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Category: Power Infrastructure

  • Wisconsin Regulators Say Data Centers Must Pay the Full Cost of Their Power

    Wisconsin Regulators Say Data Centers Must Pay the Full Cost of Their Power

    Wisconsin utility regulators have taken the position that data centers must cover the full cost of the energy infrastructure their facilities require, according to an April 23, 2026 report from Wisconsin Watch. The stance addresses the central fight of the data center boom: whether households and small businesses end up subsidizing the power plants, substations, and transmission lines built to serve a handful of very large computing campuses.

    The report’s headline frames the position as a directive — data centers, not the general body of ratepayers, bear the cost of their own demand. The underlying details of the proceeding, and how “full cost” will be defined and enforced, are not spelled out in the source material available to us.

    Executive Summary

    As reported by Wisconsin Watch on April 23, 2026, Wisconsin regulators have signaled that data centers seeking grid connections in the state must bear the full cost of their energy needs. In utility ratemaking terms, this is a cost-allocation principle: when a single customer’s demand forces the construction of new generation or grid capacity, that customer — rather than the shared pool of ratepayers — should pay for it.

    It matters because Wisconsin has become one of the Midwest’s most active data center markets, anchored by Microsoft’s multi-billion-dollar campus in Mount Pleasant and a pipeline of other announced projects. Each hyperscale campus can demand hundreds of megawatts — on the scale of a small city — and someone must pay for the infrastructure that serves it.

    The bigger significance is precedential. Regulators in many states are wrestling with the same question, and several utilities have proposed special tariffs for very large customers. A clear “you demand it, you pay for it” stance from a state actively courting data center investment offers a template others can copy — and a test of whether such terms slow investment or simply formalize what serious developers already expect to pay.

    The Cost-Allocation Fight Behind Every Data Center Boom

    Regulated utilities recover the cost of new infrastructure through rates approved by state commissions, and those costs are typically spread across all customer classes. That model works when growth is broad and gradual. It strains when one customer class — hyperscale data centers — arrives suddenly and demands capacity additions measured in gigawatts. If a utility builds a power plant or transmission line primarily for one campus and the project later shrinks or cancels, the leftover cost, known as a stranded asset, can land on everyone else’s bills.

    That risk is why “who pays” has become the defining regulatory question of the AI infrastructure cycle. Consumer advocates warn of cross-subsidization — ordinary ratepayers underwriting corporate compute. Utilities and developers counter that large loads can spread fixed grid costs over more sales and put downward pressure on rates if structured well. The Wisconsin position, as reported, comes down firmly on the side of insulating the general ratepayer.

    Why Wisconsin Is a Bellwether

    Wisconsin is not a legacy data center hub like Northern Virginia, which makes its posture instructive: it is a state actively attracting new hyperscale investment while setting terms at the front end rather than repairing cost shifts after the fact. Microsoft’s Mount Pleasant development, announced in 2024, put the state on the hyperscale map, and Wisconsin utilities have since proposed rate structures aimed at very large customers — typically featuring long-term contract commitments and minimum payments so that infrastructure built for a data center is paid for by that data center even if its plans change.

    A regulatory endorsement of full cost responsibility strengthens the utilities’ hand in structuring those deals and gives economic developers a cleaner pitch: growth without a ratepayer backlash. States competing for the same projects will watch whether Wisconsin’s pipeline holds up under these terms.

    What “Full Cost” Could Mean in Practice

    The phrase sounds simple; the implementation is not. Full cost responsibility can be enforced through several mechanisms: dedicated rate classes for very large loads, up-front contributions toward interconnection and grid upgrades, minimum demand charges that guarantee revenue regardless of actual usage, contract terms of a decade or more, and exit fees or collateral that protect against a project walking away mid-build. Each mechanism allocates a different slice of risk between the developer, the utility, and its shareholders.

    The definitional boundaries matter enormously. Does “full cost” cover only the local wires and substations, or a share of new generation? Does it apply to grandfathered projects or only new applicants? A principle announced by regulators becomes real only when it is written into approved tariffs and signed contracts, and the reported material does not yet show that level of detail.

    Winners, Losers, and the National Template

    Residential and small-business ratepayers are the clearest intended beneficiaries — the policy exists to keep their bills from absorbing data center-driven costs. Well-capitalized hyperscalers can generally live with full-cost terms; they already sign long-term commitments in other markets, and predictable rules can be preferable to political uncertainty. The squeeze falls on thinner-capitalized or speculative projects, which lose the ability to socialize their risk. Utilities get growth with less rate-case blowback, though they take on more counterparty risk concentrated in a few very large contracts.

    If Wisconsin’s stance holds and investment continues anyway, the template argument writes itself: states can welcome AI infrastructure without asking captive ratepayers to underwrite it. If projects visibly divert to states with softer terms, expect a counter-narrative that strict cost allocation costs jobs and tax base. Either outcome will be cited in commission dockets across the country.

    Background

    Wisconsin’s arrival as a data center state dates largely to 2024, when Microsoft announced a multi-billion-dollar campus in Mount Pleasant, southeast Wisconsin — on land once slated for the Foxconn manufacturing project — followed by further large-load proposals elsewhere in the state. That growth pushed Wisconsin utilities to propose rate structures for very large customers designed to ensure new infrastructure is paid for by the customers who require it.

    Nationally, the surge in AI-driven electricity demand has made cost allocation the central issue in utility regulation. State commissions, consumer advocates, utilities, and hyperscale developers are negotiating who bears the cost — and the risk — of the biggest grid build-out in decades, and headline positions like Wisconsin’s are being watched as potential templates.

    Source: Wisconsin regulators: Data centers must cover full cost of their energy needs — Wisconsin Watch report, April 23, 2026, on Wisconsin regulators’ position that data centers must bear the full cost of the energy infrastructure they require.

  • ABB Takes UPS to 34.5kV to Cut AI Data Center Losses

    ABB Takes UPS to 34.5kV to Cut AI Data Center Losses

    ABB has introduced a 34.5kV version of its HiPerGuard medium-voltage uninterruptible power supply, announced on 22 April 2026. The company positions the product as connecting directly to a medium-voltage grid feed, eliminating conversion steps between the utility connection and the data center’s power train, and says the result is lower power costs for AI data centers.

    At 34.5kV, the unit sits at the top of the medium-voltage distribution class commonly used by North American utilities. The announcement is a product-capability disclosure rather than a customer deployment: the material published alongside the headline does not name sites, buyers, delivery dates or measured efficiency gains.

    Executive Summary

    An uninterruptible power supply is the equipment that keeps a data center’s servers running through a grid disturbance, bridging the seconds or minutes until generators take over. Conventionally, that equipment lives at low voltage — typically a few hundred volts — which means utility power arriving at medium voltage must first be stepped down through transformers, then protected, then distributed. Every one of those stages costs a percentage of the power passing through it, and each percentage becomes heat that must itself be cooled.

    ABB’s claim with the 34.5kV HiPerGuard is that the UPS can sit further upstream, taking the medium-voltage feed directly and removing conversion stages from the chain. The commercial argument is straightforward: fewer stages mean fewer losses, less transformer and switchgear capacity to buy, and less floor space consumed by electrical rooms that could otherwise hold revenue-generating IT equipment.

    The timing matters more than the voltage number. AI training and inference racks have moved from tens of kilowatts to the hundreds, with megawatt-scale racks on vendor roadmaps. At those densities the electrical distribution system, not the building shell, becomes the constraint. Medium-voltage UPS is one of several architectural responses to that constraint — and this announcement is a claim about a direction of travel that the released material does not yet quantify.

    Voltage Is the New Density Lever

    Power density in data centers has historically been solved by moving air and water more cleverly. That era is ending. When a single rack draws hundreds of kilowatts, the limiting factor shifts to how much current the distribution system can carry without unmanageable conductor sizes, losses and fault energy. Physics is unhelpful here: for a given amount of power, halving current requires doubling voltage, and copper cost and resistive loss scale with current, not with power.

    Raising the voltage at which protected power is handled is therefore one of the few structural levers available. Doing it at the UPS means the medium-voltage feed can travel deeper into the facility before being stepped down close to the load, shortening the low-voltage runs that dominate conductor spend. It also compresses the equipment chain: each transformation stage carries its own footprint, maintenance regime, failure modes and efficiency penalty. Removing stages removes all four at once.

    The counterpoint worth stating plainly is that this is a re-architecture, not a component swap. Medium-voltage equipment brings different clearance requirements, different arc-flash considerations, different qualification standards for the technicians who work on it, and a smaller pool of contractors able to commission it. Operators who adopt it are trading one set of engineering problems for another, and the trade only pays at scale.

    Where the Savings Actually Come From

    The headline frames the benefit as lower power costs. In a data center’s cost structure, electrical losses are compounded rather than linear: a watt lost in a transformer or rectifier is a watt bought from the utility and also a watt of heat that the cooling plant must remove, at further energy cost. Small efficiency percentages at the front of the power chain therefore multiply through the operating budget over a facility life measured in decades.

    The capital side may matter as much. Eliminating conversion stages means fewer step-down transformers, less associated switchgear, and less electrical room area — space that, in a market where construction timelines and grid connections are the binding constraints, converts directly into deployable IT capacity per site. For operators who cannot get more megawatts from their utility, extracting more usable compute from the megawatts already contracted is the highest-value optimization available.

    None of that is quantified in the material accompanying this announcement. There is no published efficiency figure, no comparison baseline, no total-cost-of-ownership model and no pricing. The mechanism ABB describes is sound engineering and widely understood in the industry; the specific magnitude of the benefit is, on the evidence released so far, an assertion rather than a demonstrated result. Buyers should treat it accordingly and ask for the numbers.

    A Crowded Answer to a Real Problem

    ABB is not alone in reading the AI power problem this way. Medium-voltage UPS lines, solid-state transformer research, and the broader industry push toward higher-voltage direct-current distribution inside the rack are all attacking the same bottleneck from different points in the chain. Chip and system vendors have been pushing rack-level power architectures upward in voltage for similar reasons. These approaches are complementary rather than mutually exclusive — a facility could plausibly take medium voltage deep into the hall and then distribute at high-voltage DC to the racks.

    The likely winners are hyperscale and large colocation operators building new capacity, where greenfield design allows the electrical architecture to be chosen rather than retrofitted, and where volume justifies training staff on medium-voltage practice. The likely losers are smaller enterprise sites and retrofit projects, which carry the complexity without the scale to amortize it. For ABB, the strategic value is defending a position in the electrification supply chain against competitors selling into the same buildings.

    The risk to watch is supply chain rather than technology. Medium-voltage switchgear, transformers and related equipment have been in constrained supply across the electrical industry, with lead times that already shape data center schedules. A product that reduces the count of such components could ease that pressure; one that simply relocates demand to a differently scarce component would not. The announcement does not address lead times or manufacturing capacity.

    Background

    ABB is a long-established electrification and automation supplier whose portfolio spans switchgear, transformers, drives and power protection. Its HiPerGuard line is a medium-voltage UPS family aimed at large industrial and data center loads, positioned against the conventional approach of stepping utility power down to low voltage before it reaches protection equipment.

    The market context is the rapid escalation of data center power requirements driven by AI workloads. As rack densities climb, operators face constrained utility connections, long grid interconnection queues and shortages of electrical equipment. That has pushed power architecture — historically a settled part of data center design — back into active competition among vendors, with voltage levels, conversion topologies and distribution schemes all under reconsideration.

    Source: New 34.5kV HiPerGuard UPS: direct grid connection cuts AI data center power costs – ABB — ABB’s 22 April 2026 announcement of a 34.5kV medium-voltage UPS positioned to remove conversion stages between the grid and AI data center loads.

  • MISO Forecasts 35% Load Growth by 2035 as Data Centers Reshape the Grid

    MISO Forecasts 35% Load Growth by 2035 as Data Centers Reshape the Grid

    The Midcontinent Independent System Operator (MISO) — the grid operator coordinating electricity across a footprint spanning 15 U.S. states and the Canadian province of Manitoba — expects electric load to jump roughly 35% by 2035, according to an April 2026 report from Utility Dive. The primary driver named in the forecast is data center growth.

    A 35% increase over roughly a decade represents a dramatic break from the era of essentially flat U.S. electricity demand that prevailed from the late 2000s through the early 2020s, and it puts one of the largest grid operators in North America on record quantifying the scale of the AI-and-cloud buildout.

    Executive Summary

    MISO’s forecast is a planning document, not a press release from a company selling something — which makes it one of the more consequential data points in the ongoing debate over how much electricity the data center boom will actually consume. Regional transmission organizations (RTOs) like MISO exist to keep supply and demand balanced in real time and to plan the wires and generation needed years ahead. When an RTO raises its ten-year demand outlook by more than a third, that number flows directly into transmission planning, capacity auctions, and the resource plans of dozens of utilities.

    The significance is twofold. First, it validates what individual utilities across the Midwest and Gulf South have been reporting piecemeal: hyperscale data center projects are arriving in interconnection queues at a pace with no modern precedent. Second, it sets up a decade of hard trade-offs. Meeting 35% growth requires new generation, new transmission, and new large-load interconnection rules — all on timelines that historically run slower than the two-to-three-year construction schedule of a data center campus.

    For the infrastructure industry, the headline number is both an opportunity signal and a warning: the grid is now the binding constraint on digital infrastructure growth, and the regions that solve power delivery fastest will win the next wave of siting decisions.

    The End of Flat Demand Is Now Official Planning Doctrine

    For roughly fifteen years, U.S. grid planners could assume that efficiency gains — LED lighting, better HVAC, industrial offshoring — would offset economic growth, keeping total electricity demand nearly flat. That assumption underpinned everything from utility rate cases to power plant retirement schedules. A 35% load-growth forecast from MISO formally retires it for one of the largest grid footprints in North America.

    What makes an RTO forecast different from a consultant’s projection is accountability: MISO must plan transmission and resource adequacy against this number. If the forecast is right and the buildout lags, the result is capacity shortfalls and price spikes. If the forecast is wrong and infrastructure is overbuilt, ratepayers carry stranded costs. Either error is expensive, which is why the assumptions behind the number — how much announced data center load actually materializes — deserve as much scrutiny as the number itself.

    Data Centers as the Marginal Buyer of Power

    A data center is, from the grid’s perspective, an unusual customer: it demands large blocks of power (often hundreds of megawatts per campus), runs at high utilization around the clock, and wants to connect years faster than traditional industrial load. When such customers become the dominant source of demand growth, they effectively set the terms of grid expansion — and grid operators, utilities, and regulators are still working out who pays for the upgrades those connections require.

    The economics cut in several directions. Utilities in MISO territory gain a growth story they have not had in a generation, which supports investment in wires and generation. Existing ratepayers face the risk of subsidizing infrastructure built for loads that may not fully arrive — a concern regulators in several states are already addressing through special large-load tariffs and financial-commitment requirements. Data center developers, meanwhile, face the reality that power availability, not land or fiber, now determines where and when they can build.

    Winners, Losers, and the Speed Mismatch

    The core tension in a 35%-by-2035 scenario is timing. Gas turbines face multi-year order backlogs, new nuclear operates on decade-plus horizons, and large transmission projects routinely take seven to ten years from planning to energization. Data center campuses go from groundbreaking to load in two or three. That mismatch favors whoever can bridge it: developers with early interconnection positions, utilities with spare capacity or fast-track large-load processes, suppliers of grid equipment, and operators pursuing on-site or co-located generation.

    It also raises competitive stakes between regions. MISO’s footprint — stretching from the upper Midwest to the Gulf Coast — competes with PJM, ERCOT, and the Southeast for hyperscale siting. A credible, well-executed plan to serve 35% more load is itself an economic-development asset; a forecast without matching buildout is a queue of frustrated customers who will site elsewhere.

    Forecast Versus Reality: The Phantom Load Question

    Every load forecast in the current environment must grapple with duplicate and speculative requests. Developers commonly file interconnection requests in multiple jurisdictions for the same project, and some announced campuses will never be built. Grid operators know this and apply screening assumptions, but the industry has little historical data on what fraction of AI-era announced load converts to actual consumption. The honest read of any 35% figure is that it is a planning scenario with meaningful uncertainty in both directions — actual growth could undershoot if projects evaporate, or overshoot if AI demand keeps compounding.

    That uncertainty is not a reason to dismiss the forecast; it is a reason to watch how MISO and its member utilities structure commitments. Mechanisms that require large customers to put capital at risk — minimum-take contracts, collateral requirements, contribution to network upgrades — are the market’s way of separating real load from phantom load, and their adoption across the footprint will be a better indicator of true demand than any single projection.

    Background

    MISO was founded in 1998 and became the first FERC-approved regional transmission organization in the United States in 2001. It coordinates generation and high-voltage transmission across a footprint stretching from the upper Midwest down through the Gulf South, serving tens of millions of people through its member utilities. Like other RTOs, it does not own power plants or lines; it operates markets and plans the system that its members build.

    The forecast arrives amid a broader U.S. re-acceleration of electricity demand after more than a decade of stagnation, driven by AI and cloud data center construction, manufacturing reshoring, and electrification. Grid operators across the country have been revising load outlooks upward repeatedly since the early 2020s, and interconnection queues for both large loads and new generation have swelled to historic levels — making forecasts like this one central to the industry debate over how much of the announced boom is real.

    Source: MISO expects load to jump 35% by 2035 on data center growth — Utility Dive report, April 21, 2026, on MISO’s ten-year load forecast.

  • PJM Moves to Rein In Data Center Demand on the World’s Busiest Grid

    PJM Moves to Rein In Data Center Demand on the World’s Busiest Grid

    PJM Interconnection — the regional grid operator serving 13 states and the District of Columbia, including Northern Virginia’s “Data Center Alley,” the densest concentration of data centers on Earth — is taking steps to rein in data center electricity demand, according to reporting from public broadcaster WHRO published April 20, 2026. The move signals that the operator of the world’s most data-center-heavy grid no longer treats hyperscale load growth as something to be absorbed without conditions.

    Executive Summary

    The significance here is less any single rule than the direction of travel. PJM is the largest wholesale electricity market operator in the United States, coordinating power for roughly 65 million people, and its territory hosts the global capital of the data center industry. For most of the past decade, the operating assumption in that territory was that if you could buy land and fiber, the grid would eventually follow. A grid operator moving to constrain or condition data center demand inverts that assumption.

    For the infrastructure industry, this matters in two ways. First, it converts power from a procurement line item into a gating factor: projects in PJM territory may increasingly be shaped by what the grid operator will allow, and on what timeline, rather than purely by developer ambition. Second, it sets a precedent. PJM’s rules and market designs are watched — and often copied — by other regional operators facing their own waves of AI-driven load requests. What PJM does about data centers rarely stays in PJM.

    The Grid Operator Blinks First

    A regional transmission organization (RTO) like PJM does not generate power or build data centers; it runs the wholesale market and keeps supply and demand in balance across its footprint. Its core legal obligation is reliability. When such an operator starts “taking steps to rein in” a category of demand, it is effectively saying that the pace of load requests has begun to strain its ability to guarantee that balance. That is a notable admission from the operator whose territory — anchored by Loudoun County, Virginia — handles more data center load than any comparable grid in the world.

    The economic backdrop makes the move legible. PJM’s recent capacity auctions — the mechanism through which it pays power plants to be available in future years — have cleared at sharply higher prices, with data center growth widely cited as a principal driver. Those costs flow through to every ratepayer in the footprint, not just the data centers causing the growth. Political and regulatory pressure to distinguish between speculative interconnection requests and real projects, and to make large loads bear more of the costs they create, has been building accordingly.

    From Land-and-Fiber to Power-First Siting

    If the grid operator for the world’s largest data center market is imposing limits, the site selection calculus changes for everyone downstream. Developers who counted on Northern Virginia’s unmatched fiber density and cloud ecosystem now have to weigh whether a grid connection will arrive on a bankable schedule. That logic has already been pushing projects toward secondary markets — and toward on-site or contracted generation that reduces dependence on the shared grid. Constraints in PJM accelerate both trends.

    There is also a sorting effect within the industry. Well-capitalized hyperscalers and established operators can absorb longer timelines, post larger financial commitments, and negotiate directly with utilities and generators. Thinly financed projects that were effectively options on future power — reserving grid capacity they might never use — are the natural target of any tightening. To the extent PJM’s steps separate firm demand from speculative demand, the result could be a healthier queue, even if headline growth numbers shrink.

    Reliability, Ratepayers, and the Politics of AI Load

    The uncomfortable center of this story is cost allocation. Electricity markets were not designed for single customers that show up requesting the load of a mid-sized city. When capacity prices rise to meet that demand, households and small businesses share the bill, and state regulators and legislators hear about it. A grid operator that visibly disciplines data center demand is, among other things, managing its own political legitimacy across 13 states with very different attitudes toward hosting the AI build-out.

    For the data center industry, the fair response is not to dismiss the concern but to engage on mechanism design: rules that require demonstrated financial commitment, that pay large loads for flexibility (curtailing during grid stress), and that let them bring their own generation can protect reliability without rationing growth. The risk, from the industry’s side, is blunt instruments — caps or moratoria that stall real projects along with speculative ones. Which kind of instrument PJM has chosen is the central question the reporting raises.

    Background

    PJM Interconnection grew out of one of the world’s oldest power pools, dating to 1927, and today runs the largest wholesale electricity market in the United States. Its footprint includes Northern Virginia, where cheap land, dense fiber routes, and proximity to federal and internet-exchange infrastructure made Loudoun County the global capital of the data center industry over the past two decades. That concentration was long a point of regional pride and tax revenue; the AI boom has turned it into a grid-planning challenge, as power demand in the region — flat for years — began climbing steeply on the back of hyperscale computing.

    By 2026 the tension was visible on ratepayer bills and in regulatory dockets: PJM’s capacity auction prices had risen sharply with data center growth cited as a key driver, and policymakers across its 13-state footprint were debating who should pay for the infrastructure the AI build-out requires. PJM’s move to rein in data center demand is the market operator’s entry into that debate.

    Source: The Mid-Atlantic’s electric grid operator is taking steps to rein in data center demand — WHRO reporting, April 20, 2026, on PJM Interconnection’s moves to constrain data center load growth.