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  • At 40 Minutes per Trailer, Oracle’s AI Gas Stopgap Has a Ceiling

    At 40 Minutes per Trailer, Oracle’s AI Gas Stopgap Has a Ceiling

    TL;DR · 30-second read

    The Short Version

    Oracle, the business-software giant, is building huge computer warehouses for artificial intelligence faster than the gas pipelines meant to power them can be finished. So it is filling trucks with natural gas and driving the fuel to the sites instead.

    It works, but the gas costs roughly four times its normal price. It also does not go far. Running even a small slice of one planned site in New Mexico would need a fresh truckload about every 40 minutes, day and night.

    The lesson is that building artificial intelligence now depends on pipes, permits and trucks, not just computer chips.

    Bloomberg reported that Oracle has been trucking compressed natural gas (CNG) directly to several data center sites so that on-site generators can run before permanent gas pipelines are ready. According to people familiar with the work, truck deliveries kept a data center outside Salt Lake City moving for more than a year while Oracle waited for a pipeline. The same approach is supporting initial work at a campus Oracle is building for OpenAI in Shackelford County, Texas. Oracle is now considering it for Project Jupiter in New Mexico, where a delayed pipeline threatens the timeline of a site with an ultimate footprint of 2.45 gigawatts.

    Certarus, a unit of Superior Plus, supplied the Utah deliveries, and VoltaGrid supplies Texas. Oracle publicly thanked VoltaGrid for “finding cost-effective power solutions to ensure our customers can access OCI capacity on schedule,” referring to Oracle Cloud Infrastructure. Last month Oracle sent the New Mexico project’s developer a force majeure notice. Oracle shares closed down 5.5% at $135.69, their steepest one-day drop since July 16.

    Executive Summary

    The announcement-free headline here is a supply chain story. Many large AI data centers have turned to on-site gas-fired power plants because grid connections take too long. Those plants still need fuel, and fuel normally arrives by pipeline, which can take months to design and build and can be held up by regulators. Oracle is filling that gap with “virtual pipelines”: fleets of trucks hauling compressed gas from a pipeline tap to the site, where it is decompressed and burned in generators.

    The approach buys time, but it has limits. Jack Weixel of East Daley Analytics puts the delivered cost at roughly four times the price of gas at a major pipeline hub once labor, specialized equipment and truck fuel are included. Ellie Holbrook of SemiAnalysis estimates that if Project Jupiter ran just 100 megawatts on trucked gas, which is about 4% of its planned capacity, each large trailer would supply only about 40 minutes of electricity. Trucked gas can energize the first phases of a campus. The date the whole campus comes online is still set by the pipeline.

    For the industry, the episode adds a new item to the list of things that can delay a data center. Developers already track turbines, transformers and interconnection queues. Gas logistics now belongs on that list too, along with the regulators who approve pipeline routes.

    The Trailer Math Sets the Ceiling

    Holbrook’s figures are the clearest way to see how far a virtual pipeline can stretch. At a 100-megawatt load, one large CNG trailer lasts about 40 minutes. A day has 1,440 minutes, so running that load around the clock means roughly 36 trailer loads every day, or one arrival every 40 minutes with no gaps for weather, traffic or a missed fill. Each load is a full cycle. Gas is drawn from a pipeline, compressed into the trailer, driven to the site (sometimes for several hours), then decompressed into the generators. A trip that long ties up several trailers on the road for every one unloading, so the fleet behind a steady stream of arrivals is much larger than the arrival count.

    That 100 megawatts is only about 4% of Project Jupiter’s planned 2.45 gigawatts. As a rough illustration, if fuel demand scaled in a straight line with load, the full footprint would need close to 900 trailer loads a day. No one has proposed doing that, and the arithmetic shows why. Trucked gas is a bridge sized for early phases, such as commissioning, initial server halls and construction power. It cannot replace a pipeline at campus scale.

    The consequence for people planning AI capacity is straightforward. A virtual pipeline can move the date a site first produces revenue. It does not move the date the site reaches full capacity. That second date still depends on Energy Transfer’s rerouted pipeline, which has slipped from this summer to next year.

    Fuel Logistics Joins Turbines and Grid Queues on the Critical Path

    On-site gas generation became popular because it let developers skip the years-long wait to connect to the electric grid. The Oracle sites show that the workaround brings its own bottleneck. A gas plant without a gas pipeline is idle equipment, and pipelines face many of the same constraints as power lines. In New Mexico, state regulators rejected Energy Transfer’s proposed route, forcing a reroute that pushed back the in-service date. The approval delay simply moved from the power line to the pipe.

    This has practical effects on how sites are chosen and planned. When fuel may need to arrive by road for a year or more, as it did in Utah, factors that rarely appeared in data center site studies start to matter. These include the distance to a pipeline tap with available compression, road access able to handle constant heavy-truck traffic, and on-site space for decompression equipment and trailer staging. Developers comparing sites need to weigh the logistics of the interim fuel supply alongside land, water and fiber.

    The suppliers stand to benefit. Until now, CNG trucking has mostly served remote mining and oil drilling operations far from the grid. Certarus and VoltaGrid are now marketing to data center builders as a transitional power source. Certarus said longer timelines for pipeline and grid connections “have created a growing need for rapidly deployable and scalable energy solutions.” Whether these services can scale is a separate question. The number of trucks, compressors and trailers available, along with the drivers to move them, sets a physical limit on how many large campuses can rely on trucked gas at the same time.

    Paying Four Times for Speed

    Oracle described VoltaGrid’s service as “cost-effective,” while East Daley’s estimate puts trucked gas at about four times hub prices. The two claims can both hold, because they measure different things. Per unit of fuel, trucked CNG is expensive. Compared with leaving finished data halls empty, missing delivery dates for customers such as OpenAI, or facing contractual exposure, a costly fuel bill can still be the cheaper choice. Oracle has not disclosed the numbers that would show which effect is larger.

    Those numbers matter because of Oracle’s financial position. Its free cash flow is negative and is expected to stay that way until more of its AI data centers are completed, so each month a site comes online earlier brings revenue forward. The force majeure notice points to the same pressure from another direction. A force majeure clause excuses a party from certain obligations when events beyond its control occur, and Oracle’s notice may shield it from some payments to the New Mexico developer if delays continue. The trucks and the notice are two responses to the same pipeline delay. One keeps work moving, and the other limits the cost if work stalls.

    The open question for investors and customers is where the extra cost lands. It could reduce Oracle’s margins in the early phases, be passed through to the tenant, or be absorbed through the developer agreement. None of these arrangements has been made public, and the answer will determine whether trucked gas is a minor bridging expense or a significant cost of speed.

    Background

    Oracle, long known for database and business software, has become a major builder of AI data centers through Oracle Cloud Infrastructure (OCI). It has committed billions of dollars and its reputation to delivering capacity quickly for customers including OpenAI, and its free cash flow is expected to remain negative until more of those facilities are complete. Its projects include a campus for OpenAI in Shackelford County, Texas, a data center near Salt Lake City, and Project Jupiter in New Mexico.

    Power has become one of the main constraints on the AI data center buildout. Many large developments now generate their own electricity with on-site natural gas plants rather than waiting for grid connections. That approach depends on gas pipelines, which take months to design and build and can be delayed by regulators. Compressed natural gas trucking companies such as Certarus and VoltaGrid, which previously served mainly remote mining and drilling operations, are now offering their services to data center developers as a temporary fuel supply.

    Sources

    Source: Oracle Moves Gas by Trucks to Avoid Data Center Power Delays (SupplyChainBrain, via Bloomberg) on Oracle’s use of trucked compressed natural gas to keep data center projects in Utah, Texas and New Mexico on schedule.

  • Oracle’s Stargate Notice: A 2.45 GW AI Campus Runs on a Gas-Permit Clock

    Oracle’s Stargate Notice: A 2.45 GW AI Campus Runs on a Gas-Permit Clock

    TL;DR · 30-second read

    The Short Version

    Oracle, a major technology company, is the main tenant of a giant planned artificial-intelligence computing site in New Mexico called Project Jupiter. It is designed to use about as much electricity as two and a half large nuclear reactors produce.

    Oracle has sent the site’s builder a legal notice. The notice lets Oracle hold back payments if the site isn’t ready by 2028 because of events outside its control.

    The real issue is power. The site will make its own electricity from natural gas, but the gas pipeline has slipped to 2027 and a key air-pollution permit is still undecided. Oracle says the project is on schedule.

    Oracle has sent a force majeure notice to the developer of Project Jupiter, a 2.45-gigawatt Stargate data center campus in New Mexico, Bloomberg first reported on September 24, as relayed by TechCrunch. Blue Owl Capital said its unit received the notice. According to Bloomberg’s sources, Oracle is not seeking to exit as the campus’s main tenant; the notice would instead allow it to delay payments if the facility misses its 2028 target to come online.

    Both companies played the move down. “Project Jupiter remains on our planned schedule,” Oracle told CNBC. “We are fully committed to New Mexico and confident in our path forward.” Blue Owl told CNBC that “this notice does not change the financial commitments to this multi-year project.”

    Executive Summary

    A force majeure clause excuses a party from contractual obligations when events outside its control get in the way. Oracle’s notice cancels nothing. It reserves the right to push back Oracle’s payments to the developer if Project Jupiter is not ready by 2028, while both Oracle and Blue Owl say no delay is expected and no financial commitment has changed.

    The reason the notice matters is the campus’s power design. Jupiter is meant to generate its own electricity with Bloom Energy fuel cells running on natural gas, and the gas supply around it has already slipped: an Energy Transfer pipeline to the site has been pushed back nearly six months, to February 1, 2027, after regulators repeatedly denied permits. The fuel cells’ air-quality permit is still pending, with a state decision due by November 23.

    For one of Stargate’s flagship sites, the schedule that decides when AI capacity actually arrives now runs through two energy permits rather than through the construction site alone.

    A Notice That Reserves Options, Not an Exit

    Force majeure provisions are standard in energy and commodities contracts, and many contracts require prompt notice of a qualifying event before a party can rely on the clause. A notice can therefore be as much about preserving rights as about predicting a delay. That reading fits both public statements: Oracle says Jupiter is on schedule, and Blue Owl says the financial commitments are unchanged.

    Both claims can be true at once, but they do not fully dissolve the tension. A tenant certain of a 2028 delivery has less reason to formally reserve payment relief. The most even-handed interpretation is that the notice works like insurance: it is bought against a risk the buyer does not expect but cannot rule out. The question for everyone else is what that risk is.

    For a 2.45 GW AI Campus, Gas Permits Set the Clock

    Project Jupiter is designed for 2.45 gigawatts, roughly the output of two and a half large nuclear reactors, and it is meant to run on Bloom Energy fuel cells, which turn natural gas into electricity through a chemical reaction rather than by burning it. That makes the campus effectively its own power plant. It also means the facility cannot operate without a steady gas supply, so the pipeline and the fuel-cell permits sit on the critical path, the chain of tasks that sets the earliest possible finish date.

    Two links in that chain have already moved. Energy Transfer’s pipeline to the site is now due February 1, 2027, nearly six months late, after regulators repeatedly denied permits; in August, Bloomberg reported that the route had been changed in response. Separately, New Mexico’s environment department faces a November 23 deadline to rule on the air-quality permit for the fuel-cell system. Neither is a construction problem that more crews or more capital can speed up. Each is a regulatory decision on its own calendar.

    On-site generation is often pitched as a way around years-long waits to connect to the public grid. Jupiter shows the trade-off: it swaps the utility’s interconnection queue for pipeline routing and air permitting. A February 2027 gas date still leaves room before a 2028 opening, but less than before, and if that margin runs out, the force majeure notice is the mechanism that decides who absorbs the wait.

    Who Carries the Timing Risk

    AI data center developers are taking on steep costs to build capacity ahead of demand from customers like OpenAI. A developer’s return depends on the tenant’s payments starting when the building is delivered. A clause letting Oracle defer those payments if 2028 slips shifts the cost of waiting toward the landlord side, here the developer and Blue Owl’s unit, and toward anyone who financed the project against its expected income.

    Blue Owl’s statement that the notice does not change the financial commitments is accurate on its face: deferring a payment is not cancelling it. But for a project funded on expected cash flow, the timing of that cash matters. Until the parties say how long payments could be deferred and on what terms, outsiders cannot size that exposure.

    A Political Flashpoint With a Deadline Attached

    Jupiter has drawn opposition from residents and environmental groups and has become a political flashpoint ahead of the midterm elections. Oracle has responded with a public outreach campaign in the state aimed at winning over critics, according to Bloomberg. The pending air permit ties that debate directly to the timetable.

    Fair questions apply on both sides. Critics’ concerns about gas-fired generation and air quality are exactly what the permit process exists to test, and repeated pipeline permit denials suggest that process has teeth. The companies, for their part, have put confident schedule statements on the record while reserving contractual relief. The November 23 permit decision will be the first hard evidence of which posture the facts support.

    Background

    Stargate is the AI infrastructure initiative that Oracle, OpenAI and SoftBank announced with President Donald Trump early in his second term, with the aim of building very large computing campuses in the United States. Project Jupiter in New Mexico is one of its flagship sites. Oracle is the main tenant; it sent the notice to the project’s developer, and Blue Owl Capital, an investment firm, said its unit received it.

    Jupiter’s energy plan relies on fuel cells from Bloom Energy running on natural gas, delivered by a pipeline from Energy Transfer, a pipeline operator. Because the campus makes its own electricity rather than drawing primarily from the grid, its gas supply and air-quality permitting are as important to its opening date as the buildings themselves.

    Sources

    Source: Oracle sends force majeure notice on its New Mexico Stargate data center — TechCrunch, September 24, 2026, reporting Bloomberg’s account of the notice and statements from Oracle and Blue Owl to CNBC.

    Primary sources: Oracle Corporation, Schedule 14A definitive proxy statement (DEF 14A), filed September 25, 2026 — Oracle’s proxy statement, including executive-compensation disclosures.

  • Blue Energy’s 2.5-GW Texas Hybrid Shows Why AI’s First Nuclear Megawatts Burn Gas

    Blue Energy’s 2.5-GW Texas Hybrid Shows Why AI’s First Nuclear Megawatts Burn Gas

    TL;DR · 30-second read

    The Short Version

    • A startup called Blue Energy asked federal nuclear regulators for permission to build a power plant on the Texas coast that runs on both natural gas and small nuclear reactors.
    • The electricity would feed a computing site built by Crusoe for artificial intelligence — buildings full of computers that need power around the clock.
    • Here is the catch: the gas part gets built first, by around 2030. The reactors come later, in the 2030s.
    • So the plant sold as nuclear will spend its early years running mostly on gas.

    EnergyTech reported that North Carolina-based startup Blue Energy has submitted its first construction permit application to the U.S. Nuclear Regulatory Commission for a hybrid gas-and-nuclear generating station at the Port of Victoria, Texas. The project would pair a GE Vernova 7HA.02 gas turbine with the GE Vernova-Hitachi BWRX-300 small modular reactor, building toward a 2.5-gigawatt plant by the early 2030s that would serve an AI data center — an “AI factory” — developed by Crusoe, along with other loads.

    The build is staged. Phase one centers on the gas turbines, which the company says are the quickest to install and commission, targeted for the end of this decade. Phase two would add perhaps five BWRX-300 units, each generating close to 300 megawatts at capacity, with the gas units eventually phased out or reduced. Blue Energy estimates project cost at more than $6 billion, with Société Générale acting as lead financial advisor.

    Executive Summary

    The filing is a procedural milestone rather than a construction start, and that distinction matters. No small modular reactor has been fully approved or begun construction in the United States. Federal applications of this kind typically take years to move through technical and environmental review before a permit issues. Blue Energy is entering a queue that also contains the Tennessee Valley Authority’s BWRX-300 application at Clinch River — which GE Vernova Hitachi says is approaching a decision — and applications from other developers including X-energy.

    What makes the Victoria project analytically interesting is not the reactor. It is the sequencing. A 2.5-gigawatt site whose first phase is combustion turbines and whose second phase is five reactors is, for the first several years of its operating life, a gas plant with a nuclear option attached. If roughly five units at close to 300 megawatts each eventually arrive, that implies on the order of 1.5 gigawatts of nuclear capacity and the balance from gas — meaning the gas fleet is not a token bridge but a substantial share of the nameplate.

    For GE Vernova, the strategic value is fleet economics: the same reactor design, the same licensing work and the same supply chain applied across multiple sites, so that each project is cheaper and faster than the last. For data center developers, the practical value is that a credible nuclear pathway may make a gas-first interconnection easier to defend to customers and communities that have made carbon commitments.

    The Permit Is Nuclear. The First Electrons Are Gas.

    Read the phasing literally. Blue Energy says phase one focuses on the gas turbines because they are the quickest to install and commission, with a target of the end of this decade. Phase two would add perhaps five BWRX-300 reactors, each producing close to 300 megawatts — a megawatt being roughly the power draw of a few hundred homes, and 300 megawatts being enough for a serious data center campus on its own. The total plant is described as 2.5 gigawatts by the early 2030s. Subtract the nuclear arithmetic from the total and roughly a gigawatt of gas-fired capacity is carrying the site before the reactors show up, and continuing alongside them after.

    That is the operational conclusion buried in an otherwise routine regulatory filing. Crusoe’s AI factory, if it energizes on the announced schedule, will be a nuclear-adjacent load long before it is a nuclear-powered one. Nobody has misstated this — the release is explicit that gas comes first and that the gas units would later be “phased out or reduced.” But the framing of hybrid gas-nuclear projects generally, and the headlines they generate, tend to lead with the reactor rather than with the turbine that will actually be spinning in 2030.

    Who this affects: any hyperscaler or AI developer signing power agreements against projects like this one needs to price two different assets. The near-term asset is dispatchable gas generation with commodity and emissions exposure. The long-term asset is a first-of-a-kind reactor deployment with schedule and licensing risk. Blending them into one “clean firm power” line item on a sustainability disclosure understates the first and overstates the certainty of the second. The honest version is that gas is buying time for nuclear to clear regulatory review — which is a defensible strategy, just not the same claim.

    Fleet Licensing Is the Product GE Vernova Is Actually Selling

    Jason Cooper, CEO of GE Vernova Hitachi Nuclear Energy, framed the Blue Energy filing around repeatability: “This is what fleet deployment looks like: projects advancing on common technology, licensing work and supply chain capabilities, allowing us to apply lessons from one project to the next.” That sentence is the commercial thesis of the entire small modular reactor category, compressed.

    Conventional nuclear construction in the United States has been defeated less by physics than by one-off engineering. Every plant a bespoke design, every licensing review starting near zero, every supply chain assembled and then dispersed. The BWRX-300 bet is that if the same design goes through the Nuclear Regulatory Commission repeatedly — Clinch River with the Tennessee Valley Authority, now Victoria with Blue Energy — the review gets shorter, the vendors keep their tooling, and the crews carry experience forward. Blue Energy’s Jake Jurewicz echoed the point, saying the team moved from technology selection to construction permitting “in a matter of months.”

    The claim is plausible and, so far, unproven at the only point that counts: a completed unit. Nothing in the release establishes that the second application will be reviewed faster than the first, or that fabrication cost falls on unit two. Investors and buyers should watch the Clinch River decision closely, because it is the first real data point on how much of the fleet argument the regulator is prepared to credit.

    More Than $6 Billion, and the Project-Finance Test

    Blue Energy puts the project above $6 billion and has engaged Société Générale as lead financial advisor. Kim Hill, the bank’s transaction lead, described the mandate as a step toward deploying private capital markets for advanced nuclear “just like it has for wind, solar, and battery technologies.” That comparison is the tell. Wind, solar and storage became bankable because their capital costs are predictable, their construction windows are short, and their revenue is typically locked to long-term contracts before anyone breaks ground.

    Advanced nuclear does not yet satisfy the first two conditions in the United States — no unit has been built to prove them. Which is another reason the gas-first phasing is more than an engineering convenience: turbines are a financeable, well-understood asset class with an established construction schedule, and early cash flow from gas generation changes the risk profile a lender sees when it underwrites the reactors behind it. The strategic investor list, which includes Constellation Technology Ventures, VXI, Engine Ventures, At One Ventures and Tamarack Global, reflects venture-stage risk tolerance; a $6 billion project needs a different class of capital entirely.

    Why the Load Growth Argument Has Real Force — and Its Limits

    Nuclear supplies about 18% of the U.S. utility-scale electricity mix, and the fleet spent years under pressure from operating costs, cheap gas, renewables and, critically, flat demand. Data center growth has reversed the demand assumption, and the industry’s argument is that carbon-free baseload — power that runs continuously rather than when the wind blows — is the natural answer for loads that run at high utilization around the clock.

    The counterargument, which the release also records, is that nuclear projects remain expensive, slow and contested on health and safety grounds. Both positions can be evaluated on evidence rather than assertion, and the evidence arrives on a schedule: permit decisions, construction starts, and the first concrete date. Until then, the sharpest thing to say about Victoria is that it is a credible attempt at a genuinely difficult sequencing problem — build generation fast enough for AI load that exists now, while licensing generation clean enough for the commitments that load has already made.

    Background

    Blue Energy is a North Carolina-based startup pursuing what it describes as a repeatable, rapidly built approach to new nuclear construction — EnergyTech has previously reported the company raised $380 million to advance prefabricated reactor construction. It selected the BWRX-300 design earlier this year for co-location with gas turbines and, by its own account, moved from technology selection to federal construction permitting within months.

    The BWRX-300 is a boiling water small modular reactor from GE Vernova Hitachi Nuclear Energy, a joint venture between GE Vernova and Hitachi. It is the design furthest along in the U.S. licensing process, through the Tennessee Valley Authority’s Clinch River project, and has been selected by several developers internationally. The broader context is a U.S. power sector that spent a decade planning around flat demand and is now contending with data center and AI load growth that has made firm, round-the-clock generation scarce and valuable again.

    Sources

    Source: SMR Startup Blue Energy, GE Vernova-Hitachi Seek Federal Construction Permit for Gas-Nuclear Hybrid — EnergyTech’s report on Blue Energy’s NRC construction permit application for a 2.5-GW gas-and-SMR plant at the Port of Victoria, Texas, intended to serve a Crusoe AI data center.

  • Constellation Buys Shell’s Rhode Island Gas Plant for $715M

    Constellation Buys Shell’s Rhode Island Gas Plant for $715M

    TL;DR · 30-second read

    The Short Version

    Constellation, one of the largest electricity producers in the United States, is paying $715 million to buy a natural gas power plant in Rhode Island from the oil company Shell. As part of the same package, Shell takes over Constellation’s share of a gas plant in Pennsylvania.

    Nobody is building anything new here. Two big companies are trading plants that already exist and are already plugged into the grid.

    That matters because the giant computer warehouses behind artificial intelligence are soaking up electricity faster than new plants can be built. A plant you can switch on today is now worth a great deal.

    Constellation Energy has agreed to acquire the Rhode Island State Energy Center, a gas-fired power station, from Shell for $715 million, and in the same package to hand Shell its interest in the Hunlock Creek generating station in northeastern Pennsylvania. Reuters reported the two legs as a single transaction announced together, with cash moving one way and a minority generating stake the other. Constellation has said it expects the purchase to be accretive, meaning it should add to per-share earnings rather than dilute them.

    The timing sits inside a busy stretch for Shell’s portfolio. In a Form 6-K filed with the Securities and Exchange Commission on September 3, Shell confirmed it had completed its acquisition of ARC Resources on September 2, a roughly $16.5 billion enterprise-value deal that adds about 370,000 barrels of oil equivalent per day of Canadian production. Selling a single merchant power plant in New England while closing a multibillion-dollar upstream gas acquisition is a fair summary of where Shell is putting its capital.

    Executive Summary

    The headline number is $715 million for a combined-cycle gas plant, but the structure is the more interesting part. Constellation is buying full ownership of dispatchable capacity in New England, generation that can be called on when the grid needs it rather than when the weather allows it. At the same time it is releasing a partial interest in a Pennsylvania plant to a buyer that wants a position there. Each side is trading breadth for concentration.

    For Constellation, already the largest operator of nuclear plants in the country, gas is the flexible complement to an around-the-clock nuclear fleet. Nuclear runs flat out; gas fills the peaks, backs up intermittent renewables, and earns capacity payments for simply being available. Owning both in the same regions gives a generator more ways to sell the same megawatt.

    For Shell, the sale continues a steady retreat from owning physical power stations in North America while it concentrates on producing and trading the gas that fuels them. The Hunlock Creek leg complicates a clean narrative of exit, and neither company has explained what Shell intends to do with that position.

    Steel in the Ground Beats Steel on Order

    The scarcest thing in American power right now is not a turbine. It is a finished plant with a signed grid connection. Interconnection queues, the waiting lines developers join to attach a new project to the transmission system, run for years in most regions. Gas turbine manufacturers have sold out much of their delivery capacity into the next decade. Against that backdrop, a plant that is built, permitted, connected and running carries a premium that has very little to do with the cost of replicating it.

    That is the logic behind a $715 million cheque for an asset nobody is describing as new. Constellation is buying time. Every year of permitting and construction it skips is a year of capacity revenue and energy margin it collects instead. The same arithmetic explains why merchant generators across the Northeast have spent the past two years buying each other’s plants rather than breaking ground on their own.

    The risk is symmetrical. Paying a scarcity premium works only if scarcity persists. If load growth from data centers arrives more slowly than forecast, or if the current wave of announced projects actually gets built, today’s premium prices become tomorrow’s writedowns. Constellation has not published the assumptions behind its accretion claim, so outsiders cannot see which side of that bet it is making.

    Two Grids, Two Different Bets

    Rhode Island sits inside the six-state New England grid, run by ISO New England. Hunlock Creek sits inside PJM, the grid operator covering 13 states and the District of Columbia from New Jersey west to Illinois. The swap therefore does something more specific than consolidate: it deepens Constellation’s position in New England while trimming a minority holding in PJM, and it gives Shell a foothold in the market where capacity prices have risen most sharply.

    PJM is where the data center load story has been loudest, driven by northern Virginia and spreading into Ohio, Pennsylvania and Maryland. Its recent capacity auctions, the periodic sales where generators are paid to guarantee availability years ahead, have cleared at record levels precisely because demand forecasts rose while older plants retired. New England has a quieter but structurally tighter story: less land, constrained pipelines into the region during winter cold snaps, and an aggressive state-level push toward renewable retail supply that raises the value of firm capacity even as it discourages new fossil construction.

    Read that way, Constellation is not buying into a boom. It is buying into a squeeze. New England needs dispatchable generation to stay reliable in February regardless of what its decarbonisation policy says about 2033, and the plants that remain face little prospect of new fossil competition. That is a defensible position to own, and a politically exposed one.

    For Shell, Power Plants Are No Longer the Point

    Shell’s direction of travel is visible in its own filings. The completion of the ARC Resources acquisition on September 2, disclosed in a Form 6-K, added roughly 370,000 barrels of oil equivalent per day and was framed by chief executive Wael Sawan around long-duration, low-cost liquids and the Montney gas basin. Shell said the deal should generate double-digit returns and be accretive to free cash flow per share from 2027. The company is also mid-way through a share buy-back programme it announced on July 30 and has reported on repeatedly since.

    Against $16.5 billion of enterprise value in upstream production, a $715 million power plant sale is a rounding adjustment, and that is the point. Shell is choosing molecules and trading over electrons and assets. Owning a merchant generator means accepting capacity market rules, state environmental policy and grid operator decisions you do not control. Selling the plant while keeping the gas supply and trading relationship captures much of the commercial upside with far less regulatory surface area.

    Which makes the Hunlock Creek leg the genuine open question of this transaction. A company retreating from US power generation does not normally buy a generating stake on the way out. Neither party has said whether Shell values it as a physical hedge for its gas trading book, a PJM beachhead, or simply a way to reduce the cash component of the deal.

    What It Means If You Are Buying Power, Not Selling It

    Data center developers reading this should notice what did not happen. No customer was named. No contracted capacity was disclosed. No power purchase agreement accompanied the announcement. This is a generator strengthening its position in a tight market, not a generator responding to a specific signed load.

    The practical implication for large electricity buyers is that the pool of counterparties who can offer firm, around-the-clock supply in the Northeast just got slightly more concentrated. Concentration is not automatically bad for buyers. Fewer, larger owners with nuclear and gas in the same region can structure blended products that a single-asset owner cannot. It does, however, mean less price tension in negotiations, and it raises the value of getting into a contract before the next round of consolidation prices it higher.

    Headlines in the sessions around the announcement pointed in both directions, with Constellation shares described as falling in one and both stocks higher in another. Short-run share moves say more about how a deal was expected than about whether it was wise. The substantive test is arithmetic that neither company has yet published.

    Background

    Constellation Energy was separated from utility parent Exelon in 2022 as a standalone competitive generator, taking with it the largest nuclear fleet in the United States alongside gas, hydro and renewable assets. Unlike a regulated utility, it sells power into wholesale markets rather than earning a set return on rate base, which makes its earnings a direct function of energy prices, capacity auctions and contracts with large customers. That model has drawn investor attention as artificial intelligence data centers began signing long-term deals for firm, carbon-free power.

    Shell entered North American merchant power partly through its trading arm and partly through acquisitions, but has spent recent years narrowing to what it does best at scale: finding, moving and selling hydrocarbons, with a large trading operation on top. Its completed purchase of ARC Resources, confirmed to the Securities and Exchange Commission in early September, is the clearest expression of that focus. Selling a New England generating station while adding Canadian gas production is consistent with a company that wants exposure to the fuel and to the market, without owning the machinery that burns it.

    Sources

    Source: Constellation Energy stock falls after Rhode Island acquisition announcement — coverage of the market reaction to Constellation’s agreement to acquire the Rhode Island State Energy Center from Shell for $715 million.

    Primary sources: Shell plc, Form 6-K filed September 3, 2026 — completion of the ARC Resources acquisition; Shell plc, Form 6-K filed September 1, 2026 — Transaction in Own Shares; Shell plc, Form 6-K filed September 1, 2026 — Admission to Trading of new Shell shares; AP News, September 7, 2026. Additional reporting on the transaction from Reuters, Hart Energy and Providence Business News.

  • OpenAI’s 8 GW Ohio Campus: Legacy Grid Covers 800 MW, New Power Plants Gate the Rest

    OpenAI’s 8 GW Ohio Campus: Legacy Grid Covers 800 MW, New Power Plants Gate the Rest

    TL;DR · 30-second read

    The Short Version

    • OpenAI, the maker of ChatGPT, will rent space in a huge computer campus planned on the grounds of an old Cold War uranium plant in rural southern Ohio.
    • At full size, the campus would use about as much electricity as eight large nuclear reactors produce.
    • Only about a tenth of that can come from today’s power lines, starting in 2028. The rest needs new power plants, including gas-fired ones, that have not been built yet.
    • The developer promises to pay for the grid upgrades itself, so local electric bills do not cover them.

    OpenAI announced on August 17 that it has agreed to secure approximately 8 gigawatts of IT capacity at the PORTS-Pike Technology Campus in Pike County, Ohio, working with developer SB Energy, NVIDIA and the U.S. Department of Energy. The campus is being developed on private land and on remediated federal land at the former Portsmouth Gaseous Diffusion Plant. SB Energy will build, own and operate the data center under a 20-year lease to OpenAI, and the site will exclusively host NVIDIA AI computing hardware.

    The first 800 megawatts are expected to be available in 2028, largely using existing AEP infrastructure. Later phases will require new grid-connected power plants, including natural gas generation, plus new transmission lines. NVIDIA will invest $1.5 billion in SB Energy and provide credit support for the land, power and shell buildout of the initial 4.25 gigawatts. The companies project 35,000 construction jobs over a six-year buildout through 2032 and 2,500 long-term operating jobs.

    Executive Summary

    The PORTS-Pike agreement is one of the largest single-site AI capacity commitments announced to date: roughly 8 gigawatts of power delivered to computing equipment, on a former uranium enrichment site in southern Ohio. OpenAI is the tenant, SB Energy is the developer and owner, NVIDIA is both the exclusive hardware supplier and a financial backer, and the Department of Energy is contributing federal land and an existing onsite water system.

    The more telling number is the smaller one. Only the first 800 megawatts, about a tenth of the headline figure, is expected to come online in 2028 on largely existing grid infrastructure. Everything after that depends on new power plants and new transmission lines, along with permits, environmental reviews and financing that the companies say must still be in place. In practice, this is a power-development project with a data center attached, and its pace will be set by generation and wires rather than by chips.

    The package also includes a pledge that SB Energy will pay the full cost of grid upgrades and new transmission rather than passing them to Ohio ratepayers, a closed-loop cooling design meant to limit ongoing water use, and more than $160 million in community grants and student software credits.

    Nine-Tenths of the Campus Waits on Power That Does Not Yet Exist

    The headline figure is 8 gigawatts-IT, a measure of the electricity delivered to servers and networking gear rather than the site’s total draw, which is higher once cooling and power conversion are counted. Against that, the companies say the first 800 megawatts should be available in 2028 “largely using existing AEP infrastructure,” meaning the transmission and substation capacity American Electric Power already has in the area. That is roughly 10% of the campus. The remaining 7 gigawatts or so, per OpenAI’s announcement, “will require new power plants connected to the grid, including natural gas generation, as well as new transmission lines and associated infrastructure.”

    That split is the operational core of the deal. Existing wires are the fastest path to power for any large data center, because new generation and new high-voltage lines each require siting, permitting, interconnection studies and equipment procurement before a single rack can be energised. Gas turbines, transformers and high-voltage switchgear have all been in heavy demand as utilities and data center developers compete for the same supply chains. The six-year buildout window through 2032 signals that the companies expect most of the capacity to arrive only as that new infrastructure is completed.

    The parties most exposed to this sequencing are OpenAI, whose compute roadmap depends on the later phases; SB Energy, which carries the development risk; AEP and PJM, the regional grid operator covering Ohio, which must study and integrate the new plants and lines; and NVIDIA, whose hardware sales at the site scale with each tranche of power that comes online.

    Why a Former Uranium Plant Works as a Power-First AI Site

    The Portsmouth Gaseous Diffusion Plant was built in the 1950s to enrich uranium, a process that consumed enormous amounts of electricity. That history left the area with heavy grid infrastructure, a large industrial footprint and federal land that has been under cleanup for years. For an AI campus, those legacy assets matter more than proximity to cities or fiber hubs: they are what allows the first 800 megawatts to arrive in 2028 instead of later.

    The Department of Energy’s role extends beyond land. PORTS-Pike is working with DOE to use the site’s existing onsite water system, and the data center will use closed-loop, air-cooled systems that recirculate water rather than evaporative cooling towers, which continuously consume water. OpenAI says ongoing water use, once the system is filled, should be comparable to an office building supporting a similar number of people, and well below what the enrichment plant historically used. It has committed to publish expected water use once the design is final.

    The model is replicable only where similar conditions exist: large parcels of already-disturbed land, legacy high-voltage infrastructure, and a federal owner willing to redevelop. Retired industrial and federal sites with those traits are a finite set, which is why they are becoming contested real estate for AI developers.

    Who Carries the Financial Risk

    The deal is structured to keep capital off OpenAI’s balance sheet up front. SB Energy builds and owns the facility, and OpenAI begins paying only as completed capacity becomes available for lease, funding those payments from revenue, cash flow and investor capital. That protects OpenAI from paying for capacity that is delayed, but it shifts construction and power-development risk to SB Energy and its financiers.

    NVIDIA fills part of that gap. Its $1.5 billion investment in SB Energy and its credit support, a guarantee-like backing that lowers borrowing costs, cover land, power and shell buildout for the initial 4.25 gigawatts. Because the site will exclusively host NVIDIA hardware, the chipmaker is effectively helping finance demand for its own products. That aligns incentives among the three companies, but it also concentrates exposure: the project’s financing, customer and supplier are tightly linked, and the backing described covers just over half of the 8 gigawatts.

    The Ratepayer Pledge Addresses the Biggest Local Objection

    Data center growth has become a flashpoint over whether households end up paying for grid expansion that serves large corporate loads. SB Energy’s commitment to pay the full cost of grid upgrades and new transmission lines, without shifting those costs to Ohio ratepayers, speaks directly to that concern, and the companies argue the new lines will also strengthen regional reliability.

    The community package, which includes $40 million from OpenAI on top of SB Energy’s earlier $40 million and $84 million in Codex credits for about 844,000 Ohio students, adds up to more than $160 million by OpenAI’s count. Alongside a union memorandum of understanding and annual public reporting on hiring, water and energy use, it is designed to build local consent for a project whose largest phases will require new permits and reviews over the coming years.

    Background

    The Portsmouth Gaseous Diffusion Plant near Piketon, Ohio, was built in the 1950s to enrich uranium for national defense and later for nuclear power fuel. Gaseous diffusion was extremely electricity-intensive, which left the region with substantial grid infrastructure. Enrichment ended in the early 2000s, and the Department of Energy has since overseen decontamination and cleanup, with parts of the site now available for redevelopment.

    SB Energy, a SoftBank-backed energy and infrastructure developer, is leading development of the PORTS-Pike campus. OpenAI has been expanding its computing capacity through long-term agreements with developers and hardware partners to support training of frontier AI models and growing demand for products such as ChatGPT and Codex.

    Sources

    Source: OpenAI joins PORTS-Pike project, OpenAI’s announcement of an approximately 8 gigawatt capacity agreement with SB Energy, NVIDIA and the U.S. Department of Energy in Pike County, Ohio.

  • Upper Merion’s 4.6M sq ft Denial Shows Why Self-Powered AI Campuses Still Need Town Hall

    Upper Merion’s 4.6M sq ft Denial Shows Why Self-Powered AI Campuses Still Need Town Hall

    TL;DR · 30-second read

    The Short Version

    A suburb outside Philadelphia voted down five giant buildings meant to hold the computers that run artificial intelligence. Together they would have covered roughly 80 football fields of floor space.

    The builder promised $55.4 million a year in local taxes, mostly for schools. Neighbors worried about noise, dirty air and home values, and more than 17,000 people signed a petition against it.

    The twist: to avoid raising local electric bills, the site would have made its own power with gas-burning generators. That fix became part of the fight. The builder says an appeal is coming.

    WHYY reported that Upper Merion Township’s Board of Supervisors on Thursday, August 13, 2026, rejected all five applications from developer Brian O’Neill for a hyperscale data center campus totaling more than 4.6 million square feet near King of Prussia, Pennsylvania. The campus would have been built at Discovery Labs, a health care and life sciences office property run by O’Neill’s company, and was designed to generate its own power using natural gas turbines with diesel backup generators.

    The vote followed a July planning commission recommendation against three of the five projects, a developer lawsuit seeking more review time that a Montgomery County judge cleared on the afternoon of the vote, and a resident petition with more than 17,000 signatures. O’Neill told 6ABC an appeal is planned.

    Executive Summary

    A suburban Philadelphia township has turned down one of the largest data center proposals in the region, despite the developer’s estimate of $55.4 million a year in local tax revenue, nearly $38 million of it for the local school district. The board’s stated grounds were procedural and specific: Chair Tina Garzillo said the township never received landscape, traffic impact, emergency management or sanitary sewer plans, and called the projects “at best speculative and conceptual in nature.”

    The case matters beyond Upper Merion because of how the campus was to be powered. Generating electricity on site is increasingly pitched as the responsible way to build AI-scale facilities without burdening the grid or ratepayers. Here, that design put gas turbines and diesel generators in front of a township board and its residents, and air pollution became a central objection. Self-generation did not remove the local approval gate; it added a power plant to what that gate had to judge.

    For developers, investors and utilities trying to forecast where AI capacity will actually get built, the vote is a reminder that a proposed campus is not capacity until it clears local land-use approval, and that the power strategy is now part of that approval.

    Self-Generation Swapped a Grid Question for a Local One

    The campus was pitched as a good grid neighbor: it would generate its own electricity so it would not strain the regional power system or push up household bills. That is an increasingly common design for AI-scale facilities, often called on-site or behind-the-meter power because the electricity is produced on the property rather than drawn from the utility. But in Upper Merion, the power plant came with the building. The proposal included natural gas turbines and diesel backup generators, and air pollution became one of residents’ leading objections, alongside noise and water use.

    That is the mechanism this vote exposes. A data center that buys power from the grid leaves most generation questions to utilities and grid planners. A data center that makes its own power brings combustion equipment, fuel supply and emissions controls onto a site that a township board must approve, in front of neighbors who will live beside it. O’Neill said scrubbers would control emissions and that discussions had been held with Bloom Energy about using fuel cells on site, but no deal had been finalized, which left the board and residents to evaluate the turbine-and-diesel version of the plan.

    Upper Merion is not the only place where on-site power has drawn local enforcement. In Vineland, New Jersey, where a data center under construction plans to use Bloom fuel cells, the city issued a stop-work order on parts of the 300-megawatt facility (a megawatt is a measure of electrical capacity), alleging that a liquefied natural gas tank and fuel cell units were being installed before city approval. Generating power on site may answer concerns about grid strain and electricity bills, but it adds a power plant to the list of things local officials get to review.

    The Board Ruled on Missing Plans, Not Just Public Anger

    The emotional scenes at the meeting can obscure what the board actually said. Garzillo cited the absence of landscape, traffic impact, emergency management and sanitary sewer plans. Those are ordinary engineering submissions for any large industrial project, and their absence gave the board a procedural basis for denial that stands apart from residents’ objections.

    The process had been heading this way for weeks. In July, the township planning commission voted not to recommend three of the five projects. The developer then sued, seeking an extension and arguing there had not been adequate time to address township concerns; a Montgomery County judge vacated the injunction on the afternoon of the vote, clearing the board to reject the extension. Vice chair William Jenaway said the developer had earlier opportunities to respond to review comments and did not do so in a timely fashion. The two sides’ accounts of the timeline differ, and an appeal would likely test them.

    For the industry, the lesson is about entitlement risk, meaning the risk that a site never receives the land-use approvals it needs. As AI demand pushes developers to repurpose existing properties, here a life sciences office campus, into data center sites, applications that arrive without complete plans risk being denied on the paperwork alone, whatever their scale or revenue promise.

    A $55.4 Million Tax Pitch Met a 17,000-Signature Petition

    The developer’s economic case was large on its face: an estimated $55.4 million a year in local tax revenue, with nearly $38 million going to the Upper Merion Area School District. For a suburban township, that is the kind of figure that usually carries weight. It did not carry the vote. Residents weighed it against quality-of-life costs that do not appear in a revenue projection, and one resident nearing retirement said a loss of home equity “would destroy our savings.”

    Both sides’ claims deserve the same scrutiny. The tax figure is the developer’s own estimate, and its value depends on assumptions about how much gets built and when. Residents’ fears about property values and health are sincere, but their magnitude depends on specifics that were never settled, such as how many turbines would run, how often, and with what controls. The water debate is similar: O’Neill said a closed-loop system would reuse cooling water, while hyperscale facilities in general can consume up to 5 million gallons of drinking water a day. Closed-loop designs reduce consumption substantially, but how much make-up water this campus would need was not specified.

    The backdrop is shifting against developers who lead with revenue. A University of Pennsylvania Annenberg Public Policy Center survey found a 12-point jump in widespread resistance to new data center construction over four months. In that climate, detailed answers on emissions, water and noise are likely to matter more to approval than headline tax estimates.

    What Comes Next for AI Capacity Around Philadelphia

    The denial is not necessarily final. The developer can appeal or submit new or revised plans, and has said an appeal is planned. Residents have said they will oppose any appeal or new application. O’Neill is also seeking approval for a data center in nearby Plymouth Township, which becomes the next test of whether a more complete application, and possibly a different power plan such as the fuel cells under discussion, changes the outcome.

    For operators, investors and utilities counting future AI capacity in the region, the practical point is that local land-use approval is a gate that neither scale, tax revenue nor a plan to stay off the grid can bypass. Capacity forecasts that treat proposed campuses as inevitable will miss decisions like this one, which are made parcel by parcel at township meetings.

    Background

    Upper Merion Township sits in Montgomery County, Pennsylvania, and includes much of the King of Prussia area, a major suburban commercial and office hub northwest of Philadelphia. Data centers, the buildings that house the servers behind internet services, have existed since the mid-20th century, but the rise of power-hungry artificial intelligence has pushed demand toward much larger hyperscale campuses that need substantial electricity and cooling.

    That demand has driven developers to look at existing commercial properties, such as office and life sciences campuses, as potential data center sites, and to consider generating their own power rather than waiting on the grid. It has also produced growing local resistance in the Philadelphia region and beyond, where township boards, not state or federal agencies, hold the zoning and land-use approvals that decide whether a campus can be built.

    Sources

    Source: Upper Merion board denies hyperscale data center campus near King of Prussia, WHYY’s report on the township supervisors’ vote rejecting a five-building data center campus.

  • Amazon’s 33M-Ton Gas Permit Shows AI’s Private Power Leaves No Grid Mix to Dilute Carbon

    Amazon’s 33M-Ton Gas Permit Shows AI’s Private Power Leaves No Grid Mix to Dilute Carbon

    TL;DR · 30-second read

    The Short Version

    Amazon is building its own natural gas power plant in west Texas to run a giant artificial intelligence computer center on the same site.

    Its permit allows up to 33 million tons a year of carbon dioxide, the main gas warming the planet. That is more than any other power plant in the country.

    Plugging into the public grid mixes in wind, solar and nuclear power. A private gas plant does not, so every ton traces back to one project, while Amazon still promises to cancel out its carbon pollution by 2040.

    Amazon is building a natural gas power plant in Pecos County, Texas, to supply a new AI data center on the same site, according to a New York Times report on August 8 that Tom’s Hardware covered the following day. Project permits describe a plant of up to 7.65 gigawatts (GW) running 35 gas turbines, authorized to release up to 33 million tons of carbon dioxide a year. That is more than any other power plant in the United States.

    Amazon co-founded The Climate Pledge in 2019 and committed to net-zero carbon emissions across its global operations by 2040. Amazon spokeswoman Margaret Callahan said “the world looks different now than when we co-founded the climate pledge,” but that “our commitment hasn’t changed.”

    Executive Summary

    The Pecos County project is a clear example of “behind-the-meter” generation at hyperscale. Behind-the-meter means power is produced on site for a single user instead of being drawn from the public grid. Hyperscalers are the handful of companies that run cloud platforms at global scale. At 7.65 GW, this is a utility-sized power station built to serve one data center campus.

    The scale matters, and so does the structure. A grid-connected data center’s footprint is an allocated share of a regional mix that includes gas, wind, solar and nuclear, and the operator can lower its reported figure with clean-energy contracts. A dedicated gas plant has one fuel and one customer. Every ton it emits traces to the AI campus it serves, and at the permitted ceiling those tons would make it the country’s largest single point source of power-sector CO2.

    For Amazon, the plant sits in direct tension with a public 2040 net-zero goal. The company says the goal is intact but has not described how the two will be reconciled. For the wider industry, the permit is a preview of the emissions ledger that comes with choosing speed-to-power over grid interconnection.

    No Grid Mix, No Dilution: Why Bring-Your-Own Power Changes the Carbon Math

    A data center plugged into the public grid consumes electrons from a shared pool. Its reported electricity emissions are calculated from that regional mix, and under common greenhouse-gas accounting practice a buyer can point to renewable-energy contracts to lower the figure it reports. Two things soften the number: the grid’s own blend of generation sources, and the contracts layered on top.

    A dedicated gas plant removes both. The 35 turbines permitted in Pecos County burn a single fuel for a single customer, so the permitted 33 million tons a year maps directly onto one AI campus. There is no wind farm or nuclear unit in the blend to average it down. If Amazon owns or controls the plant, standard accounting treats those tons as the company’s direct emissions, which are the hardest category to offset with purchased certificates. Even under a third-party ownership model, the link between the smokestack and the server hall is unambiguous.

    That is why the number stands out. The permit is a ceiling, and actual emissions will depend on how many turbines are built and how hard they run. At the permitted level, though, one company’s AI buildout would exceed every other power plant in the country. Everyone weighing on-site generation is affected: Amazon’s own 2040 accounting, the more than 700 members of The Climate Pledge that Amazon co-founded, and every other hyperscaler now pricing the trade-off between waiting for the grid and building its own power.

    Speed to Power Is Choosing the Fuel

    The shift to on-site generation is driven mainly by time. Connecting a large new load to the grid can take years of studies and upgrades, and communities have grown wary of data centers pushing up local electricity bills. Building power on site sidesteps both problems. Gas has become the leading choice because turbines scale quickly and fuel is available. Nuclear agreements such as Microsoft’s Three Mile Island deal and large renewable portfolios are also being pursued, but they generally take longer to deliver at gigawatt scale.

    Policy points in the same direction. The Trump administration has backed gas-fired data center projects and promoted oil, natural gas and coal over renewables, which lowers the regulatory friction for fossil-fueled generation at data center sites. Pecos County sits in the Permian Basin region, and that proximity to gas production strengthens the logistics case.

    The economics change too. By building a 7.65 GW plant, Amazon effectively becomes a major power producer, which means taking on turbine procurement, fuel supply, plant operations and fuel-price exposure that grid customers leave to utilities. Turbine manufacturers and gas suppliers gain a large anchor customer. The operator gains control over its timeline, and in exchange it owns the emissions outright.

    Testing the Claim That the Commitment Hasn’t Changed

    Amazon’s position is that its 2040 net-zero goal stands even as the landscape shifts. The claim deserves a fair test. The company’s emissions have risen each year for the past several years, a trend analysts attribute to data center construction for AI. Microsoft has made a similar case about its 2030 goal amid its own carbon-intensive expansion. Neither company has abandoned its target, and ambitious targets set in advance of a technology shift are not inherently disingenuous.

    The tension is structural, though. Gas plants are typically built to operate for decades, which would carry a facility of this size well past 2040. For a net-zero commitment to hold, something has to bridge the gap. That could be carbon capture, a later fuel switch, running the turbines far below their permitted ceiling as grid or clean supply arrives, or large-scale offsets. None of these has been described for this site. Until one is, the commitment is a statement of intent that the Pecos County permit does not yet support.

    Background

    Amazon operates more data centers than any other company worldwide and is building several new AI-focused campuses around the world. In 2019 it co-founded The Climate Pledge, committing to net-zero carbon emissions across its operations by 2040. Its emissions have nonetheless risen each year for the past several years as data center construction accelerated.

    Across the industry, hyperscalers and data center operators are increasingly building dedicated on-site power instead of waiting for grid connections, driven by long interconnection timelines and local concern over rising electricity bills. Some are pursuing nuclear and renewable deals, but natural gas has become the leading choice because it can be scaled and brought online quickly.

    Sources

    Source: Amazon’s new 7.65GW Texas AI data center power plant could become the largest source of CO₂ pollution in the US (Tom’s Hardware, August 9, 2026): coverage of permits for Amazon’s 35-turbine gas plant powering an AI data center in Pecos County, Texas.

  • Texas Tops the Nation in Proposed Gas Plants for Data Centers

    Texas Tops the Nation in Proposed Gas Plants for Data Centers

    Texas now leads the United States in proposed natural gas power plants intended to serve data centers, according to reporting by the Texas Tribune published July 2, 2026. The report notes that the proposed plants would emit large amounts of greenhouse gases if built.

    The finding places Texas at the center of a national trend: as AI-driven data center demand outpaces what existing grids can deliver, developers are increasingly proposing dedicated, on-site or co-located gas generation rather than waiting in utility interconnection queues.

    Executive Summary

    The Texas Tribune’s July 2026 reporting identifies Texas as the top state for proposed power plants tied to data centers — and specifically flags the greenhouse gas consequences of that pipeline. The headline fact is simple but significant: the AI infrastructure boom is no longer just a real estate and chip story; it is a power generation story, and Texas is where the most new fossil-fueled capacity is being proposed to feed it.

    Why it matters: data centers historically plugged into the existing grid and bought power like any other large customer. The scale of AI campuses — often requiring hundreds of megawatts each, comparable to a small city — has flipped that model. Developers are now proposing their own gas plants, or pairing with generation developers, to guarantee power on their construction timelines. That accelerates buildout but shifts emissions, siting, and reliability questions onto communities and regulators who are still catching up.

    For the infrastructure industry, the report is a signal of where the market has moved: speed-to-power is the binding constraint on AI capacity, and Texas — with its independent grid, comparatively fast permitting, and abundant natural gas — has become the path of least resistance.

    Why Texas Became the Epicenter of the Gas-for-AI Buildout

    Texas offers a combination no other state matches: an independent grid operated by ERCOT (the Electric Reliability Council of Texas, which runs the grid for most of the state outside federal interconnection oversight), a deregulated energy-only power market, in-state natural gas supply from the Permian Basin, and a permitting culture that moves faster than most coastal states. For a data center developer whose customers are demanding capacity in 18–24 months rather than the five-plus years a utility interconnection can take, those attributes translate directly into revenue.

    The result the Tribune documents — Texas leading the nation in proposed data-center power plants — is the logical endpoint of that competition. When the grid cannot deliver power fast enough, developers bring their own. Natural gas turbines are the default choice because they are dispatchable (they run whenever needed, unlike weather-dependent wind and solar) and can be ordered, sited, and built faster than nuclear, though turbine order backlogs have become their own bottleneck industry-wide.

    The Emissions Trade-Off Behind the AI Boom

    The Tribune’s framing highlights the tension the industry has been navigating for two years: the same hyperscale companies that made aggressive carbon-neutrality pledges are now, directly or through partners, driving a wave of new fossil-fueled generation. Gas plants emit roughly half the carbon dioxide of coal per unit of electricity, but a large fleet of new gas capacity running at high utilization to serve round-the-clock compute loads still represents a substantial, long-lived emissions commitment — these plants typically operate for 30 years or more.

    This does not mean the criticism writes itself in only one direction. Proponents argue that new, efficient gas capacity can displace older, dirtier generation, firm up a grid that is adding record amounts of solar and storage, and that some proposed plants may be bridge solutions later paired with carbon capture or displaced by nuclear. Those arguments deserve scrutiny too: bridge claims are only as good as the retirement and conversion commitments behind them, and the release-level reporting here does not indicate such commitments exist for the Texas pipeline.

    What a Proposal Pipeline Does — and Does Not — Tell Us

    A crucial caveat for readers: “proposed” is doing heavy lifting in this story. Power plant proposal pipelines everywhere are inflated by speculative filings — developers reserve interconnection positions, file air permits, and announce projects to attract customers and capital, and a meaningful fraction never get built. The same phenomenon inflates data center announcement figures. Texas leading in proposals confirms where developer intent is concentrated; it does not tell us how many megawatts will actually enter service, or when.

    That said, the direction is unambiguous. Even a partial realization of the Texas pipeline would reshape the state’s power market — affecting gas demand, electricity prices for other consumers, water use for cooling, and ERCOT’s planning assumptions. Texas legislators have already responded to large-load growth with new interconnection and curtailment rules for big electricity users, a sign that regulators expect the trend to persist.

    Winners, Losers, and the Competitive Map

    The near-term winners are clear: gas turbine manufacturers with multi-year order books, midstream companies moving Permian gas, engineering and construction firms, and landowners in transmission-adjacent counties. Data center operators who secure firm power early gain a genuine moat, because speed-to-power — not land or capital — is currently the scarcest input in AI infrastructure.

    The open question is who bears the costs. Residential and industrial ratepayers may face higher prices if large loads strain the system faster than supply arrives; communities near proposed plants absorb local air-quality and water impacts; and operators themselves carry stranded-asset risk if AI demand forecasts prove overbuilt or if more efficient chips and models bend the power curve downward. Competing states — Virginia, Georgia, Ohio, Arizona — are watching whether Texas’s speed advantage outweighs its grid-reliability reputation, still shadowed by the 2021 winter storm failures.

    Background

    Texas has spent two decades building a reputation as the country’s most market-driven electricity system: ERCOT runs an energy-only market with no capacity payments, the state leads the nation in wind generation and has surged in utility-scale solar and batteries, and its independence from federal grid oversight speeds interconnection. That same system drew scrutiny after the February 2021 winter storm, when generation failures caused days-long blackouts — a backdrop that still colors every debate about adding large new loads.

    The AI boom collided with this landscape beginning in 2023–2024, when hyperscale cloud and AI companies began announcing data center campuses at unprecedented scale and grid operators nationwide sharply raised their demand forecasts. With interconnection queues stretching years, developers turned to dedicated gas generation, and Texas — with in-state gas supply and fast permitting — emerged as the natural home for that model. The Texas Tribune’s July 2026 reporting quantifies where that trend has led: more proposed data-center power plants than any other state.

    Source: Texas leads nation in proposed power plants for data centers, which would emit large amounts of greenhouse gases — Texas Tribune reporting, July 2, 2026, on the gas-fired generation pipeline behind the state’s data center boom.

  • Chevron Eyes More Deals to Power US Data Centers, Reuters Reports

    Chevron Eyes More Deals to Power US Data Centers, Reuters Reports

    Reuters reported on June 27, 2026 that Chevron, the second-largest US oil and gas producer, is looking at more deals to supply electricity to American data centers. The report signals that Chevron intends to expand beyond its previously announced data-center power venture and treat AI-driven electricity demand as an ongoing line of business rather than a one-off experiment.

    Executive Summary

    According to the Reuters report, Chevron is actively seeking additional opportunities to power US data centers. The company had already staked out a position in this market: in early 2025 it unveiled a venture with investment firm Engine No. 1 and turbine maker GE Vernova to build natural-gas power plants co-located with data centers — so-called behind-the-meter generation that serves a facility directly rather than routing through the public grid — with a stated ambition of up to four gigawatts of capacity. A statement of appetite for “more deals” suggests that pipeline is progressing well enough for Chevron to widen it.

    Why it matters: the binding constraint on AI infrastructure has shifted from chips to electricity. Utility interconnection queues in major US markets now stretch years, and hyperscalers and data-center developers are increasingly willing to contract directly with anyone who can deliver firm power on a faster clock. An integrated oil major brings its own fuel supply, engineering capability, and balance sheet to that problem — a combination few pure-play power developers can match.

    From Barrels to Electrons: Why Oil Majors Want AI Load

    Oil and gas companies have spent the past decade searching for growth businesses that fit their existing skills. Data-center power is unusually well matched: it monetizes natural gas — which Chevron produces in large volumes, particularly in the Permian Basin — through long-term contracts with creditworthy technology counterparties, and it uses project-development muscle the industry already has. Unlike many diversification bets, it does not require the company to learn an unfamiliar trade; it moves gas one step further down the value chain, from selling the fuel to selling the electricity made from it.

    For Chevron, the strategic appeal is margin and duration. Spot gas prices are volatile, but a multi-year power contract with a data-center operator converts that volatility into something closer to an annuity. If AI demand projections hold, an oil major that locks in supply relationships now is positioning itself in one of the few large, growing markets for hydrocarbons in the developed world.

    Behind-the-Meter Power: The Speed Play

    The core product here is speed. Connecting a large new load to the grid in many US regions means joining an interconnection queue and waiting — often three to five years or more — while studies and upgrades grind forward. Behind-the-meter generation sidesteps much of that by building the power plant at the data-center site, dedicated to that customer. For an AI developer racing to energize capacity, shaving years off time-to-power can be worth paying a premium.

    The trade-offs are real, though. On-site gas generation ties the facility’s economics to fuel prices and turbine availability, and gas turbines are themselves in short supply, with manufacturers reporting multi-year order backlogs. It also raises questions for local communities and regulators about emissions, water, and whether large loads that bypass the grid still contribute fairly to shared infrastructure costs. None of these is disqualifying, but each is a live negotiation in every deal of this kind.

    The Competitive Field Is Crowding Fast

    Chevron is not alone in this pivot. Rival Exxon Mobil has discussed plans for gas-fired plants with carbon capture aimed at data centers, and a broad set of players — independent power producers, private-equity-backed developers, nuclear operators, and the utilities themselves — are all courting the same hyperscale customers. The winners will likely be those who can credibly promise firm megawatts on the shortest timeline, which favors companies with secured turbine slots, owned fuel supply, and sites already in hand.

    For data-center operators and their tenants, more competition among power suppliers is straightforwardly good news: more options, more negotiating leverage, and a wider menu of structures from full behind-the-meter islands to hybrid grid-plus-onsite designs. For utilities, it is more ambiguous — every gigawatt served behind the meter is load growth they do not capture, at a moment when load growth had finally returned to their business case.

    Background

    Chevron is one of the world’s largest integrated energy companies and the second-largest US oil and gas producer, with major positions in the Permian Basin of Texas and New Mexico. Like other oil majors, it has been searching for growth avenues as transportation-fuel demand matures; powering data centers emerged as a candidate in early 2025, when Chevron announced a venture with Engine No. 1 and GE Vernova to build gas-fired plants co-located with computing facilities.

    The backdrop is a step-change in US electricity demand. After roughly two decades of flat consumption, AI training and cloud computing have driven forecasts of sustained load growth, while grid interconnection queues and equipment shortages slow conventional responses. That gap between demand and deliverable supply is the market opening that Chevron — and a growing list of competitors — is moving to fill.

    Source: Chevron eyes more deals to power US data centers — Reuters, a June 27, 2026 report on the oil major’s plans to expand its role in supplying electricity to American data centers.

  • Behind-the-Meter Gas Plants for Data Centers May Raise US Energy Bills

    Behind-the-Meter Gas Plants for Data Centers May Raise US Energy Bills

    Utility Dive reported on June 7, 2026 that behind-the-meter gas plants — power generation built on a data center’s own site, outside the utility’s meter — will raise US energy bills. The finding lands as AI data center developers increasingly turn to on-site gas turbines to sidestep multi-year grid interconnection queues, raising the question of who ultimately pays for the workaround.

    Executive Summary

    The report’s headline claim is direct: the wave of behind-the-meter (BTM) gas generation being planned for US data centers will not insulate ordinary consumers from AI’s power demand — it will add to their bills. “Behind the meter” means the plant serves the facility directly, bypassing the utility grid for most or all of its supply, and often bypassing the retail rates, transmission charges, and regulatory review that grid-served customers face.

    Why it matters: BTM gas has been marketed as the pressure-release valve for the AI boom — a way for hyperscalers to get hundreds of megawatts energized in two or three years instead of waiting five or more for grid interconnection, without burdening other customers. If independent analysis concludes the opposite — that these plants raise systemwide costs anyway — it undercuts a central argument utilities, developers, and some policymakers have used to wave the projects through, and it strengthens the hand of regulators pushing for special large-load tariffs and cost-allocation rules.

    Why Data Centers Are Building Their Own Power Plants

    The context for this report is the collision between AI-driven load growth and a grid that cannot connect large customers quickly. Interconnection queues in major US markets stretch years, and transmission upgrades longer still. For a hyperscaler racing to deploy GPUs, a gas turbine on-site — behind the meter — converts an electricity problem into a procurement problem: buy the turbine, permit the plant, burn the fuel, skip the queue. That speed premium is why BTM gas has moved from a niche arrangement to a defining feature of the current data center buildout.

    The pitch to regulators has been that this is self-contained: the data center pays for its own generation, so other ratepayers are held harmless. The Utility Dive report’s conclusion — that these plants will raise US energy bills — challenges that framing at its core.

    How a Private Power Plant Can Raise Everyone Else’s Bill

    With only the headline finding available, the report’s specific modeling cannot be evaluated here, but the mechanisms by which BTM generation can raise systemwide costs are well understood in utility economics. First, natural gas markets are shared: a fleet of new gas plants competing for fuel, pipeline capacity, and turbines can push up gas prices, and because gas units set the marginal price of electricity in much of the country, higher gas costs flow into wholesale power prices for everyone. Second, BTM facilities typically still rely on the grid for backup and startup power while contributing little to the fixed costs of the wires — costs that get spread across remaining customers. Third, if BTM load later converts to grid service, the system must absorb a large customer it never planned for.

    Each of these is a cost-shifting channel, not a conspiracy: individually rational decisions by data center developers can still produce a collectively expensive outcome. That is precisely the kind of externality utility regulation exists to police.

    Winners, Losers, and the Regulatory Stakes

    The near-term winners of the BTM boom are clear regardless of the report’s conclusion: gas turbine manufacturers with multi-year order books, gas producers and pipeline owners, and developers who can monetize speed-to-power. The contested question is who bears the residual cost. If the report’s finding holds, the losers include residential and small-business ratepayers — and, notably, utilities’ own political capital, since public backlash over rising bills tends to land on the regulated utility whether or not it caused the increase.

    For the data center industry, the strategic risk is regulatory: findings like this one give state commissions ammunition to impose standby charges, minimum-take tariffs, exit fees, or cost-allocation rules on large loads. Several states were already moving in that direction before this report. Operators that get ahead of the issue — structuring deals that demonstrably cover their grid costs — will face less friction than those that treat BTM as a permanent regulatory bypass.

    Background

    The US data center industry entered a period of unprecedented power demand growth in the mid-2020s, driven by AI training and inference workloads. After two decades of roughly flat US electricity consumption, utilities began forecasting sustained load growth, with data centers the largest single driver. Grid interconnection processes designed for a slower era became the bottleneck, and “speed to power” replaced land and fiber as the industry’s scarcest resource.

    Behind-the-meter generation — long a niche arrangement for industrial plants with steam needs or reliability concerns — was repurposed as the fast lane: developers began pairing data center campuses with dedicated on-site gas turbines, sometimes at gigawatt scale. Utility Dive, a trade publication covering the US electric power sector, has tracked the resulting policy fight over who pays for AI’s power appetite; this report is part of that running debate.

    Source: Behind-the-meter data center gas plants will raise US energy bills — Utility Dive, a June 7, 2026 report on the ratepayer costs of on-site gas generation built for US data centers.