PJM Interconnection, the largest electric grid operator in North America, set a new all-time peak-load record of 168.158 gigawatts (GW) during a heat wave, S&P Global reported on July 9, 2026. Peak load is the highest instantaneous electricity demand a grid must serve, and PJM’s footprint spans 13 states and the District of Columbia — including Northern Virginia, the densest data center market in the world.
Executive Summary
The number itself is the story: 168.158 GW is an all-time record for a grid that has operated since 1927, exceeding the prior widely cited all-time mark of roughly 165.6 GW set in the summer of 2006. Grid demand in mature economies was assumed for years to be flat or declining as efficiency gains offset growth; a new absolute record — set during a heat wave, when air conditioning load stacks on top of everything else — signals that assumption no longer holds in PJM territory.
Why it matters: PJM is where the AI infrastructure boom and the physical grid meet most directly. The region hosts the largest concentration of data centers on earth, and PJM’s own planning processes, capacity auctions, and interconnection queue have all been reshaped by projected data center growth. A record peak turns those projections into observed, metered reality — with consequences for power prices, data center siting decisions, and the pace of generation and transmission construction.
The End of Flat Demand
For roughly two decades, U.S. grid planners could count on a comfortable pattern: efficiency improvements (LED lighting, better HVAC, industrial offshoring) absorbed most economic growth, so peak demand crept along or even fell. That the previous PJM record dated to 2006 illustrates the point — the grid went nearly twenty years without needing to serve a bigger hour. A new record, driven by weather layered on structural load growth, marks a regime change. Data centers, electrification of heating and transport, and reshored manufacturing are all pushing the same direction, and data centers are the fastest-moving of the three because a single large AI campus can draw hundreds of megawatts continuously, day and night.
Heat Waves Are the Stress Test
Records like this are set when a heat wave pushes air-conditioning demand to its maximum at the same time that always-on loads — including data centers — are running flat out. Unlike residential cooling, data center load does not relent in the evening or on weekends, which raises the floor beneath every weather-driven spike. For grid operators, that changes the risk calculus: reserve margins (the buffer of spare generating capacity above expected peak) get consumed from both ends, by rising peaks and by the retirement of older coal and gas plants. PJM has publicly warned for several years that retirements were outpacing new entry; a record peak is exactly the scenario those warnings anticipated.
The Economics: Someone Pays for the Peak
Grids are built for their single highest hour, so peaks are expensive. In PJM, the cost shows up through capacity auctions — payments to generators for being available when demand spikes — and recent PJM capacity auctions have cleared at record-high prices, driven in large part by demand forecasts that data center growth dominates. Those costs flow to ratepayers across the footprint, which is why data center load growth has become a live political issue in states like Virginia, Ohio, and Pennsylvania. A verified record peak strengthens the case of utilities and generators seeking to build; it also sharpens questions from consumer advocates about who should bear the cost of infrastructure that primarily serves new industrial customers.
Winners, Losers, and the Siting Chessboard
Owners of existing dispatchable generation — gas, nuclear, and remaining coal in the PJM footprint — are clear near-term beneficiaries, since scarcity raises the value of every megawatt that can run on command. Data center developers face a more complicated picture: record peaks validate the demand they are bringing, but also lengthen interconnection timelines, raise power costs, and invite regulatory scrutiny. Expect continued interest in behind-the-meter and co-located generation, long-term nuclear power purchase agreements, and siting in less-constrained regions. For the connectivity and colocation industry broadly, grid capacity — not land, not fiber — is now the binding constraint on where digital infrastructure gets built.
Background
PJM Interconnection began in 1927 as a power pool among Pennsylvania and New Jersey utilities and grew into the largest regional transmission organization in North America, coordinating the grid and wholesale markets for 13 states and Washington, D.C. Its territory includes Northern Virginia’s “Data Center Alley,” the densest concentration of data centers in the world, which has made PJM the front line where AI-driven electricity demand meets grid reality.
For most of the 2010s, PJM demand was flat as efficiency gains offset growth, and its 2006-era peak record went unchallenged. That changed as data center construction accelerated, power plant retirements thinned reserve margins, and PJM’s capacity auctions began clearing at record prices — a trajectory that made a new all-time peak a question of when, not if.
On 2026-07-09, CNBC published a ranking of the ten U.S. states it judges best positioned to land new artificial-intelligence data center deals despite a rising tide of public opposition to large campuses. The list frames a national contest for hyperscale investment against the backdrop of grid strain, water concerns and local political pushback.
Executive Summary
The CNBC feature is essentially a state-by-state scorecard for AI data center attractiveness at a moment when siting has become the single hardest problem in the industry. Where a decade ago the debate was about tax abatements and fiber routes, it now turns on interconnection queues, gas turbine availability, water withdrawals and whether a county commission will approve a rezoning after a packed public hearing.
For infrastructure buyers, the ranking matters less as a definitive verdict than as a signal of where the pipeline is likely to concentrate. For host communities, it is a reminder that the states judged most ‘winnable’ by capital are precisely the ones facing the loudest local debates about who benefits from a multi-billion-dollar build.
What a ‘Best Positioned’ Ranking Actually Measures
Rankings of this kind typically blend a handful of durable inputs: available and dispatchable power, transmission headroom, permitting speed, tax treatment, land availability, workforce, fiber density and climate suitability for cooling. None of those variables is new, but their relative weight has shifted sharply. Power availability — measured in years to interconnect, not megawatts on paper — has overtaken tax policy as the binding constraint for gigawatt-scale AI campuses.
That reordering changes which states look attractive. Jurisdictions with vertically integrated utilities, permissive siting rules for gas peakers or nuclear uprates, and cooperative public utility commissions have a structural edge over states with congested interconnection queues, regardless of how generous their incentives look on a spreadsheet.
The Opposition Curve Is Bending
The CNBC framing — ‘despite rising public opposition’ — reflects a real inflection. Data center opposition, once confined to a few Northern Virginia counties, is now a recurring feature of local politics in Georgia, Texas, Arizona and the Midwest. Residents cite noise from cooling equipment, transmission line routing, water use, property tax abatements and the perception that grid costs are being socialized while benefits accrue to a handful of hyperscalers.
The important business question is not whether opposition exists, but whether it changes outcomes. So far the evidence is mixed: some projects have been delayed or downsized, others have proceeded largely on schedule after community benefit agreements. States that develop clearer siting rules and cost-allocation frameworks may quietly pull ahead of nominally cheaper jurisdictions where every hearing becomes a referendum.
Winners, Losers and the Second Tier
A top-ten list implicitly names losers — states that were competitive for cloud-era builds but are structurally disadvantaged for AI-scale campuses. The likely laggards are jurisdictions with tight grids, aggressive decarbonization timelines that constrain new gas generation, or moratoria under active consideration. That does not mean those markets go dark; they will still host inference, edge and enterprise workloads. But the trillion-dollar question of where training capacity lands is increasingly being answered elsewhere.
For the second tier — states that did not make the list — the strategic response is unglamorous: shorten interconnection timelines, publish transparent siting criteria, and negotiate cost-allocation rules that survive contact with a local newspaper. Incentive stacking alone no longer moves the needle.
What the Ranking Cannot Tell You
Any state-level scorecard obscures the fact that AI siting decisions are made at the substation, not the statehouse. Two counties within the same ‘winner’ state can face wildly different interconnection timelines, water availability and community sentiment. Investors reading the list should treat it as a starting filter, not a site selection tool. And host communities should recognize that being on such a list is a leading indicator of proposals to come, not a guarantee of net benefit.
Background
The U.S. data center industry has spent two decades clustering around a handful of markets — Northern Virginia, Dallas, Phoenix, Silicon Valley, Chicago and Atlanta — chosen for fiber, power and tax treatment. The AI training boom that accelerated after 2023 broke that pattern by demanding campuses an order of magnitude larger, with power needs measured in gigawatts and lead times measured in years.
As those requirements collided with congested grids and slow permitting in legacy markets, developers began scouting states with spare generation, cooperative utilities and available land. That shift, in turn, exported the siting debate to communities with little prior experience of large-scale digital infrastructure — and produced the public opposition the CNBC ranking now takes as its backdrop.
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.
Reuters reported on June 30, 2026 that PJM Interconnection — the largest power grid operator in the United States, coordinating electricity across 13 states and the District of Columbia for roughly 65 million people — is moving toward actively managing data center demand on its system. The report signals a shift from treating data centers as ordinary customers whose consumption must simply be served, toward a framework in which the grid operator can shape when and how much power the largest new loads draw.
Details of the mechanism, timeline, and scope were not spelled out in the headline announcement, but the direction alone is consequential: PJM’s territory includes Northern Virginia’s “Data Center Alley,” the densest concentration of data centers in the world, and the region at the center of the AI-driven surge in U.S. electricity demand.
Executive Summary
According to Reuters, PJM is taking steps toward managing data center demand rather than passively absorbing it. For decades, U.S. grid planning worked on a simple premise: customers decide how much electricity they need, and the grid builds to serve it. AI data centers — single facilities that can draw hundreds of megawatts, comparable to a small city — have broken that premise. Interconnection queues are backed up, capacity prices in PJM’s markets have surged, and the gap between how fast data centers can be built (one to two years) and how fast power plants and transmission can be built (five to ten years) keeps widening.
Moving to “manage” that demand means the operator of America’s biggest wholesale power market is preparing tools — potentially ranging from voluntary demand-response participation to conditions on new large-load interconnections to curtailment provisions, though the report does not specify which — to control the timing and firmness of data center consumption. That matters far beyond PJM’s footprint: as the largest grid and the home of the world’s biggest data center cluster, PJM’s rules tend to become the template other regions study.
For the data center industry, the message is that access to the grid is no longer an unconditional entitlement. Flexibility — the ability to shift, shed, or self-supply load — is becoming a bargaining chip in getting connected at all.
From Passive Host to Active Manager
Grid operators like PJM are regional transmission organizations (RTOs): nonprofit entities that run the wholesale electricity market and the high-voltage network across their territory, under rules approved by federal regulators. Historically, their job was to forecast demand and make sure supply met it. Demand itself was treated as a given. A move toward managing data center demand inverts that relationship for the first time at this scale — the grid operator would have a say in how the largest customers consume, not just how generators produce.
The trigger is arithmetic. Load growth in PJM was essentially flat for nearly two decades; AI data centers ended that era abruptly. When a single campus can request as much power as a steel mill or a small utility’s entire service territory, and dozens of such requests arrive at once, the traditional “build to serve” model produces either reliability risk or enormous costs socialized across all ratepayers. Managing demand is the third option: make the new load itself part of the reliability solution.
The Economics of Curtailable Compute
The core idea behind demand management is that not every megawatt-hour of computing is equally urgent. AI training runs can, in principle, pause or shift in time; some workloads can migrate between facilities in different regions. If data centers agree to reduce consumption during the few dozen hours a year when the grid is most stressed, the system needs less peak capacity — which is exactly the product whose price has been surging in PJM’s capacity auctions, the market where power plants are paid to be available.
The unresolved tension is that most data center operators sell their customers uninterrupted uptime, and inference workloads serving live users are far harder to pause than training. Whether flexibility is genuinely available at scale — and at what price data center operators would sell it — is the open economic question. If PJM’s framework rewards flexible loads with faster interconnection or lower costs, it effectively creates a market price for interruptibility, and data center designs will adapt to capture it: more batteries, more on-site generation, more workload-orchestration software.
Winners, Losers, and the Ratepayer Question
Developers with flexible-by-design facilities, on-site generation, or storage stand to gain priority in a demand-managed regime. Operators marketing strict 24/7 firmness with no curtailment tolerance may face slower interconnection or higher costs. Utilities and generators face a subtler effect: managed demand blunts the extreme scarcity that has driven capacity prices up, which helps consumers but trims the windfall that scarcity was delivering to existing power plants.
For households and businesses in PJM’s 13-state footprint, the stakes are direct. Capacity costs flow into retail electricity bills, and the politics of ordinary ratepayers subsidizing infrastructure for the world’s wealthiest technology companies have grown sharp. A credible demand-management framework is partly a political instrument: it lets PJM tell states and consumers that data centers are being asked to carry reliability risk, not just impose it. Whether the framework has real teeth — mandatory obligations versus voluntary programs — will determine whether that assurance holds up.
A Template Other Grids Will Study
PJM is not acting in a vacuum. Texas’s ERCOT grid, the other major destination for large flexible loads, has been developing its own approach to interconnecting and, when necessary, curtailing very large customers. When the two biggest data center markets in the country both condition grid access on demand flexibility, it stops being an experiment and becomes the emerging national norm. Data center site selection, financing models, and colocation contracts will all have to price in a world where the grid can ask the largest computers on Earth to throttle down.
Background
PJM Interconnection, headquartered in Pennsylvania, grew from a 1927 power pool into the largest regional transmission organization in the United States, dispatching generation and running wholesale power markets across a footprint from Illinois to the mid-Atlantic. Its territory includes Northern Virginia, where decades of fiber density and proximity to federal and enterprise customers created “Data Center Alley” — the largest data center market in the world.
The generative-AI boom that accelerated from 2023 onward transformed data centers from a steady, modest slice of electricity demand into the dominant driver of U.S. load growth, ending a long era of flat consumption. PJM’s capacity auctions delivered record-high prices as demand forecasts jumped, interconnection requests piled up, and state officials began questioning who should bear the cost. The June 2026 move toward managing data center demand is the institutional response to that collision between AI’s growth curve and the grid’s construction timelines.
PJM Interconnection, the regional grid operator serving 13 states and the District of Columbia, announced on June 16, 2026 via its Inside Lines publication that its overhauled generator interconnection process is delivering results. The announcement, titled “New Interconnection Process Delivers,” signals that the reformed study framework — approved by federal regulators in 2022 to replace PJM’s clogged first-come, first-served queue — is now moving projects through review at a pace the old system could not match.
Executive Summary
Interconnection is the process by which a new power plant, battery, or other resource gets studied and approved to plug into the transmission grid. For years it has been one of the most stubborn bottlenecks in American energy: PJM’s legacy queue accumulated thousands of speculative and serious projects alike, with study timelines stretching years and many projects withdrawing before ever being built. In 2022, PJM won federal approval to replace that serial queue with a cluster-based, “first-ready, first-served” model that studies projects in batches and requires financial commitments up front to weed out placeholders.
PJM’s declaration that the new process “delivers” matters because the region is simultaneously facing surging electricity demand — driven prominently by data center growth in markets like Northern Virginia, the largest data center concentration in the world — alongside the retirement of older generation. Whether new supply can be connected fast enough is now a first-order question for grid reliability, electricity prices, and the pace of digital infrastructure buildout.
The announcement is a progress marker rather than a finish line: clearing studies is a necessary step, but megawatts only matter once projects secure equipment, financing, and construction — stages the interconnection process does not control.
Why the Queue Became the Grid’s Chokepoint
Under the old regime, PJM studied interconnection requests one at a time in the order received. That design worked when a handful of large plants applied each year, but it collapsed under the modern development model, in which developers file many speculative requests — often for renewables and storage — and decide later which to build. Each withdrawal forced restudies of everyone behind it, compounding delays. The result was a backlog measured in years, and a paradox: enormous volumes of proposed generation on paper, with comparatively little of it reaching commercial operation.
The reformed process attacks this structurally. Projects are studied together in clusters, network upgrade costs are shared across the cluster rather than assigned by queue position, and developers must post deposits and demonstrate site control to stay in. “First-ready, first-served” replaces “first-in-line,” which changes developer incentives from claiming a place early to being genuinely prepared. This is a governance fix as much as an engineering one — and PJM’s announcement suggests the incentive redesign is doing its job.
The Collision With Data Center Demand
PJM’s territory includes the densest data center market on the planet, and the region’s load forecasts have swung from decades of flat demand to sustained growth. That reversal makes interconnection speed a commercial issue for the digital infrastructure industry, not just a utility concern: a data center campus is only as viable as the power that can reach it, and new generation stuck in study limbo tightens capacity markets and pushes up costs for every large power buyer.
For data center operators, colocation providers, and their customers, a functioning interconnection pipeline is upstream of everything — site selection, lease pricing, and expansion timelines. If PJM can convert its backlog into energized projects, it relieves pressure on the supply side of an equation that has recently been dominated by demand headlines. If it cannot, the alternatives — demand curtailment, delayed retirements of aging plants, or higher capacity prices — all carry costs that eventually land on tenants and end users.
From Cleared Studies to Steel in the Ground
A cleared study is not a power plant. Projects that emerge from PJM’s process with signed interconnection agreements still face equipment lead times — transformers and high-voltage gear remain constrained industry-wide — plus financing, permitting, and supply chain realities. Historically, a large share of queued projects never get built, so the headline metric that matters over time is commercial operation dates, not study completions.
It is also worth noting the source here: this is PJM’s own publication reporting on PJM’s own reform. That does not make the claim wrong — grid operators publish detailed queue statistics that independent analysts scrutinize closely — but a self-assessment titled “Delivers” should be read as a progress report from the institution being measured. The durable test is whether independent queue data shows sustained throughput across successive study cycles, and whether new entrants, not just legacy backlog projects, move through on predictable timelines.
Background
PJM Interconnection, headquartered in Pennsylvania, is the largest regional transmission organization in the United States, coordinating the grid and wholesale power markets from the Mid-Atlantic into the Midwest. Like other U.S. grid operators, PJM saw its interconnection queue swell dramatically through the early 2020s as renewable, storage, and gas projects applied faster than its serial study process could handle, prompting a FERC-approved overhaul in 2022 that shifted to clustered, readiness-based studies and a phased transition to work off the backlog.
The reform arrived just as PJM’s demand outlook inverted. After years of flat load, forecasts turned sharply upward on data center growth and electrification, while older coal and gas plants moved toward retirement — making the speed at which new resources can connect a central reliability and cost question for the region, and a closely watched variable for the digital infrastructure industry that depends on PJM power.
Montgomery County, Maryland, a large suburb just outside Washington, has stopped accepting building applications for new data centers for six months. Data centers are the huge warehouses of computers that run apps, online storage and artificial intelligence.
The surprise is that the pause also covers a project already proposed on the site of an old, shut-down power plant. Builders often like those sites because they are already wired into the electric grid.
Local leaders say they want rules on electricity, water and noise written before anything gets built.
On June 12, 2026, Montgomery County Executive Marc Elrich signed an executive order directing the county’s Department of Permitting Services to stop accepting, processing and considering permit applications for new data centers. Montgomery County announced that the order takes effect immediately and sets a six-month moratorium, which can end sooner if the County Council adopts permanent zoning rules for data centers.
The pause applies to projects already proposed, including a potential data center at the site of the decommissioned power plant in Dickerson, in the county’s western reaches along the Potomac River. Council Vice President Marilyn Balcombe and Councilmembers Will Jawando and Kristin Mink backed the order.
Executive Summary
Montgomery County has frozen data center permitting for six months so its County Council can write a legal framework for the industry. The county said the order responds to concerns about data centers’ energy consumption, water use for cooling, and noise near homes. It is a pause, not a ban: officials described it as time to set rules before applications move forward.
What makes the order consequential is its scope. Elrich said his approach differs from an earlier proposal by Council Member Glass that would have exempted the Dickerson site and let it keep moving through permitting. His order does not exempt it. A project on a retired power plant parcel, which is the kind of site developers typically prize for its existing grid ties, now waits in the same line as everything else.
For developers and investors, the signal is that in Montgomery County, a site’s power-plant legacy is not a substitute for local approval. The rules that emerge on clean energy, water, noise and labor will determine whether the county remains a practical option next to one of the world’s densest data center markets.
Why a Retired Power Plant Didn’t Earn a Head Start
For data center developers, a decommissioned power plant is often one of the most attractive parcels available. Such sites are usually already used for heavy industry, and they sit where high-voltage transmission lines once carried the plant’s output to the grid. That matters because the scarce input for today’s AI-driven data center buildout is electricity, not land. Connecting a large new electricity customer can take years, and a site with an existing grid footprint is widely seen as a way to shorten that wait.
Montgomery County’s order removes that advantage for Dickerson. Elrich explicitly contrasted his order with Council Member Glass’s earlier proposal, which exempted the Dickerson site. Councilmember Mink said a large data center is in the permitting process now and that the order covers it “and all others,” calling that an important distinction. Councilmember Jawando said the moratorium bill he introduced in May was the only one that covered the Dickerson project. The county’s elected leadership treated the site’s history as no reason to let it proceed ahead of the rules.
The reasoning is visible in the concerns officials named: grid strain, brownouts, water for cooling, noise, and watershed protection. An existing transmission connection addresses whether power can physically reach a site. It does not answer whether the county wants that load on its local system, where cooling water comes from, or how loud cooling equipment will be near homes. The Dickerson developer is the first party affected. The same logic applies to any developer or landowner that has valued retired generating sites on the assumption that local approval follows the grid connection. In Montgomery County, at least, it does not.
What Six Months Is Meant to Produce
The moratorium is scheduled to expire in six months, around mid-December 2026. It ends earlier if the County Council adopts Zoning Text Amendments, which are changes to the written zoning code that define where a use is allowed and under what conditions. In practice, the pause gives the Council a deadline. If permanent rules arrive first, the freeze lifts on them.
Officials have already sketched what they want those rules to cover. Jawando listed “clean energy, no subsidies, union labor, and a safe watershed.” Mink wants the County Noise Ordinance updated and watershed protections established. Climate Change Officer Sarah Kogel-Smucker said the goal is to align data center development with the county’s climate goals through best practices for clean energy and efficient cooling. Each of these would raise a project’s costs or narrow its design choices. Clean-energy requirements affect how a facility buys power. Water limits push operators toward cooling systems that use less water, which can mean more electricity. A no-subsidy stance removes the tax incentives many jurisdictions use to compete for these projects.
None of these positions has become law yet, and they will not all carry equal weight. How the Council balances them will decide whether Montgomery becomes a place where data centers can be built under strict conditions or one where the conditions make the economics hard to close. Balcombe framed the intent as the former: “The moratorium does not mean we stop; it means we work harder.”
A Pause on the Doorstep of Data Center Alley
Montgomery County sits across the Potomac River from Loudoun County, Virginia, whose Ashburn area is known as Data Center Alley and hosts one of the largest concentrations of data centers in the world. Maryland and Northern Virginia are both served by PJM Interconnection, the grid operator for much of the mid-Atlantic. That is why concerns about grid strain and brownouts carry weight on both sides of the river.
The order should not be read as more than it is. It is one county’s six-month pause, and it does not by itself redirect regional demand. What it does show is that a jurisdiction immediately adjacent to the industry’s busiest cluster has chosen to write rules before approving projects, including one on a site with an energy-industry past. Jawando cast the decision in national terms, saying communities across the country face the same choice. Developers looking for land near Northern Virginia’s network and power infrastructure now have one fewer county where timing is predictable.
Weighing the Claims on Both Sides
The order’s stated rationale includes serious claims, notably brownouts. Whether any single facility would contribute to them depends on its size and on the utility’s planning, and officials framed the risks in general terms rather than attaching load or water figures to the Dickerson project. The rules the Council writes will be more durable if they rest on measured impacts rather than on the general reputation of the industry.
The same scrutiny applies to the other side of the argument. Jawando’s description of “corporate promises of profits that may never come” is a political judgment, not a finding. Kogel-Smucker’s observation that data centers are “critical to our digital economy” is the counterweight. No jobs, tax revenue or investment figures for the Dickerson project were offered at the announcement to test either view. The six months are most useful if both the county and the developer put those numbers on the table.
Background
Montgomery County is a large suburban county bordering Washington, D.C., to the northwest, with its western edge on the Potomac River. Across the river lies Loudoun County, Virginia, home to Ashburn’s Data Center Alley, one of the largest concentrations of data centers anywhere. Data center demand across the region has grown with cloud computing and, more recently, artificial intelligence workloads, which require large amounts of electricity and cooling.
Montgomery County had been working toward data center rules before the order. Its Climate Change Officer co-led a community forum on data centers in February 2026, Council Member Glass had put forward a proposal that exempted the Dickerson site, and Councilmember Jawando introduced a moratorium bill in May that covered Dickerson. Elrich’s June 12 executive order paused permitting while the Council finishes that work.
Seattle’s city council voted unanimously on June 9 to temporarily stop new giant data centers from being built in the city. Data centers are warehouse-sized buildings packed with computers, and the biggest new ones run artificial intelligence.
Four companies had asked the city’s electric utility to power five of them. Together, those five could draw as much electricity as about 300,000 homes.
Council members said their main worry is that everyone else’s power bills could rise to cover the cost. The pause gives the city time to study bills, water use and pollution before it makes any permanent decision.
On June 9, 2026, the Seattle City Council unanimously adopted two measures aimed at large data centers, the council announced on its official blog. Amended Council Bill 121214, sponsored by Councilmember Eddie Lin and Council President Joy Hollingsworth, places an emergency, temporary freeze on siting new data centers while the city conducts impact studies. The freeze covers facilities used primarily for storing and processing digital data that have more than 20 megavolt-amperes (MVA) of power capacity and require uninterruptible power. It can be extended by six months if necessary.
A companion measure, amended Resolution 32204 sponsored by Councilmember Debora Juarez, sets a policy framework and directs city departments and the Mayor’s Office to analyze how such facilities affect grid capacity, water use, utility rates, land use, local jobs and public health. The votes followed reports in April that four companies had approached Seattle City Light, the city’s electric utility, about five large data centers with a combined maximum demand of 369 megawatts. Mayor Katie B. Wilson said the mayor’s office looks forward to signing the ordinance, which takes effect immediately under its emergency designation. A public hearing is required within 60 days.
Executive Summary
Seattle has paused new large data centers after four companies sought 369 megawatts of capacity for five facilities. By the council’s own comparison, that is enough electricity to power about 300,000 homes. The ordinance uses a 20 MVA threshold, which targets large, always-on computing facilities rather than small server rooms. It takes effect immediately, and the council says it can be extended by six months.
The notable part is the reason. Every official quoted — the two sponsors, the council president and the mayor — cited utility rates or ratepayers. Environmental and water concerns were also named, but the shared argument was cost. The question the council put to developers is not whether the grid can physically deliver the power. It is who pays to deliver it.
For AI infrastructure developers, the lesson reaches beyond Seattle. Where the people who govern a utility answer to the people who pay its bills, a large new load has to make a persuasive case to those ratepayers. A service request alone may not be enough.
The Argument That Carried the Vote Was the Power Bill
The measures passed 9-0, and the officials behind them made a consistent case. Councilmember Lin said large AI data centers are “driving up utility costs for residents and small businesses” and that “Seattleites should not be subsidizing record profits of large corporations from the AI boom.” Council President Hollingsworth said growth must not come “at the expense of residents and ratepayers.” Mayor Wilson cited “the potential impacts of large-load data centers on utility rates.” Air, water and noise concerns appear alongside, but rates are the thread that runs through every statement.
Here is the mechanism. When a utility has to add substations, transmission lines or new power supply to serve a single very large customer, its rate design decides who pays. If those costs are spread across the whole customer base, households and small businesses carry part of them. If the tariff assigns them to the new load, the developer carries them. Resolution 32204 directs the city to study exactly these questions, grid capacity and utility rates, before any permanent rules are set. In Seattle the utility is City Light. It sits under the same elected council that voted the pause, and Juarez chairs the committee that oversees it. The people deciding whether 369 megawatts gets connected are directly accountable to the people who would share the bill.
That is why this matters for AI infrastructure. A developer can secure land, chips and a utility service request and still be stopped at the point where the grid-upgrade bill meets ratepayers. The council has not yet shown Seattle-specific evidence that these five projects would raise rates; producing that evidence is the stated purpose of the studies. The vote still establishes the test. A large AI load in this city will have to show residents it will not cost them money. Developers who can answer that question credibly, for example by paying their own grid costs, will be better placed than those who cannot.
What 369 Megawatts Means for a City Grid
The five proposed facilities had a combined maximum demand of 369 megawatts, about 74 megawatts each on average. The actual split among them has not been disclosed. Maximum demand is peak draw, not average use. However, large computing facilities tend to run close to their peak around the clock, which makes them attractive customers for utility revenue and demanding ones for utility planning. The council’s comparison to roughly 300,000 homes shows the scale: this is a city-sized block of new demand, requested by four companies in a single round.
The 20 MVA threshold sets the boundary. Megavolt-amperes measure electrical capacity and, for data center equipment, are close to megawatts. The definition also requires uninterruptible power, meaning battery and backup systems that keep servers running through outages. Together these criteria capture purpose-built, high-density computing sites while leaving smaller office server rooms outside the definition.
Colocation Stays, Mega-Sites Wait
Lin drew an explicit line between “mega AI data centers” and the city’s smaller colocation facilities. Colocation facilities are shared buildings where many organizations rent space for their servers, and Lin said Seattle’s support 911 call centers, municipal operations, hospitals, universities and cancer research. The freeze applies to new siting, so existing facilities keep operating. The open question for colocation operators is how the 20 MVA line will apply to any expansion plans.
Where the demand goes next is uncertain. Lin spoke of developing safeguards “locally and regionally,” which suggests the city expects the issue to extend beyond its borders. Developers could wait out the studies, redesign projects to meet whatever conditions emerge, or pursue sites elsewhere in the region. None has said publicly which it intends.
What the Pause Does and Does Not Establish
Juarez described the measure as a pause for accountability and said it “does not stop AI or data centers.” It is temporary, it requires a public hearing within 60 days, and permanent rules depend on studies that have not yet been done. The council cited “tens of thousands” of residents raising concerns and pointed to rate increases elsewhere in the country. Both are statements of position; the studies are what will test them locally. The developers’ side is equally unsubstantiated so far. The four companies have not publicly set out what they would pay for, what jobs or tax revenue they would bring, or how they would limit the impact on existing customers.
This is one city’s decision, and it should not be read as a nationwide trend. It is notable because Seattle is a major West Coast technology center, and because the council framed the decision in cost terms rather than opposition to the technology itself. That framing can be answered with evidence, which gives both sides a clear question to argue over.
Background
Seattle City Light is the city’s electric utility, and the elected City Council oversees it through a committee currently chaired by Councilmember Debora Juarez. That structure puts decisions about serving very large new customers in the hands of officials who answer directly to local voters and ratepayers.
Large data centers, especially those built for artificial intelligence, need continuous, high-capacity power, and they have become a growing source of new electricity demand for utilities across the United States. Seattle’s action came two months after reports that four companies had approached City Light about five facilities. Seattle’s decision is one of the more prominent local responses to that growth, because the city is a major West Coast technology center.
Bloomberg Government reported on June 8, 2026 that lawmakers are floating solutions to the rising power costs associated with data centers — a signal that the electricity-bill impact of the computing buildout has moved from utility commission dockets into the legislative arena. The report’s headline frames the issue squarely as a cost problem in search of a policy fix.
The report arrives amid an unprecedented wave of data center construction driven by artificial intelligence workloads, which has made large computing facilities one of the fastest-growing sources of new electricity demand in the United States.
Executive Summary
The core news, per Bloomberg Government’s June 8 report, is that the cost side of the data center boom — specifically, who pays for the power infrastructure these facilities require — is now attracting active legislative attention, with lawmakers proposing potential solutions rather than merely holding hearings. The report itself is headline-level; the specific proposals, sponsors, and legislative vehicles are not detailed in the material available to us, and we flag that below.
Why it matters: for the past two years, the fight over data center power costs has largely played out state by state, before public utility commissions — the regulators who approve electricity rates. When lawmakers start floating statutory fixes, the rules of the game can change faster and more broadly. Rate design — the technical framework that decides how a utility’s costs are divided among households, businesses, and large industrial customers — is the lever most often discussed, because it determines whether a new transmission line or power plant built substantially to serve a data center is paid for by that data center or spread across everyone’s bills.
For data center developers, utilities, and the customers signing multi-hundred-megawatt capacity deals, this is policy risk in its early, formative stage — the moment when engagement matters most and outcomes are least predictable.
Why Electricity Bills Became a Data Center Story
Data centers concentrate enormous electrical demand in single locations: a large AI campus can draw as much power as a mid-sized city. Serving that demand often requires new generation, new transmission lines, and substation upgrades. Under traditional utility rate-making, much of that infrastructure cost goes into the utility’s general ‘rate base’ — the pool of investment recovered from all customers over decades. When the new demand comes overwhelmingly from one class of customer, other ratepayers can end up subsidizing infrastructure they did not ask for and do not use.
That cost-shifting question is what turns an infrastructure story into a kitchen-table story. Household electricity bills are politically salient in a way that interconnection queues are not, and the Bloomberg Government headline — lawmakers floating solutions to data center power costs — suggests elected officials now see both a genuine allocation problem and a constituency that cares about it. It is worth being even-handed here: data centers also bring tax revenue, jobs during construction, and in some regions have funded grid upgrades that benefit all users. The policy question is not whether data centers are good or bad, but whether the current rules assign their costs accurately.
The Rate-Design Toolkit Lawmakers Are Reaching For
Although the report does not specify which solutions are on the table, the toolkit in active discussion across the industry is well established. It includes creating dedicated tariff classes for very large loads, so data centers pay rates reflecting their actual cost to serve; minimum-take or long-term contract requirements, which protect other customers if a data center closes or scales back before its infrastructure is paid off; and ‘bring your own power’ frameworks that push hyperscale customers toward self-supplied or co-located generation. Each approach shifts risk between the data center customer, the utility’s shareholders, and the general ratepayer base — and each has trade-offs in speed, cost, and legal durability.
The federal-versus-state dimension matters too. Retail rate design is traditionally state territory, while interstate transmission costs and wholesale market rules sit with federal regulators. Legislative proposals could target either layer, and the editorial significance of lawmakers entering the fray is that statutes can override or standardize what has so far been a patchwork of case-by-case commission rulings.
Policy Risk Meets the AI Buildout
For the data center industry, the emergence of legislative interest is a double-edged development. On one hand, clear statutory rules could reduce uncertainty: developers currently face a different rate fight in every state, and a predictable large-load tariff framework can actually accelerate siting decisions. On the other hand, rules written in a politically charged environment — where rising bills are the headline — could impose costs, contract terms, or delays that change project economics, particularly for speculative capacity built ahead of signed tenants.
Utilities sit in the middle. Load growth is the best news the regulated utility sector has had in decades, but only if regulators and legislators let them recover the associated investment without triggering a ratepayer backlash. Expect utilities to support frameworks that lock in long-term commitments from data center customers, and expect hyperscale buyers with strong credit to accept them in exchange for speed. The parties most exposed are smaller developers and enterprises without the balance sheet to sign decade-long minimum-payment contracts. For everyone in the buildout, the practical takeaway is that power procurement is no longer just an engineering and price question — it is now a regulatory and legislative one.
Background
Electricity demand from data centers has grown rapidly since the generative-AI boom began in late 2022, ending roughly two decades of flat U.S. power demand and making computing facilities one of the largest sources of new load on the grid. Individual AI campuses now request capacity measured in the hundreds of megawatts — comparable to small cities — concentrated in hubs such as Northern Virginia, Texas, and the Midwest.
The cost question has followed the demand. Since 2024, state utility commissions have fielded a growing number of cases over how to charge very large loads, and several utilities have proposed dedicated data center tariffs. Bloomberg Government, the source of this report, is a policy-focused news service covering Congress and federal agencies, which itself suggests the issue has reached the national legislative agenda rather than remaining purely a state regulatory matter.
The Wall Street Journal reported on June 6, 2026 that Ireland — one of Europe’s most important data center hubs — is telling technology companies seeking new data center capacity that they should bring their own power generation rather than rely on the national grid. The report frames the stance as a response to years of mounting strain between the country’s booming digital infrastructure sector and an electricity system struggling to keep pace.
Executive Summary
According to the Journal’s reporting, Irish authorities are effectively shifting the burden of powering new data centers onto the companies that build them. Instead of queuing for grid connections that may not materialize for years, hyperscalers — the largest cloud and internet platforms, such as those operating massive server campuses — are being pointed toward on-site or self-procured generation as the price of admission.
Why it matters: Ireland has long punched far above its weight in European data center capacity, and its grid has been under visible stress as a result. If the sovereign host of one of the continent’s densest cloud clusters is now telling its largest customers to power themselves, that is a signal moment for every grid-constrained market — from Dublin to Northern Virginia to Singapore. The economics, siting logic, and competitive dynamics of data center development all change when the utility is no longer assumed to show up.
How Ireland Became the Test Case for Grid Saturation
Ireland’s predicament is not new — it is the culmination of a decade-long collision between two national success stories. Dublin became a preferred European landing zone for American cloud providers, drawn by tax policy, connectivity, a skilled workforce, and EU market access. But data centers are extraordinarily power-dense tenants: official Irish statistics have shown them consuming roughly a fifth of the country’s metered electricity in recent years, a share without parallel among developed economies. The grid operator, EirGrid, had already moved years earlier to restrict new data center connections in the Dublin region, citing capacity and system-stability concerns.
Seen against that backdrop, a “bring your own power” posture is less a sudden policy lurch than the logical end state of a queue that stopped moving. When a grid cannot absorb new large loads without threatening reliability for households and other industry, the choices narrow to three: build transmission and generation faster (slow and politically hard), ration connections (which Ireland has effectively done), or push the load to self-supply. Ireland now appears to be leaning into the third option.
The Economics of Powering Yourself
Self-generation transforms the data center cost model. A grid connection socializes enormous capital costs — power plants, transmission lines, system balancing — across all ratepayers. Bringing your own power means the developer finances generation capacity itself: on-site gas turbines or engines, batteries, contracted private-wire renewables, or some hybrid. That raises upfront capital expenditure substantially and adds fuel-supply, permitting, and emissions obligations that a simple utility contract never carried.
For hyperscalers, this is expensive but survivable — the largest cloud companies have the balance sheets, the energy-procurement teams, and increasingly the appetite to act as their own utilities, as the global wave of data-center-adjacent generation deals demonstrates. For smaller colocation operators and enterprises, the calculus is harsher: self-generation at scale requires expertise and capital that mid-tier players often lack. The likely effect is consolidation of new Irish capacity in the hands of the very largest operators, and a widening gap between markets where power is a utility service and markets where it is a competitive weapon.
Winners, Losers, and the Emissions Question
The clearest near-term beneficiaries are the suppliers of behind-the-meter power: gas turbine and reciprocating-engine manufacturers, battery storage integrators, and developers of private-wire renewable projects, all of which face a customer newly compelled to buy. Grid ratepayers arguably benefit too, since new digital load stops competing with homes and factories for constrained supply. The losers are developers whose Irish pipelines were premised on eventual grid connections, and potentially Ireland’s own climate accounting — if “your own power” means on-site fossil generation, national emissions targets absorb the impact even as grid stress eases.
That tension deserves scrutiny in both directions. Critics of data center growth will note that self-generation can amount to distributed gas plants by another name; industry advocates will counter that hyperscalers have been among the largest corporate buyers of renewable energy in Europe. Both claims can be true, and the honest answer depends on implementation details — fuel types, run hours, and whether storage and renewables are mandated alongside thermal capacity — that the reporting available at publication does not settle.
A Template Other Grids Are Watching
Ireland is not alone; it is simply early. Regulators and utilities in other saturated hubs — the Amsterdam region, Singapore, and parts of the United States where interconnection queues stretch years — have all experimented with pauses, caps, or conditions on data center growth. What makes the Irish stance notable is its directness: rather than saying “no,” it says “yes, if you power it yourself.” That formulation lets a small country keep courting digital investment without asking its citizens to underwrite the electricity. Expect other grid-constrained jurisdictions to study it closely, and expect site-selection teams to treat credible self-generation plans as a standard part of the pitch rather than an exotic fallback. In the AI era, the scarce input is no longer land or fiber — it is firm power, and whoever can bring their own will build first.
Background
Ireland became one of Europe’s foremost data center markets over the past two decades, with Dublin serving as a primary European hub for major American cloud and internet companies. That success came with an unusual burden: official Irish statistics have shown data centers consuming on the order of one-fifth of the country’s metered electricity — a share far higher than in most developed economies — prompting public debate over grid reliability, climate targets, and who should bear the cost of digital growth.
Grid operator EirGrid responded years before this report by constraining new data center connections in the Dublin region, and national policy has since wrestled with how to reconcile continued digital investment with electricity system limits. The reported ‘bring your own power’ stance represents the sharpest articulation yet of where that debate has landed.
PJM Interconnection’s independent market monitor has concluded that AI-driven data center growth is reshaping the power markets it oversees, according to a June 2026 report from Data Center Knowledge. PJM operates the largest wholesale electricity market in the United States, coordinating the grid across 13 states and the District of Columbia for roughly 65 million people.
The finding matters because it comes from the market’s designated referee rather than from a vendor or developer: the monitor exists precisely to assess, without commercial interest, whether the market is functioning competitively — and it is now attributing a fundamental shift in that market to data center load.
Executive Summary
The headline is short but consequential: PJM’s market monitor — the independent body charged with policing competition in the nation’s largest electricity market — has identified AI data center growth as a force actively reshaping that market. For two decades, US grid planners worked in a world of essentially flat electricity demand, where efficiency gains offset economic growth. That assumption has broken, and PJM, whose footprint includes Northern Virginia’s Data Center Alley, is where it broke first and hardest.
When the market monitor says demand growth is ‘reshaping’ the market, it is signaling that data center load is no longer a forecasting footnote but a structural driver of prices, planning, and investment decisions. PJM’s recent capacity auctions — the mechanism that pays generators to be available years in advance — have produced record-setting results widely attributed in part to surging demand forecasts, and those costs flow through utility bills to every customer class.
For the industry, an independent confirmation of this shift cuts both ways. It validates the scale of the AI infrastructure build-out that developers have been describing. It also raises the stakes for how that growth is managed: who pays for new transmission and generation, how speculative interconnection requests are filtered from real ones, and whether supply can be added fast enough to keep reliability and affordability intact.
From Forecasting Footnote to Structural Force
The most important word in this story is ‘reshaping.’ Grid operators revise load forecasts constantly; what they rarely do is declare that the character of the market itself has changed. PJM’s service territory covers all or part of 13 states and DC, and it includes the densest concentration of data centers on the planet in Northern Virginia. When demand there grows, it does not simply add megawatts — it changes which power plants run, where transmission congestion appears, and how much capacity the market must procure years ahead.
An assessment from the independent market monitor carries different weight than one from PJM itself or from data center developers. The monitor’s role — in PJM’s case performed by an outside firm — is to evaluate market competitiveness and flag structural problems without a commercial stake in the outcome. Its reports are read closely by federal and state regulators. Framing AI data center growth as market-reshaping effectively puts the issue on the regulatory agenda, not just the industry conference circuit.
Capacity Markets, and Who Ends Up Paying
PJM runs a capacity market: generators are paid not only for the electricity they produce but for committing to be available during future peak periods. When demand forecasts rise sharply — as data center growth has caused them to — the market must procure more capacity against a supply base that has been shrinking as older coal and gas plants retire. Basic economics follows: tighter supply against higher demand means higher clearing prices, and PJM’s recent auctions have set records that state officials and consumer advocates have publicly protested.
Capacity costs are socialized across ratepayers, which is where the political friction originates. Households and small businesses in PJM states are seeing bill increases driven partly by demand they did not create. Expect the policy debate to center on cost allocation: large-load tariffs that require data centers to underwrite the infrastructure they trigger, minimum take-or-pay commitments, and rules for co-located or behind-the-meter arrangements where a data center pairs directly with a power plant. How those rules land will materially affect data center project economics in the region.
Winners, Losers, and the Speculation Problem
The near-term winners are clear: owners of existing generation in PJM, whose assets have been revalued by scarcity, and transmission developers with projects in flight. Data center operators with secured power — signed interconnection agreements and energized substations — hold an asset that is increasingly the scarcest input in the industry. The squeezed parties are late-arriving developers facing multi-year waits for grid connection, and energy-intensive industries competing for the same electrons.
The unresolved analytical problem is demand-forecast quality. It is widely acknowledged in the industry that developers file interconnection requests with multiple utilities for the same prospective project, meaning some portion of announced demand is duplicative or speculative. If markets procure capacity against inflated forecasts, ratepayers overpay; if forecasts are discounted too aggressively and the load shows up, reliability suffers. Distinguishing real load from phantom load is arguably the central technical challenge the monitor’s finding implies — and one the industry itself has an interest in helping solve, since credibility with regulators depends on it.
The Supply Response Is the Whole Game
High prices are a symptom; the cure is new supply, and here timelines diverge badly. A hyperscale data center can be built in roughly two to three years. New gas turbines face multi-year equipment backlogs, nuclear operates on decade scales, and renewables plus storage — often the fastest option — face their own interconnection queues and siting fights. Transmission, the connective tissue, is slower still.
That mismatch, more than any single auction result, is what ‘reshaping the market’ means in practice. It pushes data center operators toward creative structures: siting near existing generation, contracting directly for new-build power, investing in on-site generation, and accepting flexibility obligations — curtailing or shifting load during grid stress — in exchange for faster connection. For infrastructure providers, grid access has moved from a line item in site selection to the decisive variable.
Background
PJM traces its roots to a 1927 power pool between Pennsylvania and New Jersey utilities and has grown into the largest regional transmission organization in the US, dispatching power across 13 states and DC. An independent market monitor oversees its wholesale markets and publishes regular assessments of their competitiveness and health. For most of the 2000s and 2010s, PJM — like the rest of the US grid — planned around flat demand, as efficiency gains offset economic growth.
That era ended as cloud and then AI data center construction accelerated, concentrated in PJM territory around Northern Virginia. The region’s recent capacity auctions have produced record-setting prices that drew objections from state officials and consumer advocates, putting data center load growth at the center of an escalating debate over grid reliability, cost allocation, and how fast new generation and transmission can be built.
