawatts of data center demand sits in the ERCOT queue against a historic system peak of 85 gigawatts. Texas Senate Bill 6 introduced similar financial obligations for new loads, but those rules apply only to interconnections after 2025, and the cleanup of speculative demand has not yet materialized.

The speculative-load problem shows up in interconnection times. An average new project in PJM can wait 4 to 5 years to become operational. Some of that delay is a real backlog. The rest comes from the inability to distinguish real submissions from speculative ones.

As Eryilmaz puts it, “Load forecasting is actually the center of all of these problems. It is a tool to help planners make the right investment decisions.”

The Cost of Inaccurate Forecasting

As Miller from CEBA notes, “A single misforecasted project can swing a transmission plan by hundreds of megawatts.” Significant inaccuracies can erode public trust in the planning process in two main ways. Underbuilding adds friction to economic development and can limit corporate access to clean power markets. Conversely, overbuilding risks raising retail rates if capacity remains underutilized. 

The goal is to achieve right-sized infrastructure investment. When planning aligns with actual large load growth, it can be net beneficial to retail rates. By spreading fixed costs across more usage, significant new demand can put downward pressure on the rates via the “denominator effect.” 

On the other hand, forecasting variability can distort capacity procurement and interconnection queue prioritization. When load forecasts spike upward, grid operators like PJM have to scramble to buy additional electricity capacity on short notice. These emergency procurements lock in major dollar commitments on the basis of unstable forecast numbers. 

PJM, Midcontinent Independent System Operator (MISO), and Southwest Power Pool (SPP) have also reshaped their interconnection queues to make room for new large loads, but those queue priorities depend on the same forecasts that are unreliable in the first place. 

“There is no substitute for good backbone regional transmission planning,” Miller says. “Full stop. That is the enabler of all of the load growth that we’re talking about.”

BTM Generation and Load Flexibility: A Near-Term Bridge

Hyperscalers’ need for power is way faster than that of utilities and RTOs. Generation alone cannot scale fast enough to meet this new demand, and hyperscalers need speed-to-power.

As Eryilmaz frames it, behind-the-meter generation and load flexibility are interim solutions to the timing mismatch between data center urgency and the grid's slower build cycles. BTM generation and flexibility work differently:

• BTM is power generated on the data center's side of the utility meter, bypassing grid interconnection entirely. The structure gives operators large, reliable blocks of power without waiting years for grid approval.
• Load flexibility is the demand-side approach. A data center modifies its grid draw in response to grid signals. In practice, that can mean curtailing compute workloads during stress events, pre-cooling facilities ahead of a heat wave, drawing from on-site batteries or generators, or shifting workloads to data centers in less-constrained regions.

The Value of Load Flexibility

Relae’s power system modeling quantifies the dollar value of load flexibility in ERCOT. Load flexibility can eliminate forced load shedding risk, even at 40 gigawatts of data center buildout, preventing $5.5 billion in annual consumer welfare losses by curtailing an average of 5% of demand for under 1% of operating hours.

Padilla from Emerald AI reinforces the scale and value of load flexibility: “With just 1% flexibility, we can unlock 100 gigawatts of data centers across the US. That’s more than the entire US nuclear fleet.”

Silicon Valley Power, a municipal utility, is the first US utility to tie flexibility to interconnection speed: flexible data centers get connected faster. NVIDIA, EPRI, Digital Realty, and PJM are partnering on the Aurora AI Factory, the first purpose-built reference design for flexible AI data centers. 

But standardized policy for load flexibility is lagging. Padilla highlights this challenge: “Today, if a data center wants to be flexible, they have nowhere to point. We need standardized tariffs, interconnection rules, and product definitions for large loads that reward them with upsizing interconnection in response to flexibility.” 

Flexibility Takes Many Forms, but it Isn't Universal

Flexibility means accepting brief, predictable downtime, and some workloads can't tolerate it. Hospital systems and mission-critical enterprise applications need 99.999% uptime, the "five nines" standard. As Padilla puts it: "99.9% uptime, with brief and predictable curtailments, is plenty" for most AI workloads. That distinction determines which data centers can participate in flexibility programs.

Miller points out that compute-level flexibility is not always feasible. BTM batteries and virtual power plants (VPPs) are among the alternatives that can offset what data centers withdraw when the grid is stressed, even at facilities whose compute workloads cannot pause directly.

Better Load Forecasting: The Longer-Term Fix

While BTM generation and load flexibility can help address near-term speed-to-power, the longer-term fix is improving load forecasting methods and the standardization of data provided by the data centers themselves.

Eryilmaz outlines three technical shifts for better load forecasting:

• Embed short-term operational forecasting into long-term planning. Short-term spikes, weather risk, and reserve considerations carry direct implications for multi-year capital decisions. The line between operations and planning breaks down when growth is nonlinear.
• Replace deterministic models with probabilistic methods. Risk metrics like loss of load hours (expected hours per year that demand exceeds supply) and expected unserved energy (total expected energy shortfall) measure both how much capacity the system has and the conditions under which it might fall short. The North American Electric Reliability Corporation (NERC) has suggested both metrics as part of its reliability framework.
• Forecast load by category. Treating all data center load as a single block hides the differences in load profiles, operational schedules, and ramp-up timing that drive system planning.

Policy Alignment

Technical forecasting improvements only scale with policy alignment, and Miller proposes a two-part fix:

On the top-down side, RTOs need authority to take an independent view of utility-submitted forecasts. They should require milestones, such as firm financial commitments and secured financing, before counting a submitted load against the regional forecast. 

On the bottom-up side, state regulators set the rules that govern how individual utilities prepare their forecasts. Large load tariffs play a big role in how utility-level forecasts come together. Federal and state authorities need to row in the same direction. Hodas frames the same alignment from the utility side: “Grid investment unlocks economic growth, but for us to make those investments, we need regulatory certainty.”

Standardizing Large-Load Data

The Federal Energy Regulatory Commission (FERC) has since moved: in June 2026 it issued show cause orders directing six RTOs and ISOs—CAISO, ISO-NE, MISO, NYISO, PJM, and SPP—to revise or justify their large-load interconnection rules, and in July 2026 it directed NERC to develop computational-load reliability standards and registration criteria by the end of the year. Both are useful first steps. But as Eryilmaz argues, voluntary disclosure has not closed the gap.

The industry cannot meaningfully compare ISO forecasts when each utility submits load data in different shapes (e.g., using different methods and data standards) on different schedules. Mandatory submission requirements and published methodologies, applied consistently across utilities, ISOs, and state regulators, are the only path to forecasts whose components are actually comparable.

Getting Load Forecasting Right Starts Now

The system-level fix to improving forecasting is through probabilistic, category-specific methods paired with data standardization and policy support. Together, these account for the scale, uncertainty, and dynamic behavior of data center loads, and give planners visibility into the range of possible futures and the likelihood of each.  

All forecasts will be wrong to some degree, but as Miller puts it, “It's ultimately not about having a perfect prediction. It's about baking in methods to account for uncertainty.” These system-level improvements won't eliminate errors entirely, but they will minimize them, leading to more confident investment decisions and a grid better prepared for what's ahead.

Frequently Asked Questions

What is load forecasting, and why is it harder now with AI data center loads?

Load forecasting predicts how much electricity a region will consume, when, and under what conditions—the basis for where to build transmission, how much generation to procure, and how corporate buyers secure clean, firm power. It was designed for two decades of flat, gradual demand growth. Data center load is none of those things: it is large, geographically concentrated, arrives in gigawatt blocks with no disclosed operating shape, and can be withdrawn as quickly as it appeared.

What is speculative load in an interconnection queue, and how do planners tell it apart from real demand?

Speculative load is capacity requested by projects that may never be built — often the same data center bidding into several regions at once while shopping for power, which counts the same gigawatts more than once. The tested filter is a financial commitment: when AEP Ohio required firm commitments before queue entry, the utility's reported data center pipeline fell from about 30 GW to roughly 5.7 GW. Milestone requirements, independent RTO review of utility submissions, and mandatory data standards are the tools planners have.

Is load flexibility proven and scalable today, or still emerging?

The modeling case for load flexibility is strong; the commercial case is still early. Duke's Nicholas Institute found the 22 largest US balancing authority areas could absorb roughly 76–126 GW of new load if it accepts modest curtailment, and Relae's ERCOT modeling shows demand response eliminating forced load shedding risk at 40 GW of data center buildout, avoiding $5.5 billion in annual consumer welfare losses. What is still missing is the market plumbing—standardized tariffs, interconnection rules, and product definitions—so a data center willing to be flexible has somewhere to sign up.

What should a company look for when evaluating a region's load forecast?

Ask whether the forecast is probabilistic or a single deterministic peak, how often it is refreshed, and whether large loads are broken out by category and operating shape rather than reported as one block of gigawatts. Then ask what milestone or financial commitment a project must clear before its megawatts count toward the forecast. A forecast that cannot answer those three questions cannot tell you how much of the queue ahead of you is real.

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Key Takeaways

• Geothermal shares the clean firm category with only three other technologies: nuclear, natural gas with carbon capture and storage (CCS), and solar or wind paired with long-duration energy storage (LDES).
• Buyers comparing geothermal to solar or unabated natural gas power contracts are comparing different products: one isn’t firm, the other isn’t clean, and both remain cheaper options because they satisfy less of what buyers currently need. 
• Geothermal’s cost premium is real, but so is the value it delivers. Geothermal can reach 90%+ capacity factor, delivering dispatchable clean power around the clock, and it sidesteps the gas turbine manufacturing backlogs and pipeline infrastructure delays slowing other firm power technologies. 
• Geothermal is closer to commercial readiness than most buyers realize. As demand for firm, low-carbon power intensifies, geothermal warrants a serious look alongside nuclear and gas with CCS.

Geothermal is Gaining Traction Despite Its Cost Premium

Hyperscalers, corporate energy buyers, and data center developers face unprecedented pressure to procure clean power. Wind and solar have played a major role in meeting this need, but they are intermittent, and load growth is accelerating and changing. This market pressure is creating bottlenecks that cannot be solved without new grid infrastructure and/or substantial additions of energy storage. Geothermal, which does not suffer from intermittency, has gained tremendous momentum as a challenger to wind and solar, yet it carries one seemingly glaring disadvantage: its cost. 

Yet, major utilities and hyperscalers alike are lining up for geothermal offtake anyway: Southern California Edison and Google have signed separate contracts with Fervo, and Meta has two 150 MW agreements in place with Sage and XGS. These contracts are signaling a growing shift in power markets: not all megawatt-hours are created equal, and the cheapest contracts may no longer contain what buyers truly need. 

Fast, Clean Firm Power: What Buyers Need Today 

In the clean firm power evolution, clean came first. Buyers signed solar and wind power purchase agreements (PPAs) and matched their annual consumption with renewable energy contracts, or offset them with renewable energy certificates (RECs). With lax carbon accounting, solar and wind remain unbeatable on price. But annual emissions tallies conceal something important—a buyer can procure as much renewable electricity as it consumes over a year while still depending on the rest of the grid during the hours when those resources are unavailable. To close that gap, buyers need a source that delivers clean power around the clock, firmly in every hour, on demand. 

Two unforgiving demands have followed since: speed and location. With today’s rapid buildout of new load, a power source needs to come online in time to deliver power when the customer needs it. It is also important to connect near a customer’s location because existing transmission assets are often fully subscribed. Failure on either axis can disqualify a project. However, a contract that can meet all attributes: clean in every hour, firm on demand, quick to deliver, and able to reach the load, might be the best (or only) option available. It is also likely to be considerably more expensive than those annual solar benchmarks that only met the clean condition. 

Four Technologies Make the Clean Firm Power Shortlist

Given this strict set of constraints, what power options should buyers consider? The right set of technologies should aim to solve as many of the aforementioned conditions as possible, and that leaves a fairly tight shortlist: 

1. Solar or Wind paired with Long-Duration Energy Storage (LDES): To achieve the level of reliability that many buyers, including data centers, require, solar or wind would have to be paired with LDES, beyond 4–8 hours, to be able to cover evening hours and remain online during increasingly common extreme weather events. While there are promising LDES technologies on the horizon, most remain expensive and not yet widely commercial. Costs rise significantly compared to a standard solar or wind PPA, and viability varies by location. This will be increasingly competitive as storage costs fall, but not yet a mature firm-power solution at scale.
2. Natural Gas with CCS: With large amounts of unabated natural gas generation coming online, CCS is an attractive option to mitigate a large portion of these emissions while retaining time to power (by building gas first and adding CCS later) and the dispatchability of gas-fired power. On the flip side, CCS is operationally complex, geographically restricted, and - unlike other options here - failure at any point in the CCS chain directly impacts the carbon intensity of power delivered. Gas-fired generation is also reliant on the gas delivery pipeline infrastructure, which may face capacity constraints. Finally, natural gas with CCS is 50% more costly per MWh than unabated firm gas.
3. Nuclear: Nuclear is seeing renewed interest from a wide range of corporate buyers and investors. Conventional nuclear and small modular reactors (SMRs) are attracting funding and offtake deals. While nuclear power holds high potential, long development timelines, high capital costs, and technology risk remain barriers to commercializing the next wave of nuclear technologies. 
4. Geothermal: Geothermal can provide firm, dispatchable, and low-carbon power with capacity factors typically above 90%. Development timelines can be faster than nuclear in regions where resources are already proven, with some projects approaching commercial readiness now. Geothermal technology is still geographically constrained, but enhanced geothermal systems (EGS) are poised to  expand their geographical flexibility by reducing the number of siting variables. 

How to Evaluate the Right Clean Firm Power Technology for Your Project

How do these various options stack up? We compared them across six dimensions:

1. Firmness: how reliably a resource can deliver power on the hour, on demand
2. Carbon: the lifecycle emissions intensity when considering the operational emissions of the generating facility and the broader system carbon impacts required to meet any reliability gaps
3. Time to power: a measure of how long it takes to get from “we need power” to delivery, including interconnection and schedule risk
4. Cost (current): the likely cost of a PPA if signed today
5. Execution risk: a measure of how likely a project’s claims regarding price, timing, and performance will hold
6. Siting flexibility: a measure of how constrained a resource is to a specific geography

This frame is ultimately something the buyer should score themselves; below you will find our current read. Red (unfavorable) represents a weakness that can end an evaluation on its own, green (favorable) means the dimension won’t constrain the decision, and yellow (moderate) sits somewhere in between. 

Comparing the clean firm power options is, perhaps ironically, challenging along the “clean” and “firm” lines. Every serious contender delivers low-carbon power around the clock, because that is the price of admission. Not one technology earns an unfavorable rating in those categories. And that is the catch: every weakness in the comparison table sits somewhere else. The dimensions that ultimately win (or end) these contracts may be the ones that the “clean firm” label can obscure or oversimplify.

A resource that cannot be energized for a decade, or sited near load, or delivered at a price a buyer cannot defend internally, may be infeasible regardless of what else it offers. None of the four clean firm generation technology groupings clear every hurdle today, but they can satisfy different buyer priorities.  

Solar or wind with LDES offers more buyer flexibility, at a price. Enough generation, storage, and other firming can deliver the reliability required, and the buyer sets that target. But the increments get expensive quickly, especially when reliability gaps remain long or unpredictable. Covering more hours means more storage and more generation to fill it, so each step toward firmness parity costs more than the one before it. Firming shortfalls also carry carbon consequences, depending on what gets called to compensate. Those emissions may be absent from GHG accounting ledgers, but that doesn’t stop them from hitting the atmosphere. 

Gas with CCS is challenged by execution and siting because the product depends on a chain: gas generation, capture, transport, and a permitted storage site capable of permanent CO₂ disposal at scale. Each piece can be developed and tested, but low-carbon electricity requires all of them to work together, which can only be demonstrated once all are built. A buyer cannot substitute a link, and cannot observe the whole chain before committing. Clean, in this sense, is conditional, and the delivered power could end up being far more carbon-intensive than advertised.

Nuclear ranks poorly on time, cost, and execution, but full-scale reactors and small modular reactors carry those weaknesses differently. A large reactor arrives in one piece, and its schedule and final cost come into focus as construction advances. By then, years and billions are committed; a buyer cannot learn from a fraction of a reactor before deciding whether to finish it. Small modular reactors are designed to break that capacity into increments a buyer could add as demand grows, which would ease the one-piece problem. But none are operating commercially in the US yet, and the signed deals target first power in the 2030s, so the modular promise is still years out. 

Geothermal’s weaknesses work somewhat differently. Conventional hydrothermal is tightly constrained by location, which buyers can screen before choosing where to procure, or co-locate where possible. Next-generation geothermal, including EGS, could widen that geography considerably. 

For EGS, the largest remaining uncertainty is execution: whether the developers can replicate successful drilling and reservoir performance at commercial scale. Part of that risk belongs to the rock, and no contract can make a reservoir perform. But drilling also produces information before the entire project has been built, and geothermal capacity can often be developed incrementally as needed. A buyer can require resource evidence before committing, tie later commitments to demonstrated performance, or spread procurement across projects rather than depend on a single field. 

Geothermal’s flexibility has limits. A buyer who needs full capacity by a fixed date may have little room to wait for wells to perform before committing to the next phase. And successful wells do not eliminate risk in project expansion or guarantee performance in other locations. Execution risk stays with the resource. What geothermal offers is more opportunity to learn about that risk while a buyer can still do something about it. 

Revisiting the Geothermal Premium

Geothermal contracts, especially EGS, remain expensive. But that premium looks different on this side of the comparison. Clean has a cost, but so does firmness, speed,  reach, and execution. Every clean firm option pays for those attributes somewhere. Solar and wind contracts will remain cheap by comparison, but it’s the wrong comparison: the market signing geothermal contracts is pricing a much larger product. 

That still leaves a hard decision. Geothermal and gas with CCS carry execution risk and siting constraints. Nuclear asks more of the buyer on cost and time. Firmed solar asks more as reliability requirements rise. The best option will change with each buyer, location, and project. Geothermal’s place in that choice is changing quickly. EGS is expanding where projects can be developed, drilling costs are falling, and commercial experience is growing. Those advances are bringing geothermal into consideration for buyers who previously had little reason to look its way. 

And that may be the more revealing aspect of the geothermal market today: buyers are signing those contracts with the alternatives in full view. Their decisions offer an early indication of what clean firm power delivered in the right place and at the right time is worth, and which risks buyers are willing to carry to get it. 

Frequently Asked Questions

Is Geothermal Cheaper Than a Solar PPA? 

No, a geothermal power contract can be significantly more expensive than a solar PPA. But they're not the same product: solar meets annual clean-energy targets, while geothermal delivers firm, dispatchable power around the clock, which is why buyers are increasingly comparing it to nuclear and gas with CCS instead.

Is Geothermal Cheaper Than Solar with LDES? 

Not necessarily on a per-contract basis, but the cost structures behave differently. Solar with LDES gets more expensive with every additional hour of reliability a buyer needs, since covering more hours means adding both more storage and more generation to fill it. Geothermal's premium, by contrast, is priced into the contract upfront as a firm, dispatchable product from day one.

How Does Geothermal's Risk Compare to Gas with CCS? 

Differently, in a way that matters to buyers. Gas with CCS depends on a chain (generation, capture, transport, and storage) that can only be verified once the whole system is built, so a buyer can't test it piece by piece. Geothermal generates performance data incrementally through drilling, letting buyers require resource evidence or tie commitments to demonstrated results before committing further, though this data does not come free.

Which Deploys Faster, Geothermal or Nuclear? 

Geothermal, in regions with already-proven resources. Fervo's Cape Station, for example, broke ground in 2023 and is on track for first power in late 2026 and 500 MW by 2028: a fraction of a typical new-nuclear large reactor timeline.

Key Takeaways

• The GHG Protocol Corporate Standard and life cycle assessment (LCA) offer distinct frameworks for measuring electricity-related emissions, one for annual corporate reporting and one for detailed cradle-to-grave analysis, leading to different emissions results.
• Renewable energy certificates (RECs) are accepted under the GHG Protocol's market-based approach to reduce reported scope 2 and scope 3: category 3 emissions, but are not explicitly addressed in ISO LCA standards, where transparent disclosure is essential.
• Using both the GHG Protocol and LCA together, while recognizing their different scopes, boundaries, and purposes, can give organizations a more complete and strategic view of electricity-related emissions and decarbonization opportunities.

Electricity-Related Emissions: Why Measurement Methods Matter

In the era of AI-driven power demand, scrutiny over electricity-related emissions is intensifying. With this increased attention comes growing confusion around how to measure and report these emissions. The GHG Protocol Corporate Standard and life cycle assessment (LCA) are two widely used methods for measuring and reporting electricity-related emissions, but each follows its own complex and often incompatible, set of rules.

This piece will examine the differences between these approaches and answer common questions such as:

• What are the differences between the GHG Protocol Corporate Standard and LCA?
• Why do they result in different emissions for the same type and amount of electricity?
• Can renewable energy contracts reduce electricity-related emissions under both methods?
• When should you use each approach?

Both the GHG Protocol Corporate Standard and LCA are powerful tools that, if used in complementary ways, can help organizations identify emissions hotspots and develop more effective pathways for decarbonization.

What Is the GHG Protocol Corporate Standard?

The GHG Protocol Corporate Standard is a globally recognized framework for corporate entities to publicly report GHG emissions throughout their value chain. It divides emissions into three scopes:

• Scope 1: Direct emissions from owned or controlled sources, such as company-owned vehicles, on-site fuel consumption, or industrial processes.,
• Scope 2: Indirect emissions from the generation of purchased electricity, heat, steam, or cooling. These emissions are generated off-site, but result from an organization's energy consumption.
• Scope 3: Indirect emissions across an organization's value chain. Scope 3 is divided into 15 categories, including a company's supply chain activities, business travel, employee commuting, investments, and product life cycle emissions.

This piece focuses on emissions associated with electricity consumed by a reporting entity. These electricity-related emissions primarily fall under scope 2 and scope 3: category 3 (fuel- and energy-related activities, or FERA).

Scope 2: Electricity Generation Emissions

Scope 2 emissions account for the generation of electricity a company purchases or uses. Hypothetically, if a company were powered by a single solar project, it would report zero scope 2 emissions. In reality, a company is powered by a combination of power generation assets and must report them under scope 2 emissions. These emissions can be reported using two methods:

• Location-based method: Reflects the average emissions intensity of the local electricity grid where the consumption occurs. This approach is mandatory under various reporting frameworks and does not take into account a company's procurement choices.
• Market-based method: Reflects an organization's actual procurement decisions and energy-sourcing strategies. It accounts for specific contracts, such as power purchase agreements (PPAs), renewable energy certificates (RECs), and green tariffs, which allow businesses to claim lower emissions from their purchased electricity.

Scope 3: Category 3 FERA

Scope 3: category 3 FERA reports on non-generation electricity emissions associated with:

• Upstream emissions: Emissions associated with the production and transportation of fuels needed for electricity generation
• Transmission and distribution losses: Emissions associated with the loss of electricity while delivering it from the generator to the consumer.

The GHG Protocol Corporate Standard does not include emissions associated with the manufacturing, construction, and end-of-life phases of electricity generation equipment; however, some datasets used for reporting may include manufacturing emissions. While scope 3: category 3 guidance may not require these emissions to be included, if possible, companies reporting on their electricity-related emissions should include these additional sources of emissions  in order to more completely represent their total emissions impact. The GHG Protocol Scope 2 Guidance allows for the reduction of some of the reported scope 3 FERA emissions by contracting renewable energy (see Appendix B).

What is an LCA?

An LCA is a systematic method used to quantify the environmental impacts of a process, product, or project throughout its full life cycle. A life cycle includes everything from raw material extraction ("cradle") to manufacturing/production ("gate") through disposal ("grave").

LCAs primarily follow a standard published by the ISO organization (ISO 14040/14044). The ISO standards establish industry-wide rules for which processes are included and how to assign environmental burdens to products.

An LCA can be used for any product, process, or project, and can estimate multiple different environmental impacts (i.e., climate change, human health, ecotoxicity, eutrophication, ozone depletion).

Electricity-Related Emissions Can Be Different Using the GHG Protocol and an LCA

The GHG Protocol Corporate Standard and an LCA (as per ISO standards) generally include different life cycle stages of electricity use when estimating GHG emissions. Therefore, the approaches can result in different reported emissions.

Key Differences in Reporting Electricity-Related Emissions

The GHG Protocol Corporate Standard includes emissions in the following phases:

• Generation (scope 2)
• Transmission and distribution losses (scope 3: category 3)
• Fuel, if applicable (scope 3: category 3)

A “cradle-to-grave” LCA considers emissions from all activities associated with power generation, including:

• Manufacturing
• Construction
• Generation
• Fuel, if applicable
• Use-phase, if applicable
• End-of-life

Use-phase electricity-related emissions are emissions generated by electricity-consuming equipment used or sold by the reporting company (representing additional scope 1 or scope 3 emissions, respectively). Examples include sulfur hexafluoride (SF6) emissions from electrical transformers or refrigerant leakage from air conditioners with high global warming potential. Please note that both the ISO and GHG Protocol Corporate Standard provide guidelines for reporting these emissions. However, due to the equipment-specific nature of these emissions, they are excluded from the following table. The table compares electricity-related emissions associated with different electricity sources using the GHG Protocol Corporate Standard approach and the LCA approach.

Reporting Electricity-Related Emissions

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* US average transportation and distribution loss rate (4.2%) times US average grid carbon intensity (410 gCO₂e/kWh). Note: gCO₂e/kWh = grams of carbon dioxide equivalent per kilowatt-hour. Source: GREET 2024 (US grid average. 10% fuel- and energy-related activities; 1% construction, facilities, maintenance, and end-of-life; 89% fuel combustion).

Reducing Electricity Emissions with Renewable Energy

Renewable Energy Mechanisms Under the GHG Protocol

The GHG Protocol Corporate Standard allows companies to contract for renewable electricity as a mechanism to reduce reported emissions. The GHG Protocol Corporate Standard defines allowable energy contracts that can be used to reduce emissions associated with electricity consumption (market-based reporting).

In North America, one of these allowable contracts is RECs, each of which represent one megawatt-hour of renewable generation. Analogous instruments used in other locations, such as Guarantees of Origin in Europe and green electricity certificates in China, are also permissible under the GHG Protocol Corporate Standard.

RECs were developed as a contractual mechanism for renewable electricity in response to the fundamental structure of "a power grid." In a power grid, it is impossible to link a single generator to a single load. Power is injected at a point in the grid and withdrawn at a different point in the grid; there is no traceable pathway.

RECs were created to track the attributes of electricity generation entering into a power grid for the entity that consumes the power at a different point. The GHG Protocol Corporate Standard allows buyers to claim exclusive use of renewable electricity with RECs even if they are actually consuming a mixture of electricity from the grid.

Renewable Energy Mechanisms Under the LCA ISO Standard

The ISO 14040 standard does not address the use of renewable electricity contracts. However, the ISO 14044 standard provides the following guidance:

"When determining the elementary flows associated with production, the actual production mix should be used whenever possible, in order to reflect the various types of resources that are consumed. As an example, for the production and delivery of electricity, account shall be taken of the electricity mix, the efficiencies of fuel combustion, conversion, transmission and distribution losses."

It does not explicitly define whether RECs can or cannot be used in the determination of the "actual production mix." In the event an organization does procure a renewable energy contract to reduce the emissions reported within the LCA, it should disclose that clearly in order to communicate the impact of the contract on the carbon intensity of the LCA with and without the use of RECs.

Powerful Tools for Different Use Cases

The GHG Protocol Corporate Standard and LCAs following the ISO Standard are both powerful tools that can provide insight into emissions associated with electricity use. The GHG Protocol Corporate Standard allows companies to use a standardized framework to report emissions associated with electricity use and interventions on an annual basis. The LCA ISO standard is a detail-driven analysis that allows a deep dive into specific processes, projects, or products. This detailed analysis allows for deeper insights into areas where a company may have more ability to address specific interventions for emission hot spots. Using these tools together, while understanding the boundaries of each, can provide companies with a more effective and impactful approach to decarbonization.

Frequently Asked Questions

What are the differences between the GHG Protocol Corporate Standard and LCA? 

The GHG Protocol is an annual corporate reporting framework covering scope 2 (generation) and scope 3: category 3 (transmission and distribution losses, fuel), while a cradle-to-grave LCA is a detailed analysis governed by ISO 14040/14044 standards that also includes manufacturing, construction, use-phase, and end-of-life emissions. LCA can also be applied to any product or process and multiple environmental impacts, not just greenhouse gas emissions.

Why do they result in different emissions for the same type and amount of electricity? 

They include different life cycle stages. The GHG Protocol excludes manufacturing, construction, and end-of-life emissions of generation equipment, while an LCA includes them.

Can renewable energy contracts reduce reported electricity-related emissions under both methods? 

Under the GHG Protocol, renewable energy contracts (e.g., RECs, PPAs) are explicitly allowed to report zero market-based scope 2 emissions, though scope 3 FERA emissions remain. Under ISO LCA standards, these contracts aren't explicitly addressed. Organizations may choose to apply them, but should transparently disclose LCA results both with and without the contract's impact.

When should you use the GHG Protocol vs an LCA? 

Use the GHG Protocol for standardized, annual corporate-wide emissions reporting and tracking procurement interventions; use an LCA for a detailed, process- or product-specific deep dive to identify specific emissions hotspots. Relae recommends using both together for a more complete, strategic view of electricity-related emissions.

Key Takeaways

• AI-driven data center demand is outpacing grid capacity, and hyperscalers are bringing more natural gas, which already supplies about 40% of US electricity, online to meet their needs.
• Pairing carbon capture and sequestration (CCS) with natural gas lets data centers source firm power today while cutting plant-level emissions up to 95%—without waiting on multi-year renewable interconnection queues.
• The Google-Broadwing deal demonstrates real progress and commitment toward natural gas with CCS as the first major commercial deployment of this exact pathway

Meeting Electricity Demand and GHG Emission Reduction Targets

Rapid growth in electricity demand across the US, driven by AI data center expansion and increased industrial electrification, is placing significant pressure on power grids. After decades of stable electricity load, demand has increased significantly since 2022 and is expected to rapidly grow for the foreseeable future. Natural gas currently fuels around 40% of US electricity generation. Its share is expected to grow in the coming years. However, unabated natural gas generation is not compatible with stakeholder targets to reduce greenhouse gas (GHG) emissions. Combining CCS with natural gas-fired generation is one pathway to meet growing electricity demand and achieve GHG emission reduction targets.

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The Role of Natural Gas in Electricity Supply

Natural Gas Generation Versus Renewable Generation Deployment

Electricity generators can provide multiple products to regional grids, generally providing two services: energy (power production) and reliability (consistent availability). Natural gas-fired plants can provide both, whereas renewable energy sources like wind and solar generate energy but offer less reliability. 

As electricity demand rapidly grows, grids will need both energy and reliability to function effectively. However, the interconnection queue for renewable energy assets has a years-long backlog which is delaying their deployment. Grids will need additional reliability assets to support the large amounts of renewables (usually in the form of storage). Some jurisdictions are creating an alternate pathway for natural gas plants to bypass the lengthy interconnection queue which may allow for the rapid development of natural gas generators.  Hyperscalers are also pursuing development of large behind-the-meter (BTM) generation of electricity from renewable and fossil sources, but these must also meet high standards for reliability. 

The Case for Carbon Capture Deployment

Electric utilities and developers of data center infrastructure are planning to build substantial new natural gas generation assets in addition to maximal deployment of renewable electricity. CCS technology enables natural gas plants to deliver stable, continuous power while significantly reducing emissions by capturing up to 95% of emitted CO₂. Natural gas plants with CCS are viable options to deliver the lower-emission, reliable power needed to respond to rapidly emerging AI data center power demand growth. The 45Q tax credit, a key government incentive for CCS, was preserved and effectively strengthened under 2025's One Big Beautiful Bill Act. The Google-Broadwing deal, the first major commercial deployment of this exact pathway, was signed in October 2025 and serves as a useful proof point.

Benefits of Integrating CCS into Natural Gas Power Generation

Integrating CCS into natural gas-fired power plants provides several advantages for data center stakeholders:

• Reduced carbon emissions: Achieve emission intensities of approximately 80–120 kg of CO₂ equivalent per megawatt-hour (CO₂e/MWh), significantly below the current US grid average of approximately 340–420 kg CO₂e/MWh.
• Reliable baseload power: Continuous, predictable electricity delivery.
• Compact infrastructure: Requires less land compared to renewable energy projects, simplifying data center siting near existing infrastructure.
• Cost: CCS integrated with new natural gas-fired generation can deliver low-cost decarbonization. Relae estimates $75-150/MWh, which is competitive in many markets with other firm baseload options such as new nuclear power or wind and solar with battery backup.

Seven Key Considerations for Implementing CCS

Stakeholders considering CCS technology must carefully evaluate seven critical factors:

1. Meeting Rapid Deployment Timelines

Traditional natural gas plants can be operational within roughly 18 months, provided they bypass interconnection queues for reliability purposes and have access to key equipment. Integrating CCS technology extends this by an additional 18–36 months. Designing plants to be "capture-ready" allows for quicker initial deployment and smoother CCS integration in the future. However, deploying a capture-ready plant without a commitment to build the carbon capture portion is inconsistent with serious climate action. 

2. Sizing Plants Optimally

CCS is most economically and environmentally optimal at natural gas plants with capacities of 100 MW or greater. It offers significant opportunities for emissions reductions for the forecasted new data center load. CCS is not suitable for smaller or highly variable natural gas plants.

3. Selecting Effective Carbon Capture Technology

CCS technologies such as solvents, sorbents, membranes, and oxyfiring vary significantly in maturity, efficiency, and cost. Choosing the right approach requires thorough evaluations aligned with specific project requirements. These will vary by setting and configuration (e.g., turbine class, reciprocating engines, number of units, water availability, etc.).

4. Navigating CO₂ Transportation Logistics

The safe and efficient transport of captured CO₂ via pipelines, rail, or barges is critical. Aligning infrastructure planning with overall project timelines prevents delays.

5. Ensuring Safe and Effective Sequestration

If there is no CO₂ storage, there is no project. Permanent CO₂ storage in Class VI injection wells requires detailed geological studies and regulatory permitting. Early collaboration with experienced sequestration operators is essential to success.

6. Conducting a Comprehensive Life Cycle Analysis

Full life cycle emissions analyses, including upstream methane leakage, construction impacts, and CO₂ transportation, are critical for accurate environmental assessments and ensuring low-carbon electricity supply. Prioritizing low-leakage, third-party verified natural gas supply enhances positive climate impacts.

7. Performing Siting Feasibility Early

An early and quick feasibility assessment is critical to identifying promising opportunities and key barriers at candidate CCS sites. Important factors include available transmission capacity, the potential to expedite approval of interconnection for thermal resources, regulatory barriers, state and local incentives, the sufficiency of natural gas infrastructure, and water supply.

Frequently Asked Questions

How much longer does adding carbon capture take compared to building a natural gas plant alone? Traditional natural gas plants can be operational within roughly 18 months, provided they bypass interconnection queues for reliability purposes and have access to key equipment. Integrating CCS technology extends this by an additional 18–36 months.

Is a "capture-ready" natural gas plant a legitimate climate strategy if the capture portion isn't committed yet? Designing plants to be "capture-ready" allows for quicker initial deployment and smoother CCS integration in the future. However, deploying a capture-ready plant without a commitment to build the carbon capture portion is inconsistent with serious climate action. “Capture committed” is a better stance than “capture ready”. 

How does the cost of natural gas-fired power with CCS compare to nuclear or renewables with battery storage? CCS integrated with new natural gas-fired generation can deliver low-cost decarbonization. Relae estimates $75-150/MWh, which is competitive in many markets with other firm baseload options such as new nuclear power or wind and solar with battery backup.

Has any hyperscaler actually deployed natural gas-fired power with CCS at scale yet? The Google-Broadwing deal, the first major commercial commitment of this exact pathway, was signed in October 2025 and serves as a useful proof point. Others are in development.

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How Relae Supports Data Center Decarbonization

Natural gas-fired generation combined with CCS is a proven solution for meeting the urgent electricity demands of data centers while significantly reducing emissions. Relae helps stakeholders navigate the complexities of CCS deployment through deep, science-backed expertise and strategic advisory services. Our experienced team provides comprehensive support throughout CCS project planning and execution, including technology selection, life cycle emissions analysis, infrastructure assessment, project viability, regulatory compliance, and risk management. 

Key Takeaways

• On April 16, 2026, two weeks before the Department of Energy’s (DOE) April 30 deadline for action on the Large Load Proceeding, FERC, the Federal Energy Regulatory Commission, provided a significant update: 
  
  • FERC issued its compliance order on PJM's Bring Your Own Generation (BYOG) tariff; the order approved four interconnection paths, rejected two PJM proposals, and directed PJM to refile by May 18. 
  • FERC's June 2026 order settled a key question around enforcement mechanisms for co-located projects. FERC rejected PJM's Two-Strike proposal (which would have terminated contracts on second violation), allowing only penalties and suspension from the three new transmission services, materially reducing developer downside risk.
  • Notably, BYOG arrangements built on the rejected elements of the compliance filing face restructuring risk before that refile. For deals that clear it, however, energization could begin as early as this summer.
• These proceedings reflect the underlying industry concerns about speed, reliability, and cost equity, shifting the risks and costs of new generation from ratepayers to the large loads, such as data centers, themselves. 
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• Developers, investors, and project teams can use quantitative grid and load modeling to navigate these risks successfully, converting regulatory exposure into priced engineering decisions.

A New Rulebook for Bring Your Own Generation in PJM

PJM Interconnection (PJM) hosts the highest concentration of data center load growth in the US, managing regional transmission across 13 states in the Eastern US, and commercial operation dates for new generation projects in its current interconnection queue stretch into the early 2030s. Bring Your Own Generation (BYOG) has become the fastest speed-to-power path around that bottleneck. 

BYOG allows large loads, such as data centers, to draw power directly from a co-located generation source connected to the bulk power grid, enabling developers to avoid lengthy interconnection queues and costly transmission upgrades, while drawing limited to no power from the bulk power grid.

The Federal Energy Regulatory Commission’s (FERC) April 16 order is now the rulebook that governs the tariffs that facilitate these BYOG arrangements. Any deal built on the paths FERC closed off must now find a way to align with one of the four approved mechanics before PJM's May 18 compliance refile. Deals that clear the refile could begin to energize as early as this summer.

Below are the top questions the Relae power advisory team is fielding most from hyperscalers, large commercial power buyers, and power producers navigating the mechanics of PJM’s BYOG tariff and the engineering realities of running a co-located project. 

What Is Co-Location?

Co-location refers to a power generation facility sited in close proximity to a large load, such as a data center, that interconnects directly to the bulk power grid. The generator serves that load contractually via a power purchase agreement (PPA), with power flowing through the meter.

BYOG is the predominant co-location model in PJM. Under a typical BYOG arrangement, on-site generation covers the majority of the data center's load (~90%), with only a small residual portion (~10%) supplied from the grid. Each co-located project effectively functions as its own mini-grid, with explicit operational obligations that are less forgiving than standard transmission service (NITS).

Why Did FERC Keep Behind-the-Meter (BTM) and Co-Location Separate?

While BTM and co-location may look similar, they sit in different regulatory buckets. That said, the line between them is less clear-cut than it once was. FERC found existing BTM rules inadequate to address the grid impacts of large co-located loads and directed PJM to treat co-location as a distinct framework. 

At the same time, BTM rules, including how tariffs and distribution charges are applied, remain under revision in a separate PJM proceeding. The two tracks moving in parallel have contributed to the conflation of the frameworks in industry discussion.

How Does Co-Location Differ from BTM Generation?

• Co-location, as this order defines it, is a bulk grid-interconnected arrangement. The host generator remains on the same interstate grid, maintains its interconnection service agreement, and continues exporting power to the grid. The co-located load connects through an approved interconnection mechanic and takes transmission service under a PJM tariff product.
• BTM is a distinct arrangement. The generator sits on the consumer's side of the utility meter and serves the load through a private line, without an interconnection agreement. The load may typically have a grid connection; however, in some circumstances, the generation may be fully off-grid or islanded. By setting a megawatt (MW) threshold for BTM, larger loads with co-located generation may no longer net out their load to reduce transmission and grid charges. FERC's jurisdiction over a BTM arrangement is narrower, and the tariff mechanics that apply to co-location do not apply in the same way.

FERC's rejection of PJM's proposed BTM rule changes illustrates this distinction. The commission is keeping the two categories separate on purpose. Ultimately, FERC’s intention seems to signal that large loads co-located with generation may not be adequately reflected in grid and transmission upgrade costs when these assets are behind the meter. Historically, BTM assets were exempt from these costs because their relatively insignificant power contributions had no meaningful financial impact on the bulk power grid.

That said, the BTM track is still moving. PJM's BTM application rules, including the netting-off mechanism that lets BTM loads avoid utility tariffs, remain under review in parallel proceedings.

For developers, regulatory clarity on co-location and BTM is increasingly critical. In April 2025, FERC upheld its rejection of the Talen-Amazon Susquehanna nuclear BTM interconnection agreement proposal, declining to rehear arguments on the initial decision. To many experts, the split ruling signaled that the structure of PJM’s interconnection service agreement (ISA) is inadequate for large loads operating behind the meter. 

However, in the initial challenge to the Talen-Amazon proposal, utility companies argued that the arrangement would unjustifiably shift transmission costs to other PJM customers. Ultimately, in June 2025, Talen Energy entered into a 1,920 MW, front-of-the-meter power purchase agreement with Amazon Web Services, which does not require FERC’s approval. 

FERC Has Always Regulated Generators, Not Loads. What Changed?

The April 16 order lands inside a larger jurisdictional shift. FERC does not typically regulate load interconnection; its authority sits with the bulk power grid. Under Orders 888 and 2003, FERC has regulated how generators connect to that system (with standardized study deposits, readiness requirements, and withdrawal penalties) while load interconnection has historically been regulated at the distribution level under state jurisdiction.

That generation-only approach to FERC regulation worked for three decades. Now, the scale of AI data centers and other large loads creates interstate impacts that state-level load regulation cannot fully address. Generation co-location breaks the pattern by routing the load through a FERC-regulated generator interconnection agreement rather than a state-regulated load-serving entity, pulling it into federal jurisdiction.

In December 2025, FERC declared PJM's existing interconnection rules (tariff) unjust and unreasonable in the PJM Co-Location Order and directed PJM to revise the tariff. The April 16 order is FERC's review of that rewrite. 

As FERC Commissioner David Rosner wrote in his concurrence to the December 2025 PJM Co-Location Order: "We are trying to meet surging demand while upholding two fundamental values that underpin the electric industry in our country: first, that all customers have a right to receive electric service on a timely basis, and second, that electric service should be reliable and affordable for all customers. Given the scale of new large loads putting demand on our grid today, it is clear that fostering both of these values requires intervention."

Which Four Interconnection Mechanics Did FERC Approve?

The April 16 order (Docket ER26-1088-000, 195 FERC ¶ 61,030) approves four ways for a data center to plug into the PJM grid. Each solves a different bottleneck: available capacity, queue position, study timing, or pre-studied capacity. All four rely on existing PJM and FERC tariff mechanics rather than new constructs, a deliberate choice to reduce legal exposure and speed up adoption. 

1. Sub-full-capacity interconnection service (available capacity). The data center co-locates with an existing host generator, and interconnects at less than the host generator's full capacity, using the portion of the existing interconnection rights the generator does not need.
2. Request acceleration at Decision Points I and II (queue position). Co-located load applications can move ahead of the standard queue at defined checkpoints, subject to PJM's study results. Co-located loads place less demand on the bulk power grid than new large loads without co-located generation, justifying the accelerated treatment. To qualify, projects must demonstrate there will be no significant network updates required or network impact, among other readiness milestones. 
3. Provisional Interconnection Service, or PIS (study timing). Interim interconnection services are provided during the full study, giving developers a bridge to early operations.
4. Surplus Interconnection Service, or SIS (pre-studied capacity). Use of unused capacity at an already-studied generator’s interconnection point, without triggering a new full study.

The four mechanics are different ways of answering the same operational question—how a co-located data center plugs into the grid without triggering a multi-year re-study of the host generator's interconnection—enabling faster speed-to-power.

Which Generators Gain Most From Surplus Interconnection Service?

SIS is the most commercially interesting of the four mechanics for existing generator owners because it monetizes previously stranded capacity.

The generators that benefit most include:

• Retiring or derated thermal units with unused megawatts of interconnection rights at high-value points (for example, retiring coal plants in PJM's eastern and mid-Atlantic footprint).
• Existing nuclear and large thermal plants near concentrated load growth, particularly in Dominion, American Electric Power (AEP), and ComEd territory (the Northern Virginia, Columbus, and Chicago metro zones), where PJM load is most concentrated.
• Storage-paired assets where the underlying generator has capacity headroom that the storage does not fully use (for example, solar-plus-storage or gas-plus-storage sites where the battery sits below the full interconnection rights).

For illustration, a host generator running at roughly 85% of its interconnection rights with a forced outage rate near 5% has material surplus capacity (10%) available to a co-located load, depending on how PJM studies the combined profile.

Owners of underutilized interconnection rights now have an approved tariff path to extract value from them by attracting data centers to co-locate with these generators.

What Transmission Service Does a Co-Located Load Receive?

Connecting to the bulk power grid and taking service from it are two separate decisions. PJM's default transmission service for any load on the system is the Network Integration Transmission Service (NITS), the standard contract for firm power year-round. NITS commits PJM to serve a customer’s full load at any and all times, meaning that PJM may need to wait for generation and/or transmission upgrades before offering it to a large load. 

Recently, PJM reopened its generation interconnection queue after pausing to study its backlog of proposed projects. With 800 proposed projects representing approximately 220 GW in new capacity in 2026, this growth signals progress, but it does not address the underlying permitting and financing challenges that have prevented projects already in the queue from being built.  

The BYOG mechanics are variations that waive or defer parts of NITS for faster speed-to-power. PJM delivers the resulting service through three tariff product types:

1. Firm contract demand: The co-located load holds firm transmission service (consistent with most aspects of NITS) and operates like any other firm load on the system. Availability is site-specific, depending on the point of interconnection. Unlike other NITS customers, entities contracting firm contract demand transmission on behalf of co-located loads cannot exceed the contracted demand level, and loads would be subject to a penalty if they withdraw additional energy beyond the contracted demand capacity. 
2. Non-firm contract demand: The load accepts interruption risk in exchange for faster interconnection or lower-cost service, making it better suited to loads with operational flexibility. It is available at more interconnection points than firm service, but power delivery is subject to curtailment based on real-time grid conditions. This service intends to provide brief and intermittent energy access from the bulk power grid, during available periods, under unanticipated circumstances, such as downtime for the co-located generator. 
3. Interim NITS: A bridge product that provides firm service on an interim basis while the co-located generator is still under construction. The load energizes early; once the generator and any transmission upgrades are complete, the project transitions to a standard NITS arrangement, and the generator can participate in the broader PJM market. However, while the load pays the NITS rate, the load is subject to curtailment under system emergency conditions, posing reliability challenges. 

In practice, a 1,000 MW data center co-located with a 900 MW on-site generator would request 100 MW from PJM under one of these three products.

The interconnection mechanic (how the load connects) and the tariff product (what service the load receives) are two distinct decisions. For example, in the case of an interim NITS, a data center and co-located load could connect through a Provisional Interconnection Service (PIS). Other co-located loads may connect by submitting a request for acceleration at Decision Points I and II to secure firm contract demand service. The connection mechanism and tariff will vary based on each co-located load’s unique characteristics and project configuration. 

For clients evaluating specific sites, the right path depends on how much of the host generator's interconnection capacity is available, how sensitive the load is to interruption, and how fast the site needs to energize. Grid modeling allows project teams to quantitatively assess their risk exposure before committing to a tariff product. 

Which Two PJM Proposals Did FERC Reject?

Two elements of PJM's original filing did not make it through the April 16 order.

1. Point of Change in Ownership substitution: PJM proposed swapping in "Point of Change in Ownership" for FERC’s mandated term "Point of Interconnection" in the definition of Co-Located Load. FERC rejected the swap as an unexplained deviation from the Co-Location Order's definition and because it could let transmission owners delay or effectively veto the Point of Change in Ownership location, creating uncertainty for co-located projects.
2. BTM application-rule changes: PJM tried to fold changes to its BTM application rules into this same compliance package. FERC rejected that on the ground the changes did not fall within the scope of the initial order. BTM remains a separate regulatory track; the April 16 order does not settle it.

Project configurations built on either rejected proposal need restructuring before PJM's May 18 refile.

The order also directs PJM to add the PIS definition to the Open Access Transmission Tariff (OATT), Part I, section 1 (paragraph 26), and flags items in paragraph 29, including assessment of the reliability of co-located loads paired with electric storage, as out of scope. 

These determinations should not be seen as FERC rejecting these tariff changes, but rather deeming them outside the scope of the order. They are open questions that belong in a separate docket. The direction to include PIS while declining to address issues not included in the compliance proceeding demonstrates FERC’s focus on speed-to-power, clarifying the rules for new co-located generators to connect to the grid more quickly.  

What Is the Two-Strike Reliability Rule, and Why Does it Matter?

The rules for violating a co-location interconnection service agreement are still being developed, but FERC has urged PJM to issue robust protections to maintain reliability and cost allocation equity. 

For both firm and non-firm contract demand transmission service, PJM will apply a penalty rate to transmission service customers who withdraw more energy from the grid than was contracted. The precise design of these rates for unreserved use is scheduled for a paper hearing this spring; however, developers should cautiously size and appropriately model load and generation sizes, as the penalties for jeopardizing PJM’s reliability are not limited to rates. 

While penalty rate design for unreserved use is underway, PJM proposed a strict Two-Strike reliability rule for co-located projects. If a co-located customer failed to adequately implement automated loadshedding or generator tripping mechanisms during unusual grid conditions, PJM has previewed severe consequences:  

• First strike: a 120-day operational pause for review.
• Second strike: termination of the transmission service contract and return to the NITS interconnection waitlist.

The entire purpose of pursuing a co-located large load configuration is to ensure speed-to-power while maintaining reliability. In a June 2026 order, FERC conceded that there are legitimate reliability concerns with co-located generation misoperation; however, PJM’s proposal to disqualify customers with multiple misoperations is unnecessarily strict. FERC ultimately agreed PJM has the authority to charge penalties to and temporarily suspend services for customers that fail to shed load or curtail, but cannot disqualify customers for misoperation. Data centers will need to rigorously model and design their co-located load and generator facilities with the understanding that multiple reliability violations could strand billion-dollar assets for multiple years. 

Which BYOG Deals Need Restructuring Before the May 18 Refile?

Any deal built around the Point of Change in Ownership substitution or the BTM application-rule changes that FERC rejected needs restructuring. 

In addition, co-located projects that relied on one of the four approved mechanics, but used PJM tariff language from the original December filing, may also need re-papering against the language PJM submits in its forthcoming May 18 compliance filing. Until PJM files that package and FERC accepts it, the operative document is the April 16 order itself.

Counterparties should confirm that operational controls, curtailment rights, and dispute mechanisms in the contract align with the proposed Two-Strike regime and the approved mechanics the project uses.

What Does Grid Modeling Reveal for a Co-Located Project?

Non-firm service is the lowest-cost tariff product for the portion of load the co-located generator does not serve, but availability depends on real-time grid conditions. Grid modeling is how developers size that exposure before signing.

Take the same 1,000 MW data center paired with a 900 MW on-site generator, contracting 100 MW of non-firm service for the residual load. Grid modeling might show non-firm power dropping out in roughly 15% of hours during the summer peak.

If the on-site generator also carries a 5% forced outage rate, the developer faces a meaningful probability of a compound event: grid supply drops out at the same moment the on-site unit trips offline.

In that window, the data center has three options, none of them free: 

1. Curtail load. 
2. Shift the load to another site. 
3. Draw more from the grid than the contract allows, which triggers a Two-Strike violation.

Grid modeling converts that risk into decisions the developer can price. A developer can test whether adding 50 MW of battery storage, contracting 150 MW of firm service instead of 100 MW of non-firm, or adding a smaller backup generator delivers the best risk-adjusted return.