POWER Magazine reports that hyperscale and AI-focused data center developers are increasingly deploying on-site generation as prime power — the primary source of electricity — rather than as backup for grid supply. The shift is being driven by multi-year interconnection queues and gigawatt-scale load requests that utilities cannot serve on operators’ timelines.
The article frames the trend as a structural change in how large computing loads are powered, not a temporary workaround while the grid catches up.
Executive Summary
For decades, data center diesel generators sat idle 99% of the year, insurance against a utility outage. POWER Magazine’s May 2026 piece argues that AI-era facilities are inverting that model: on-site turbines, engines, and increasingly fuel cells are being sized to carry the base load, with the grid demoted to a secondary or supplementary role.
The change matters because it decouples data center build timelines from utility interconnection queues that now stretch five years or more in several U.S. markets. It also shifts who bears the cost of new generation, who chooses the fuel, and who is accountable for the emissions — moving decisions from regulated utility planning processes into private commercial ones.
The article does not quantify how much AI capacity is being built this way, but treats the pattern as established enough across the industry to describe as a category shift rather than a set of one-off projects.
Why the Grid Became the Bottleneck
A modern AI training campus can request 500 megawatts to more than a gigawatt at a single site — roughly the draw of a mid-sized city. U.S. transmission planning, permitting, and equipment lead times were not built for loads of that size arriving in 18-month cycles. Large transformers alone now carry multi-year backlogs. Faced with utility responses measured in years, developers with hyperscaler contracts and finite construction windows are choosing to generate power themselves.
On-site prime power is not new — industrial sites, hospitals, and remote operations have done it for a century. What is new is the scale at which general-purpose computing infrastructure is adopting it, and the willingness of tenants to accept a self-generated power product rather than wait for a utility one.
The Fuel Question Nobody Wants to Answer Cleanly
Prime power at data center scale currently means natural gas turbines or reciprocating engines in most cases, with fuel cells and, in a few announced projects, small modular reactors positioned as future options. Each choice carries trade-offs the industry rarely discusses in the same sentence: gas is fast and financeable but carbon-intensive; fuel cells are cleaner per kilowatt-hour but expensive and supply-constrained; nuclear is low-carbon but years from commercial deployment at the sizes being discussed.
Operators marketing 24/7 clean energy commitments and operators building gas-fired prime power are, in some cases, the same companies. That is not necessarily hypocrisy — sustainability commitments typically cover corporate portfolios, not individual sites — but it does mean buyers and communities should read specific project disclosures carefully rather than relying on parent-company pledges.
Winners, Losers, and Who Pays for the Grid
The winners are gas turbine manufacturers, EPC contractors with power-plant experience, and developers who can site, permit, and finance generation alongside compute. Utilities lose a category of load they had expected to plan around; regulators lose visibility into where large new emissions sources are appearing; and ratepayers face a more complex question about who pays for grid upgrades if the largest new users bypass the system.
There is also a quieter loser: the narrative that AI growth would automatically pull the grid toward cleaner, more flexible operation. If the largest loads leave the grid entirely, the reverse dynamic can take hold — utilities lose the anchor customers that would have justified transmission and clean generation investment.
A Structural Shift, Not a Stopgap
The POWER Magazine framing — from backup to prime — is the important claim. If on-site generation were a bridge until interconnections cleared, the industry would treat it as temporary infrastructure. Instead, projects are being permitted, financed, and contracted on 15- to 25-year horizons, which is how long the equipment is expected to run. That is a bet that grid-served gigawatt loads will remain hard to obtain for the foreseeable future.
Whether that bet is correct depends on transmission reform, interconnection queue processing, and whether utilities can stand up large-load tariffs quickly enough to compete. None of those variables are moving at AI-buildout speed today.
Background
Data centers have historically been utility customers first and self-generators only as a fallback. Diesel backup generators, sized to carry the site through a grid outage, were standard equipment but ran only during tests and emergencies. The economics favored buying grid power because it was cheaper, cleaner in most regions, and available on request.
The AI buildout beginning in 2023 broke that model. Single-site power requests jumped from tens of megawatts to hundreds and then to gigawatts, colliding with a U.S. transmission system that had not added significant new capacity in a decade. On-site prime power emerged as the industry’s answer — controversial on emissions grounds, but faster than waiting for the grid.
IEEE Spectrum reported on May 13, 2026 on an emerging infrastructure concept: placing small, modular data centers directly at electric-grid substations as a way to keep surging AI power usage in check. Rather than concentrating hundreds of megawatts of computing at a single campus and forcing utilities to build new transmission to serve it, the approach distributes compute in small increments at points where the grid already has capacity, interconnection equipment, and land.
Executive Summary
The idea IEEE Spectrum describes inverts the dominant pattern of the AI buildout. Instead of asking the grid to come to the data center — often a multi-year, multi-billion-dollar transmission and generation exercise — micro data centers go to the grid, occupying the underused margins of existing substations. A substation is the node where high-voltage transmission is stepped down for local distribution; many have spare transformer capacity for part of the day or year, plus fenced land and existing utility interconnection.
Why it matters: interconnection queues and transmission constraints, not chips, have become the binding constraint on AI capacity growth in many U.S. markets. Any credible mechanism that adds compute without triggering new large-load interconnection studies deserves attention from utilities, hyperscalers, and colocation operators alike. The open question — which the source coverage frames but cannot yet settle — is whether compute measured in hundreds of kilowatts to a few megawatts per site can meaningfully offset demand measured in gigawatts.
Why the Substation Is Suddenly Prime Real Estate
The scarce resource in the AI era is not land or servers — it is grid interconnection. Large data center campuses in major markets face waits that can stretch for years while utilities study whether the transmission system can absorb a new load of 100 MW or more. A substation-sited micro facility sidesteps much of that: the interconnection already exists, the utility already owns and monitors the site, and the incremental load can be sized to fit whatever headroom the local transformer bank actually has.
There is also a load-shaping logic. Substation loading varies by hour and season; a data center that can throttle or shift its work — as some AI training and batch-inference workloads can — could soak up capacity when the neighborhood demand is low and back off at peak. In that framing, the micro data center is less a tenant than a grid instrument: a flexible load that improves utilization of assets ratepayers have already paid for.
The Economics Cut Both Ways
Distributing compute forfeits the economies of scale that made the hyperscale model dominant. A 200 MW campus amortizes security, staffing, cooling plant, and network backbone across a vast footprint; a 1 MW pod at a substation must be nearly autonomous — remotely operated, prefabricated, and cheap to service — or its cost per kilowatt will not compete. The viability of the model rests heavily on modular manufacturing driving unit costs down, something the industry has promised for a decade with mixed results.
On the revenue side, however, distributed sites have an asset central campuses lack: proximity. Inference — the serving of trained AI models to users — benefits from being near population centers, and substations are by definition embedded where people and businesses are. If AI demand shifts from training-dominated to inference-dominated, as most industry roadmaps assume, the value of many small, close-in sites rises relative to a few remote giants.
Utilities as Gatekeepers — and Potential Partners
Nothing in this model works without the utility, which controls the substation, the interconnection, and the tariff. That is both the model’s strength and its fragility. Utilities gain a new class of revenue-generating, potentially flexible load and a better story for regulators worried about data centers driving up residential rates. But utilities are conservative by design and by regulation: hosting third-party commercial equipment inside the substation fence raises questions of liability, security, union work rules, and whether ratepayer-funded assets can be leveraged for private gain.
Expect the regulatory treatment to vary sharply by state and by whether the market is vertically integrated or restructured. Pilots with a single cooperative or municipal utility are one thing; scaling across investor-owned utilities under public-utility-commission oversight is a much longer road, and the source coverage does not indicate that road has been mapped.
A Complement, Not a Substitute
It is worth being precise about scale. AI’s incremental power demand is commonly discussed in gigawatts per year in the U.S. alone; substation-sited pods of a megawatt or less would need to be deployed by the thousands to absorb even a modest share. That does not make the idea a gimmick — grid-edge flexibility has outsized value precisely at the margins where systems break — but it does mean micro data centers are best understood as a pressure valve, as the framing suggests, rather than a replacement for large campuses, new generation, and transmission expansion. The realistic outcome is a layered market: hyperscale for training, regional colocation for enterprise, and grid-embedded micro sites for latency-sensitive inference and load balancing.
Background
The idea of the micro or edge data center predates the AI boom — telecoms and content networks have long placed small compute nodes near users — but it struggled commercially because most cloud workloads tolerated centralization. Two forces revived it: the AI buildout’s collision with grid interconnection queues, and the rise of latency-sensitive inference. By 2026, utilities, regulators, and hyperscalers were all publicly wrestling with how to add gigawatts of data center load without destabilizing rates or reliability, making grid-aware siting concepts — flexible loads, curtailable contracts, and now substation-sited compute — a mainstream topic of industry discussion rather than a fringe experiment.
PPL Corporation’s pipeline of “advanced-stage” data center projects seeking to connect in its Pennsylvania service territory has grown to 28.3 gigawatts, according to a May 10, 2026 report by Utility Dive. The figure refers to prospective load — data centers that have progressed beyond casual inquiry into serious interconnection planning with the utility — not capacity that is contracted, under construction, or energized.
For scale, 28.3 GW of potential new demand concentrated in one utility’s footprint is several times the historical peak load of PPL’s Pennsylvania system, making it one of the clearest single data points yet on how large the AI-driven interconnection wave has become.
Executive Summary
Utilities increasingly disclose their data center “pipelines” — the aggregate megawatts of projects in active interconnection discussions — as a forward indicator of load growth. PPL’s disclosure that its advanced pipeline has reached 28.3 GW in Pennsylvania matters for three reasons. First, it quantifies demand pressure in PJM Interconnection, the 13-state grid region that already faces tightening capacity margins. Second, it signals that Pennsylvania, with its proximity to fiber routes, available land, and in-state generation, has become a first-tier data center market rather than a spillover from Northern Virginia. Third, it frames the central planning question of this cycle: how much of a paper pipeline converts into steel, concrete, and actual megawatt-hours.
The distinction between pipeline and reality is the heart of the story. Developers routinely file interconnection requests at multiple utilities for the same project, and “advanced” is a utility-defined category, not a standardized industry term. Even so, the direction and magnitude of the number — and the fact that it keeps growing — tells investors, regulators, and infrastructure buyers that the interconnection queue, not chips or capital, is now the binding constraint on data center growth.
What “Advanced” Actually Means — and Why the Definition Matters
When a utility labels pipeline projects “advanced,” it generally means the developer has moved past an initial inquiry: engineering studies are underway, agreements may be in negotiation, and sites are typically identified. That is meaningfully stronger than the raw interconnection queue, which is notorious for speculative and duplicative requests. But it still is not a commitment. No standardized definition governs the term across utilities, so a project counted as advanced at PPL could simultaneously appear in another utility’s pipeline while the developer shops for the fastest path to power.
The practical consequence is that 28.3 GW should be read as a demand signal, not a construction forecast. Utilities themselves typically plan around a conversion rate — an internal estimate of what fraction of the pipeline materializes — though the report at hand does not disclose PPL’s assumption. The honest framing is that even a modest conversion of a pipeline this size would represent transformative load growth for a single service territory.
Pennsylvania’s Emergence as a Load-Growth Epicenter
For two decades, U.S. data center demand concentrated in Northern Virginia. As land, power, and community tolerance tightened there, developers fanned out along the PJM footprint, and central and eastern Pennsylvania — PPL’s territory — offered a compelling combination: transmission access, proximity to East Coast network routes, comparatively available land, and significant in-state generation including nuclear and gas. A 28.3 GW advanced pipeline suggests that migration is no longer incremental; Pennsylvania is being treated as a primary market.
That creates a genuine economic opportunity for the state — construction activity, tax base, and potential anchor tenants for new generation — alongside a genuine planning burden. Interconnecting even a fraction of this load requires new transmission, substations, and ultimately generation, all of which run on multi-year timelines that sit awkwardly against data center developers’ desired 24- to 36-month schedules.
The Ratepayer Question Hanging Over Every Gigawatt
The unresolved policy issue beneath these numbers is cost allocation: who pays for the grid upgrades that hyperscale load requires, and who bears the risk if forecast load never shows up. PJM’s recent capacity market results have already drawn scrutiny over rising costs attributed partly to data center demand, and utilities across the region have been developing large-load tariffs — contract structures requiring minimum payments, collateral, or long-term commitments from data center customers — precisely to shield residential ratepayers from stranded-asset risk.
A pipeline of 28.3 GW sharpens that debate rather than settling it. If utilities build for demand that fails to materialize, ordinary customers can be left carrying the cost; if they under-build, they forfeit economic development and constrain a strategically important industry. The quality of the screening — how rigorously “advanced” projects are vetted for financial commitment — is therefore not a technicality. It is the mechanism that determines whether this boom is financed by its beneficiaries.
Winners, Losers, and the New Scarcity
The clearest winners from a demand signal of this size are owners of existing generation in PJM, transmission developers, and the electrical-equipment supply chain — transformers, switchgear, and high-voltage gear already carry long lead times, and this level of demand extends them. Data center operators with interconnection positions already secured hold assets that appreciate as the queue lengthens. The squeezed parties are late-arriving developers facing multi-year waits, industrial customers competing for the same grid headroom, and any market participant that underestimated how quickly regional capacity margins would tighten.
For enterprise buyers of data center capacity, the takeaway is concrete: power availability, not real estate, now drives site selection and delivery dates. Contracted, deliverable megawatts in PJM have become the scarce commodity, and pipelines like PPL’s explain why.
Background
PPL Corporation, headquartered in Allentown, Pennsylvania, delivers electricity through PPL Electric Utilities to roughly 1.5 million customers in central and eastern Pennsylvania, a territory inside PJM Interconnection — the regional transmission organization spanning 13 states and Washington, D.C. For most of the past two decades, U.S. utilities planned around flat or declining load; efficiency gains offset economic growth, and grid investment focused on reliability rather than expansion.
The AI buildout that accelerated from 2023 onward broke that pattern. Hyperscale and AI-specialist developers began requesting grid connections measured in hundreds of megawatts per campus, overwhelming interconnection processes designed for a slower era. Utilities across PJM — where Northern Virginia’s data center concentration already strained the system — started publishing pipeline figures to communicate the scale of prospective demand to investors and regulators, and those figures have grown with nearly every disclosure. PPL’s 28.3 GW advanced pipeline is among the largest single-utility totals reported to date.
Data Center Knowledge reported on 9 May 2026 that a Texas data center has stopped waiting for a grid connection and will instead be served by generation sited behind the meter — industry shorthand for power that reaches the load without passing through the utility’s revenue meter, typically from plant on or adjacent to the customer’s own property. The stated trigger is delay in the interconnection queue: the study-and-approval process through which a large new load or generator is modelled, cleared and physically tied into the transmission network.
The report as circulated to us is headline-level. It does not name the operator, the site, the megawatt capacity, the generating technology, the counterparties or the energisation date, so the size of the commitment cannot be established from this source alone.
Executive Summary
The substantiated claim is narrow but consequential: at least one Texas data center project has concluded that private generation is a faster route to electrons than the queue for public grid capacity. That is a decision about time, not ideology. A shell with tenants and no power earns nothing, and self-supply converts a regulatory wait into a construction schedule the operator controls.
It matters because it inverts a fifty-year assumption in this industry. Data centers were historically sited where large, reliable, cheap grid power already existed; the operator’s job was to buy it well. When queue times stretch past the useful life of an AI hardware generation, the operator’s job becomes building a power plant as a precondition of building a data center — a different balance sheet, a different risk register and a different set of counterparties.
Read with appropriate caution. A single trade report of a single project establishes a direction of travel, not its magnitude. What follows treats the behind-the-meter decision as reported and examines the economics and risks that any such decision entails, while marking clearly where the source is silent.
What Behind the Meter Actually Buys — and What It Costs
Grid power is, in ordinary conditions, the cheapest and least troublesome electricity a data center can buy. Someone else finances the plant, maintains it, holds the fuel contracts, carries the outage risk and spreads the cost across many customers. Going behind the meter means taking all of that onto your own books: capital for generating equipment, firm fuel supply, air permits, spare parts, operators on shift, and redundancy engineered to the availability level your tenants’ contracts require.
What the operator gets in exchange is a schedule. Interconnection is an administrative queue in which the customer’s position is set by process, not by willingness to pay; on-site generation is a procurement and construction problem, and construction problems respond to money. The arithmetic that makes the swap rational is straightforward: if a leased or pre-let facility is earning nothing while it waits, the carrying cost of idle capital plus foregone revenue can exceed the premium on self-generated power for a long time. That premium is real, and it recurs every year the plant runs.
The corollary is that this decision is much easier with contracted demand behind it. Speculative capacity rarely justifies a private power plant. Where an operator has firm hyperscale or AI tenancy, the revenue is certain enough to underwrite generation assets; where it does not, behind-the-meter economics look considerably thinner. The report does not tell us which situation applies here, and that distinction changes how much the case should be generalised.
The Queue Became the Scarce Asset
For most of the past decade the constraints on data center siting were land, fibre routes, water, tax treatment and labour. Power was a line item. The last few years have promoted grid access to the binding constraint almost everywhere large campuses are proposed, and the practical effect is that a credible, near-dated path to megawatts is now the asset being competed for — more than the acreage it sits on.
That reordering creates identifiable winners. Suppliers of on-site generating equipment and the engineering firms that install it gain pricing power, because their delivery slots are what a stranded project is actually buying. Landowners with gas pipeline adjacency, existing industrial permits or brownfield interconnects become disproportionately valuable. Developers who can present a financed, permitted power solution can charge for certainty in a market where certainty is scarce.
The losers are less visible. Developers whose principal advantage was an early queue position lose that advantage when rivals stop queuing. Utilities forgo the load growth that would have supported their own investment cases, and lose the revenue base across which fixed network costs are spread. System planners face a harder forecasting problem when significant demand exists but does not appear as grid load. None of these effects is catastrophic at the scale of one project; all of them compound if the pattern holds.
Texas Rules, Texas Risks
Texas is a plausible place for this to surface first. ERCOT, the grid operator covering most of the state, runs an energy-only market and sits largely apart from the two big interconnections that cover the rest of the country, which has historically made it quick to build in and attractive to load. Rapid demand growth has strained that reputation, and Texas has abundant gas infrastructure and a permitting culture that makes private generation a more available answer than it would be in many jurisdictions.
It also lands in an unresolved policy argument that deserves scrutiny in both directions. Consumer advocates argue that very large loads which self-supply but retain grid ties for backup or standby service should still contribute to the network costs they rely on; operators argue that adding generation alongside new demand relieves rather than burdens the system. Both positions are testable and neither should be accepted on assertion: the fair questions are what the load’s actual grid interaction looks like under stress, whether the on-site plant is dispatchable to the system or purely captive, and what the standby tariff genuinely recovers. Nothing in this report answers those questions for this project.
The risk ledger is equally concrete. Generating equipment has its own multi-year lead times, so the swap is not automatically fast. Firm fuel transport must be contracted, and fuel price exposure moves onto the operator. Air permitting can consume the schedule the queue exit was meant to save. And behind-the-meter is often a bridge rather than a destination — many operators intend to connect eventually and run private generation as an interim or hybrid arrangement. Whether that is the plan here is precisely the sort of thing the available reporting does not say.
Background
Data centers were traditionally sited where large, reliable grid power already existed, alongside fibre routes, water and favourable tax treatment. The rise of AI training and inference workloads has pushed campus power requirements to a scale that many transmission systems cannot absorb quickly, and the interconnection queue — the sequential study process that clears new loads and generators for connection — has become the binding constraint on when a facility can open rather than a routine administrative step.
Texas is a focal point for that pressure. Most of the state is served by ERCOT, an energy-only market operating largely independently of the wider US interconnections, which long gave it a reputation for speed and low cost and attracted heavy data center investment. As demand growth has outpaced network build-out, operators there have increasingly explored on-site generation, co-location with power plants and other private-supply arrangements. Data Center Knowledge, which reported this case, is a long-established trade publication covering the sector.
The Trump administration is advancing measures to bar foreign technology considered a national-security risk from the US bulk-power system, according to a Nextgov/FCW report dated May 8, 2026. The move revives and extends earlier executive efforts to police the origins of transformers, inverters, control systems and other grid-connected equipment.
Executive Summary
Washington is again training its regulatory attention on the electric grid’s supply chain. The reported action would restrict the use of equipment from designated foreign adversaries in US power infrastructure, echoing a 2020 executive order that was paused and then partially unwound before returning to the policy agenda.
For data-center operators, the stakes are practical rather than abstract. High-voltage transformers, medium-voltage switchgear, battery inverters and grid-tied controls increasingly determine whether new capacity comes online on schedule. Any rule that narrows the pool of eligible suppliers reshapes procurement, lead times and cost curves for hyperscale and colocation builds alike.
What ‘Risky Foreign Technology’ Actually Means
The phrase is broad by design. In earlier iterations, US officials focused on bulk-power equipment sourced from countries designated as foreign adversaries, with particular concern about large power transformers and digital control systems that could be remotely accessed or tampered with. The underlying worry is that embedded firmware, software updates or hardware backdoors in critical grid equipment could be exploited during a conflict or crisis.
For a lay reader, the concern is less about a single dramatic hack than about slow, quiet dependence. If a handful of foreign vendors supply components that sit inside substations for thirty or forty years, replacing them later is expensive and disruptive. Regulators appear to be trying to prevent that lock-in from deepening while alternatives still exist.
Direct Line to Data-Center Power
Data centers do not run on abstractions; they run on transformers, switchgear and increasingly on-site generation. The industry is already contending with multi-year lead times for large transformers and constrained global manufacturing capacity. A rule that narrows sourcing options, even at the margin, tightens an already tight market and raises the premium on domestic and allied-country supply.
Operators building AI-scale campuses should expect procurement teams to be asked new questions: Where was this transformer wound? Whose firmware runs the relay? Is the inverter vendor on a restricted list? Compliance overhead is real, but the bigger operational risk is discovering late in a project that a specified component is no longer eligible.
Winners, Losers and Second-Order Effects
Domestic manufacturers of transformers, switchgear and inverters stand to benefit if the policy sticks and is enforced consistently. Allied suppliers in Europe, Japan, South Korea and Canada are likely secondary beneficiaries. The clearest losers would be Chinese-origin equipment makers and, indirectly, US buyers who had been counting on lower-cost imports to hold down capital budgets.
The second-order effect is timing. Even a well-intentioned rule can slow projects if the domestic industrial base cannot expand fast enough to absorb displaced demand. That risk deserves scrutiny on its own merits, separate from the security rationale.
An Even-Handed Read of the Politics
Supply-chain security in the grid is not a partisan invention; both the 2020 Trump executive order and subsequent Biden-era reviews concluded that the sector had exposure worth addressing. Where reasonable people differ is on scope, speed and how narrowly to define ‘risky.’ Overly broad rules can raise costs without proportionate security gains; overly narrow ones can leave gaps. The forthcoming details, not the headline, will determine which category this action falls into.
Background
Concerns about foreign-made equipment in the US grid escalated in May 2020, when the first Trump administration issued Executive Order 13920 declaring a national emergency over bulk-power system supply chains. That order was suspended early in the Biden administration pending review, and subsequent policy focused on voluntary guidance, prohibited-transaction rules for specific equipment and expanded domestic manufacturing incentives.
In parallel, US utilities and data-center developers have wrestled with a global shortage of large power transformers, lead times that can stretch past two years, and rapid load growth driven by AI, electrification and reshoring. Those pressures form the practical backdrop against which any new sourcing restrictions will be judged.
The Public Service Commission of Wisconsin has approved a power-supply arrangement between Alliant Energy and Meta to serve a planned data center in the utility’s Wisconsin territory, according to Wisconsin Watch reporting published May 6, 2026. Commissioners signed off on the deal but publicly criticized its ‘black box’ approach — a reference to confidential contract terms that keep key details, including those bearing on ordinary ratepayers, out of public view.
Executive Summary
State approval of a utility-hyperscaler power contract is normally a routine milestone. What makes this one notable is the regulators’ own commentary: the commission approved the Alliant-Meta arrangement while simultaneously faulting how much of it is shielded from public scrutiny. That dual message — yes to the deal, no to the process — captures the bind facing utility commissions across the country as AI data centers arrive with unprecedented power demands and equally unprecedented confidentiality requirements.
For the data center industry, the approval clears a regulatory hurdle for one of Wisconsin’s marquee technology projects. For utilities and their customers, the ‘black box’ criticism is the more consequential signal: commissioners are telegraphing that future large-load contracts may face demands for greater transparency, standardized tariff structures, or explicit ratepayer-protection findings before they get a vote.
Approve Now, Object Later: What a Split Verdict Signals
Regulators rarely attach public criticism to a deal they are approving. When they do, it usually means they concluded the underlying project serves the state’s interest — jobs, tax base, grid investment — but want to put the utility and its counterparties on notice for the next filing. The ‘black box’ language, as reported by Wisconsin Watch, suggests commissioners felt they were asked to vote on an arrangement whose economics they could describe to the public only in outline. That is an uncomfortable position for a body whose core mandate is protecting captive ratepayers, the households and small businesses who cannot shop for another electric utility.
The practical takeaway for developers and utilities is that approval-with-a-rebuke is a warning shot, not a victory lap. Commissions in several states have begun moving from one-off confidential contracts toward published large-load tariffs — standardized rate schedules for very big customers — precisely because case-by-case secrecy erodes public confidence. Wisconsin’s commissioners appear to be signaling sympathy with that direction, even as they let this deal proceed.
Who Pays for the Grid AI Needs?
The central economic question in any hyperscale power deal is cost allocation: does the data center pay the full cost of the generation, transmission, and distribution built to serve it, or do some costs land in the general rate base that all customers fund? Special contracts typically include minimum-take commitments, exit fees, and contributions toward infrastructure, but when those terms are confidential, outside parties cannot verify that the protections are adequate. That verification gap — not any specific allegation of subsidy — is what a ‘black box’ complaint is really about.
The stakes are larger than one contract. A single hyperscale campus can draw hundreds of megawatts, comparable to a small city, and utilities nationwide are proposing major generation and grid buildouts on the strength of data center demand forecasts. If a big customer later scales back, cancels, or negotiates better terms, stranded costs can migrate to everyone else’s bills. Transparent, verifiable contract structures are the primary tool regulators have to prevent that outcome — which is why their absence draws pointed language even from commissioners voting yes.
Wisconsin’s Bid for the AI Buildout
Wisconsin has emerged as a genuine contender in the Midwest data center race. Microsoft is developing a major campus in Mount Pleasant in We Energies territory, and Meta has publicly committed to a large data center project in Alliant Energy’s service area, announced in late 2025. Competitive electricity, available land, water, fiber routes, and an aggressive economic-development posture have put the state on hyperscaler shortlists that once defaulted to Virginia, Ohio, or Iowa.
That competitive dynamic cuts both ways in regulatory proceedings. States courting these projects have an incentive to accommodate confidentiality, since hyperscalers guard site economics closely and can take their capital elsewhere. But the same growth concentrates demand risk on local utilities and their customers. The commission’s approach here — approve the project, criticize the opacity — is an attempt to hold both goals at once, and other state commissions facing similar filings will likely study how Wisconsin manages that balance.
Background
The approval lands amid a national surge in data center electricity demand driven by AI computing, which has made utility commissions unlikely gatekeepers of the technology buildout. Wisconsin’s share of that surge includes Microsoft’s multi-billion-dollar campus in Mount Pleasant and Meta’s late-2025 announcement of a major data center in Alliant Energy’s service territory — the project behind this power deal. Meta, the parent of Facebook and Instagram, operates one of the world’s largest data center fleets and typically negotiates dedicated energy arrangements, often paired with renewable-power procurement, for each new campus.
Special contracts between utilities and very large customers have existed for decades, but the scale of AI-era loads has intensified scrutiny of them. Regulators in several states have questioned whether confidential, negotiated deals adequately insulate ordinary customers from the cost of new generation and grid capacity built for a single tenant — the same tension the Wisconsin commission voiced in this decision.
American Electric Power is publicly weighing withdrawal from two of the country’s largest wholesale power markets — PJM Interconnection and the Southwest Power Pool — citing the slow pace at which new generation gets studied, approved and connected to the grid, according to a report published by Utility Dive on 6 May 2026.
AEP is among the largest transmission owners in PJM and a long-standing SPP member through its Oklahoma, Arkansas, Louisiana and Texas operating companies. The available source material is headline-level: it indicates AEP is examining an exit, not that the company has filed a withdrawal notice with federal regulators or set a date.
Executive Summary
Regional transmission organizations, or RTOs, are the independent bodies that run the high-voltage grid and wholesale power markets across most of the eastern United States. Utilities join them voluntarily, and once inside, they hand over control of transmission planning and the queue that determines when new power plants can plug in. AEP saying out loud that it may leave two of them is unusual. Utilities have migrated between RTOs before, but a large incumbent threatening to step outside organized markets entirely is a governance event, not a routine filing.
The stated grievance is generation interconnection: the multi-year engineering and cost-allocation process every new power plant must clear before it can energize. Queues across the country have lengthened as developers filed far more projects than the grid can absorb, and as demand forecasts — driven heavily by data centers and industrial electrification — moved faster than the studies designed to serve them. For a utility trying to build or contract generation to match load growth in Ohio, Indiana, Virginia, West Virginia and Oklahoma, the queue is the bottleneck between a signed customer and a served customer.
What matters for buyers of digital infrastructure is not whether AEP ultimately leaves. It is that a utility of this size considers the market structure itself a liability worth reopening. Data centers are sited on ten- to twenty-year horizons; the assumption that the rules governing power supply are stable for that period is now a live question in a meaningful part of the eastern grid.
Two Markets, One Complaint — and What That Implies
The most analytically interesting feature of the report is that AEP names both PJM and SPP. These are very different institutions. PJM coordinates a largely restructured, competitive footprint across the Mid-Atlantic and parts of the Midwest, where merchant generators compete and a capacity market pays for future reliability. SPP spans mostly vertically integrated territory in the Plains and South, where utilities still own their generation and recover costs through state rate cases. If the same utility finds the interconnection process unworkable in both, the diagnosis pointing only at PJM’s design is incomplete.
That cuts in two directions, and both deserve equal scrutiny. It strengthens the argument that queue processing is a systemic failure of the current model rather than one operator’s mismanagement — a fair reading. It also weakens the implicit premise that leaving would solve the problem, because a utility outside an RTO still runs an interconnection process under federal rules, still needs system impact and facilities studies, and still faces the same constrained supply of turbines, transformers, high-voltage breakers and skilled labor that is throttling projects industry-wide. Neither AEP nor the RTOs have, in the material available, shown how much of the delay is queue administration versus physical supply chain. That distinction is the whole argument, and it is unresolved.
What Leaving an RTO Actually Requires
Exit is not a decision a utility makes alone. Withdrawal from an RTO typically requires approval from the Federal Energy Regulatory Commission, compliance with notice provisions in the RTO’s governing agreements, and in practice the acquiescence of state regulators in every state where the utility operates — states that have their own views on reliability, rates and whether their consumers benefit from a larger market. FERC has historically been attentive to whether a departure strands costs on the members left behind, and obligations for transmission projects already approved under regional plans generally do not evaporate on the way out.
Then there is the operational bill. An RTO provides centralized dispatch, reserve sharing across a wide area, and a resource adequacy framework. A departing utility must replicate those functions or buy them, either by running its own balancing authority or joining another market. It also inherits seams — the friction at the borders between neighboring grids, where power that used to flow on a single set of rules now needs contracts, scheduling and duplicated reserves. Seams cost real money and, historically, are the argument that built RTOs in the first place. Precedent from past migrations, such as the moves of several Midwestern utilities from MISO into PJM last decade, suggests a timeline measured in years, not quarters.
None of that makes the threat empty. A large transmission owner signalling that the exit math is being run changes the bargaining table inside RTO stakeholder processes, where votes are weighted and reform packages are negotiated among generators, load-serving entities, states and consumer advocates. Observers are entitled to ask whether this is leverage, intent, or both — and to note that leverage is a legitimate governance tool, not a scandal. The honest answer is that the available reporting does not distinguish between them.
The Data Center Angle Is Real but Frequently Misstated
Two clarifications matter here. First, the process AEP is reportedly complaining about is generation interconnection — plugging power plants in — which is a separate queue from large load interconnection, the process a hyperscale campus goes through to plug demand in. Developers care about both, because a load request is only as good as the supply behind it, but they are governed by different rules and different disputes.
Second, the geography deserves precision. Northern Virginia’s Data Center Alley sits in Dominion Energy’s service territory, not AEP’s, so an AEP withdrawal would not remove Loudoun County from PJM. What it would do is shrink the footprint across which PJM plans transmission, shares reserves and allocates costs — and a smaller pool changes the arithmetic for everyone still inside, including the utilities serving the Alley. AEP’s own data center exposure is concentrated elsewhere: central Ohio, which has attracted substantial hyperscale and semiconductor investment, plus growing interest across Appalachian Power’s Virginia and West Virginia footprint and Indiana Michigan Power’s territory.
For site selection, the practical effect is a new diligence line item. A campus reaching commercial operation in 2030 or later, in AEP territory, may be energized under a market structure, capacity obligation and cost-allocation regime different from the one modelled at underwriting. That is not a reason to avoid the region; central Ohio’s fundamentals — land, fiber, water, workforce, existing anchor tenants — are unchanged. It is a reason to price structural risk explicitly rather than assume it away.
Winners, Losers and the Claims That Remain Unproven
If AEP stayed and secured faster queue treatment, the winners would be its own generation plans and the customers waiting on them, and the loser would be the principle that all developers queue on equal terms — a principle merchant generators and independent power producers defend precisely because it protects them from incumbent preference. If AEP left, it would gain control over the sequencing of its own build-out and lose the reserve-sharing and market-depth benefits of a wide area. Consumers could plausibly land on either side depending on whether seams costs exceed the value of faster capacity additions. Anyone claiming certainty about that outcome, in either direction, is ahead of the evidence.
The RTOs have a defensible record to point to. Both operate under FERC Order 2023, which replaced serial, project-by-project studies with cluster analysis and first-ready, first-served rules, and PJM has stood up expedited pathways for shovel-ready projects. It is reasonable for PJM and SPP to argue that reforms adopted only recently have not had time to show results. It is equally reasonable for a utility facing near-term load commitments to say that a reform which pays off in 2029 does not help a customer energizing in 2027. Both claims can be true; neither is proven by assertion.
The fair-minded conclusion is narrow. This is a credible signal of strain in RTO governance from a participant with standing to know, reported at a level of detail too thin to adjudicate. It should raise the priority of queue reform on every regulator’s docket. It should not, on this evidence, be read as a verdict that PJM or SPP have failed, nor as a commitment by AEP to go anywhere.
Background
American Electric Power is one of the largest electric utility holding companies in the United States, headquartered in Columbus, Ohio, operating regulated utilities across a footprint that stretches from Michigan and Ohio through Appalachia into Oklahoma, Arkansas, Louisiana and Texas. That geography is unusual: it straddles three separate wholesale market structures — PJM in the east, SPP in the west, and ERCOT in Texas — which gives the company direct comparative experience of how different market designs handle new generation.
PJM and SPP both emerged from the federal push in the late 1990s and 2000s to separate grid operation from utility ownership and create competitive wholesale markets. The bargain was that utilities would cede control of transmission planning and dispatch in exchange for a larger, more efficient pool. That bargain has come under strain since 2023 as electricity demand began growing again after two decades of flat consumption, driven substantially by data centers, and as interconnection queues filled with more projects than could be studied or built. The result is a widening gap between how quickly load can be signed and how quickly supply can be connected — the gap at the centre of AEP’s reported complaint.
The North American Electric Reliability Corporation (NERC) — the regulatory body responsible for the reliability of the bulk power system in the United States and Canada — has issued a warning that the rapid growth of data-center electricity demand risks overtaxing the grid, according to reporting by Latitude Media published May 3, 2026. The alert places the AI-driven data-center build-out squarely among the leading reliability risks facing the North American power system.
Executive Summary
NERC is not a trade group or an advocacy organization: it is the FERC-certified Electric Reliability Organization whose standards are mandatory and enforceable for grid operators across North America. When NERC elevates a risk, utilities, regional transmission organizations, and regulators are expected to respond. The reported warning frames unchecked data-center load growth — the wave of large, concentrated electricity demand from AI and cloud facilities — as a material threat to grid reliability, not merely a planning challenge.
The significance lies less in the observation itself, which grid planners have discussed for several years, than in the messenger and the framing. Reliability warnings from NERC historically precede changes in interconnection rules, resource-adequacy requirements, and planning standards. For data-center developers and their customers, that means the era of assuming the grid will simply absorb new campus-scale loads is closing, and the terms of grid access are likely to tighten.
Why the Messenger Matters More Than the Message
Grid strain from data centers is not a new story — utilities in Virginia, Texas, Georgia, and elsewhere have reported unprecedented interconnection queues for years, and NERC’s own long-term reliability assessments have repeatedly flagged accelerating demand growth after two decades of roughly flat US electricity consumption. What changes when NERC issues a pointed warning is the institutional weight behind it. NERC’s assessments feed directly into how utilities justify infrastructure spending before state regulators and how regional grid operators set reserve requirements — the buffer of spare generating capacity kept available for peak conditions.
A reliability warning of this kind typically functions as a forcing mechanism. It gives utilities cover to demand stricter commitments from large-load customers, gives regulators grounds to scrutinize speculative interconnection requests, and gives grid operators justification to slow or condition approvals. The practical effect is that a NERC alarm tends to translate, over the following quarters, into new rules rather than remaining rhetoric.
The Core Problem: Speed, Scale, and Concentration
Data-center load is difficult for grid planners for three compounding reasons. First is speed: a large data-center campus can be built in two to three years, while new high-voltage transmission lines and large power plants routinely take seven to ten years to permit and construct. Second is scale: modern AI campuses request power in the hundreds of megawatts — a single facility can draw as much electricity as a mid-sized city. Third is concentration: developers cluster where fiber, land, and power intersect, so the demand lands on a handful of regional grids rather than spreading evenly across the country.
There is also a planning-data problem that reliability bodies have wrestled with publicly: developers frequently submit interconnection requests to multiple utilities for the same project, a practice sometimes called phantom load. Grid planners cannot easily distinguish which requests represent real, committed demand, which makes forecasting — the foundation of reliability planning — genuinely harder. A warning about “unchecked” growth is, in part, a warning about growth that planners cannot see clearly.
Winners, Losers, and the Coming Rule Changes
If NERC’s warning hardens into policy, the likely instruments are familiar: stricter financial commitments and deposits for interconnection requests, minimum-take or ramp-schedule contracts for large loads, requirements for on-site or contracted generation, and curtailment provisions that let grid operators reduce a data center’s draw during system emergencies. Each of these shifts risk from ratepayers and the grid back onto the load itself.
The relative winners in that world are developers who already control their power story — those with signed long-term supply agreements, on-site generation, flexible-load capability, or sites in regions with surplus capacity. Speculative developers banking on cheap, unconditional grid access face longer timelines and higher costs. Utilities gain leverage but also face a genuine dilemma: overbuild for demand that may not materialize and ratepayers foot the bill, or underbuild and reliability suffers. That asymmetry is precisely why an independent reliability body raising the flag matters — it pushes the debate from utility earnings calls into the formal reliability-standards process.
What a Reliability Warning Does Not Say
It is worth being precise about what a warning like this does and does not establish. It does not mean blackouts are imminent, and it does not assign blame to any individual company or project. Reliability risk is probabilistic: it means the margin between available supply and projected peak demand is narrowing faster than infrastructure is being added, raising the odds of emergency measures during extreme conditions. Nor does the warning settle the policy question of who should pay for grid upgrades — that fight is playing out state by state in rate cases and large-load tariff proceedings, and NERC’s role is to describe the risk, not to allocate its costs.
Background
NERC was formed in 1968 after the 1965 Northeast blackout and became the enforceable Electric Reliability Organization for the United States under the Energy Policy Act of 2005, with the Federal Energy Regulatory Commission (FERC) as its overseer. It publishes seasonal and long-term reliability assessments that grid operators and utilities treat as authoritative, and in recent years those assessments have tracked a historic shift: after two decades of essentially flat US electricity demand, consumption is rising again, driven by AI and cloud data centers, manufacturing reshoring, and electrification.
Data centers sit at the center of that shift because their demand is large, fast-arriving, and geographically concentrated, while the transmission and generation needed to serve them move on much slower permitting and construction timelines. The May 2026 warning reported by Latitude Media extends a line of increasingly direct statements from reliability authorities that the gap between load growth and infrastructure build-out is itself becoming a systemic risk.
President Trump has declared a national emergency covering the U.S. electric grid and moved to block certain foreign-made equipment from being installed on it, according to a report published by Utility Dive on May 2, 2026. The action is framed as a national-security measure aimed at hardware installed in the bulk power system — the high-voltage backbone that moves electricity from generators to local distribution networks.
The report available to us is a headline-level summary rather than a full text of the declaration, so the operative details — which equipment classes are covered, which countries or vendors are implicated, when restrictions take effect, and whether orders already in transit are exempt — are not established by the source. What is established: an emergency has been declared, and a prohibition on some foreign-made grid equipment is being pursued.
Executive Summary
Emergency declarations matter in the power sector because they unlock authorities that ordinary rulemaking does not. Depending on the statute invoked, a declared emergency can let federal agencies restrict procurement, direct generation to stay online, or waive certain permitting and environmental review steps. The same declaration can therefore both accelerate some projects and constrain others — which is precisely the tension for anyone buying electrical infrastructure right now.
For data-center developers, the constraint side is the one to watch. Large power transformers, medium-voltage switchgear, high-voltage breakers, and grid-tied inverters are long-lead items with a globally concentrated supply base. Any restriction that narrows the pool of qualified suppliers pushes demand toward domestic manufacturers whose order books are already committed to utilities. The binding constraint on a campus is rarely the servers; it is the substation.
The measured read is that this is a supply-side policy event with delivery-schedule consequences, not a demand-side one. It does not change how much power AI and cloud buildouts need. It changes who is legally permitted to sell the hardware that delivers it, and how long the queue is to get it.
What a Grid Equipment Lockdown Actually Touches
“Grid equipment” is a broad phrase covering a narrow set of physically enormous objects. The category most exposed is the large power transformer — a custom-built unit, often weighing hundreds of tons, that steps voltage up or down between transmission and distribution. These are not catalog items. They are engineered to a utility’s specification, built to order, and shipped by specialized heavy haul. A second category is power electronics: grid-tied inverters that convert direct current from solar and battery systems into alternating current the grid can accept, along with the control and communications gear that supervises them.
The security argument for scrutinizing this hardware is not exotic. Modern transformers and inverters contain embedded firmware, remote monitoring links, and control interfaces. A component installed on the bulk power system sits inside the trust boundary of critical infrastructure for decades. Whether the current declaration reflects a specific, documented threat or a precautionary posture is exactly what the underlying record would need to show — and the summary source available here does not show it either way. That is a gap in what has been published, not evidence for or against the policy.
The counter-consideration deserves the same seriousness. Restricting suppliers on a compressed timeline can degrade reliability through a different mechanism: utilities that cannot source replacement units carry thinner spares inventories, and thin spares turn ordinary equipment failures into extended outages. A durable policy has to weigh the security risk of a compromised component against the reliability risk of a component that cannot be obtained at all. Neither risk is hypothetical, and the release as reported does not tell us how the administration balanced them.
The Procurement Math for Data Center Developers
Data-center power procurement is a queue problem before it is a price problem. A developer signs an interconnection agreement with a utility, and that agreement typically requires new or upgraded substation equipment. Some of that equipment the utility buys; increasingly, on large campuses, the customer buys it — sometimes ordering transformers years ahead and holding them as owner-furnished equipment. That practice exists precisely because lead times for heavy electrical gear have been the industry’s chronic bottleneck for several years, well before this declaration.
Narrowing the approved supplier list reprices that queue in two ways. First, orders redirect toward domestic and allied manufacturers whose capacity is already substantially spoken for, extending waits for everyone in line. Second, buyers with the balance sheet to place speculative orders, pay expedite premiums, and absorb schedule slippage gain a relative advantage. That asymmetry favors hyperscalers and the largest developers over regional colocation operators and enterprise self-builds. The policy is neutral on its face; its practical incidence is not.
The winners are more predictable than usual. Domestic transformer and switchgear manufacturers, and firms with U.S. or allied-country assembly footprints, gain pricing power and a stronger case for capacity expansion. Whether that translates into new domestic factories depends on whether they believe the restriction will outlast the administration that issued it — a genuinely open question given that grid-equipment restrictions have been issued, suspended, and revisited across previous administrations. Manufacturers finance multi-hundred-million-dollar plants on decade horizons, not on executive actions that can be reversed by the next signature.
Interconnection Timelines and the Risk of Both Directions
The most consequential detail, and the one the reported summary does not settle, is retroactivity. If restrictions apply only to future purchase orders, developers with equipment already ordered are largely insulated and the market effect is gradual. If they reach equipment already manufactured, in transit, or installed but not yet energized, the effect is immediate and disruptive: projects near completion could face requalification, re-sourcing, or replacement of units that cost millions and take years to rebuild. The gap between those two scenarios is the difference between a manageable procurement adjustment and a wave of schedule failures.
Emergency authorities cut both ways here, which is why the declaration should not be read as purely restrictive. The same posture that constrains sourcing can also be used to expedite approvals, keep retiring generation available, or prioritize allocation of scarce equipment to critical loads. Whether data centers are treated as a critical load or as discretionary demand competing with residential and industrial customers is a policy choice that has not been publicly resolved — and it materially affects who gets a transformer first.
The practical response for anyone with capital committed to a site is unglamorous: audit the country of origin and component provenance of every long-lead electrical item on order, confirm with suppliers whether their units and subassemblies would fall inside a plausible restriction, and revisit contractual force-majeure and schedule-relief language with counsel. Those steps are cheap relative to the exposure, and they are worth taking before the operative text is fully known rather than after.
Reading a Thin Source Honestly
One editorial note is warranted. The material available for this article is a headline and a trade-press attribution, not the text of the declaration or an accompanying order. That supports reporting the fact of the action and analyzing the mechanisms it plausibly engages. It does not support claims about scope, covered nations, dollar impacts, or effective dates, and readers should treat any coverage asserting those specifics without citing the operative document with corresponding caution.
It also means the policy deserves evaluation on its published record once that record exists. Supporters will argue that supply-chain provenance in critical infrastructure is a legitimate and long-standing security concern that prior administrations of both parties have engaged with. Critics will argue that emergency authorities are a blunt instrument for a structural manufacturing problem, and that capacity is built by sustained industrial policy rather than by prohibition. Both arguments are testable against the actual order — its findings, its exemptions, and its waiver process. Neither is testable against a headline.
Background
Concern about foreign-manufactured equipment on the U.S. bulk power system predates this action. A 2020 executive order sought to restrict bulk-power-system equipment associated with foreign adversaries; it was suspended under the subsequent administration and the underlying policy question revisited, with the Energy Department separately addressing certain equipment serving critical defense facilities. The recurring theme across those efforts is that transmission-class hardware is long-lived, software-controlled, and sourced from a globally concentrated manufacturing base.
That base has been strained independently of security policy. Sustained demand from grid modernization, renewable interconnection, electrification, and — most recently — AI and cloud data-center buildouts has pushed lead times for transformers and switchgear well beyond historical norms, making electrical equipment rather than land, capital, or chips the practical gating factor on many campuses. Any policy that changes who may supply that equipment therefore lands on a market that already had little slack.
PJM Interconnection, the grid operator serving the largest electricity market in the United States, has reopened its interconnection queue — the formal waiting line new power plants must join before they can connect to the grid — and gas-fired generation leads the intake at 106 gigawatts (GW), according to an April 30, 2026 report by Utility Dive. The queue had been closed to new entrants for years while PJM worked through a massive backlog under reformed study rules.
Executive Summary
The reopening of PJM’s queue is one of the most consequential grid events of the decade for the data-center industry. PJM’s territory — spanning 13 states and the District of Columbia, including the Northern Virginia corridor that hosts the world’s densest concentration of data centers — has been the epicenter of the load-growth crunch. For years, developers of new generation could not even get in line, while demand forecasts climbed relentlessly on the back of AI and cloud expansion.
That 106 GW of gas-fired capacity leads the new intake is the headline signal: developers are betting that dispatchable, fuel-based generation is what the market will pay for. For context, 106 GW of proposed gas alone approaches the scale of PJM’s entire historical peak load — a striking statement of intent, even acknowledging that interconnection requests are proposals, not power plants, and that historically only a fraction of queued projects reach commercial operation.
The Queue Reopens Into a Seller’s Market
An interconnection queue is the study pipeline through which a grid operator evaluates whether a proposed generator can connect safely and what network upgrades it must fund. PJM froze new entries while it transitioned from a first-come, first-served process — which had become clogged with speculative projects — to a clustered, first-ready, first-served model. The reopening is therefore a pressure release: years of pent-up development interest arriving all at once.
The market these projects are entering is unusually favorable to generators. PJM’s recent capacity auctions have cleared at elevated prices, reflecting tightening reserve margins as older coal and gas plants retire faster than replacements arrive and as data-center load grows. High capacity prices are precisely the signal designed to attract new steel in the ground — and 106 GW of gas proposals suggests the signal is being heard.
Why Gas Leads — Economics, Not Ideology
Gas-fired turbines dominate this intake for practical reasons. They are dispatchable — able to run on demand rather than when the weather cooperates — which is what capacity markets and 24/7 data-center loads reward most. They site on relatively small footprints near existing gas pipelines and transmission. And developers can point to a revenue stack (capacity payments, energy sales, and potentially direct contracts with large loads) that pencils today.
But the gas wave faces its own bottlenecks. Turbine manufacturers are reporting multi-year order backlogs industry-wide, EPC (engineering, procurement, and construction) labor is scarce, and gas pipeline expansion in parts of PJM’s eastern footprint has historically faced permitting resistance. Proposing 106 GW is easy; procuring turbines, pipe, and crews for even a fifth of it is the hard part. The queue position is now arguably the cheapest asset in the whole development chain.
What This Means for Data-Center Developers
For hyperscalers and colocation operators stuck in multi-year utility interconnection waits, a generation-heavy queue is cautiously good news: more supply eventually means faster load interconnection and less severe capacity-price escalation. It also strengthens the case for co-location deals, in which a data center sites directly alongside a new plant and contracts for its output — a structure regulators in PJM have been actively wrestling with.
The timing mismatch remains the industry’s core problem. Data centers can be built in 18–24 months; a new combined-cycle gas plant typically takes four or more years from queue entry through studies, permitting, and construction. Even under PJM’s reformed process, the bulk of this 106 GW cannot plausibly serve load until late this decade. Buyers planning capacity for 2027–2028 should not count on this queue cycle to bail them out.
The Decarbonization Tension Nobody Should Ignore
A gas-led buildout sits uneasily beside the carbon-neutrality pledges of the very customers driving the demand. Most major cloud providers maintain public net-zero or carbon-free-energy targets, and a decade of gas additions in PJM would make those targets harder to reconcile with grid reality — unless paired with offsets, carbon capture, or an eventual nuclear and storage wave. The honest framing is that the market is prioritizing reliability and speed-to-power first and emissions second. Whether that ordering persists will depend on state policy in PJM’s footprint, federal rules, and how loudly corporate energy buyers push back through their procurement.
Background
PJM Interconnection grew out of a 1927 power pool among Pennsylvania and New Jersey utilities and today operates the largest wholesale electricity market in the United States. Its territory contains Northern Virginia’s “Data Center Alley,” which by itself consumes more data-center power than most countries. Over the past several years PJM became the poster child for the interconnection bottleneck: thousands of proposed projects — predominantly renewables in earlier cycles — languished in multi-year study backlogs, prompting a federally approved overhaul of its queue process and a temporary halt to new applications.
The reopening lands amid record demand forecasts, plant retirements, and capacity prices that have drawn political scrutiny across PJM’s member states. The resource mix of this new intake — and how much of it survives to construction — will shape the region’s reliability, emissions trajectory, and data-center growth capacity into the 2030s.
