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In defense of “everything bagel” policymaking.

Writers have likely spilled more ink on the word “abundance” in the past couple months than at any other point in the word’s history.
Beneath the hubbub, fed by Ezra Klein and Derek Thompson’s bestselling new book, lies a pressing question: What would it take to build things faster? Few climate advocates would deny the salience of the question, given the incontrovertible need to fix the sluggish pace of many clean energy projects.
A critical question demands an actionable answer. To date, many takes on various sides of the debate have focused more on high-level narrative than precise policy prescriptions. If we zoom in to look at the actual sources of delay in clean energy projects, what sorts of solutions would we come up with? What would a data-backed agenda for clean energy abundance look like?
The most glaring threat to clean energy deployment is, of course, the Republican Party’s plan to gut the Inflation Reduction Act. But “abundance” proponents posit that Democrats have imposed their own hurdles, in the form of well-intentioned policies that get in the way of government-backed building projects. According to some broad-brush recommendations, Democrats should adopt an abundance agenda focused on rolling back such policies.
But the reality for clean energy is more nuanced. At least as often, expediting clean energy projects will require more, not less, government intervention. So too will the task of ensuring those projects benefit workers and communities.
To craft a grounded agenda for clean energy abundance, we can start by taking stock of successes and gaps in implementing the IRA. The law’s core strategy was to unite climate, jobs, and justice goals. The IRA aims to use incentives to channel a wave of clean energy investments towards good union jobs and communities that have endured decades of divestment.
Klein and Thompson are wary that such “everything bagel” strategies try to do too much. Other “abundance” advocates explicitly support sidelining the IRA’s labor objectives to expedite clean energy buildout.
But here’s the thing about everything bagels: They taste good.
They taste good because they combine ingredients that go well together. The question — whether for bagels or policies — is, are we using congruent ingredients?
The data suggests that clean energy growth, union jobs, and equitable investments — like garlic, onion, and sesame seeds — can indeed pair well together. While we have a long way to go, early indicators show significant post-IRA progress on all three fronts: a nearly 100-gigawatt boom in clean energy installations, an historic high in clean energy union density, and outsized clean investments flowing to fossil fuel communities. If we can design policy to yield such a win-win-win, why would we choose otherwise?
Klein and Thompson are of course right that to realize the potential of the IRA, we must reduce the long lag time in building clean energy projects. That lag time does not stem from incentives for clean energy companies to provide quality jobs, negotiate Community Benefits Agreements, or invest in low-income communities. Such incentives did not deter clean energy companies from applying for IRA funding in droves. Programs that included all such incentives were typically oversubscribed, with companies applying for up to 10 times the amount of available funding.
If labor and equity incentives are not holding up clean energy deployment, what is? And what are the remedies?
Some of the biggest delays point not to an excess of policymaking — the concern of many “abundance” proponents — but an absence. Such gaps call for more market-shaping policies to expedite the clean energy transition.
Take, for example, the years-long queues for clean energy projects to connect to the electrical grid, which developers rank as one of the largest sources of delay. That wait stems from a piecemeal approach to transmission buildout — the result not of overregulation by progressive lawmakers, but rather the opposite: a hands-off mode of governance that has created vast inefficiencies. For years, grid operators have built transmission lines not according to a strategic plan, but in response to the requests of individual projects to connect to the grid. This reactive, haphazard approach requires a laborious battery of studies to determine the incremental transmission upgrades (and the associated costs) needed to connect each project. As a result, project developers face high cost uncertainty and a nearly five-year median wait time to finish the process, contributing to the withdrawal of about three of every four proposed projects.
The solution, according to clean energy developers, buyers, and analysts alike, is to fill the regulatory void that has enabled such a fragmentary system. Transmission experts have called for rules that require grid operators to proactively plan new transmission lines in anticipation of new clean energy generation and then charge a preestablished fee for projects to connect, yielding more strategic grid expansion, greater cost certainty for developers, fewer studies, and reduced wait times to connect to the grid. Last year, the Federal Energy Regulatory Commission took a step in this direction by requiring grid operators to adopt regional transmission planning. Many energy analysts applauded the move and highlighted the need for additional policies to expedite transmission buildout.
Another source of delay that underscores policy gaps is the 137-week lag time to obtain a large power transformer, due to supply chain shortages. The United States imports four of every five large power transformers used on our electric grid. Amid the post-pandemic snarling of global supply chains, such high import dependency has created another bottleneck for building out the new transmission lines that clean energy projects demand. To stimulate domestic transformer production, the National Infrastructure Advisory Council — including representatives from major utilities — has proposed that the federal government establish new transformer manufacturing investments and create a public stockpiling system that stabilizes demand. That is, a clean energy abundance agenda also requires new industrial policies.
While such clean energy delays call for additional policymaking, “abundance” advocates are correct that other delays call for ending problematic policies. Rising local restrictions on clean energy development, for example, pose a major hurdle. However, the map of those restrictions, as tracked in an authoritative Columbia University report, does not support the notion that they stem primarily from Democrats’ penchant for overregulation. Of the 11 states with more than 10 such restrictions, six are red, three are purple, and two are blue — New York and Texas, Virginia and Kansas, Maine and Indiana, etc. To take on such restrictions, we shouldn’t let concern with progressive wish lists eclipse a focused challenge to old-fashioned, transpartisan NIMBYism.
“Abundance” proponents also focus their ire on permitting processes like those required by the National Environmental Policy Act, which the Supreme Court curtailed last week. Permitting needs mending, but with a chisel, not a Musk-esque chainsaw. The Biden administration produced a chisel last year: a NEPA reform to expedite clean energy projects and support environmental justice. In February, the Trump administration tossed out that reform and nearly five decades of NEPA rules without offering a replacement — a chainsaw maneuver that has created more, not less, uncertainty for project developers. When the wreckage of this administration ends, we’ll need to fill the void with targeted permitting policies that streamline clean energy while protecting communities.
Finally, a clean energy abundance agenda should also welcome pro-worker, pro-equity incentives like those in the IRA “everything bagel.” Despite claims to the contrary, such policies can help to overcome additional sources of delay and facilitate buildout.
For example, Community Benefits Agreements, which IRA programs encouraged, offer a distinct, pro-building advantage: a way to avoid the community opposition that has become a top-tier reason for delays and cancellations of wind and solar projects. CBAs give community and labor groups a tool to secure locally-defined economic, health, and environmental benefits from clean energy projects. For clean energy firms, they offer an opportunity to obtain explicit project support from community organizations. Three out of four wind and solar developers agree that increased community engagement reduces project cancellations, and more than 80% see it as at least somewhat “feasible” to offer benefits via CBAs. Indeed, developers and communities are increasingly using CBAs, from a wind farm off the coast of Rhode Island to a solar park in California’s central valley, to deliver tangible benefits and completed projects — the ingredients of abundance.
A similar win-win can come from incentives for clean energy companies to pay construction workers decent wages, which the IRA included. Most peer-reviewed studies find that the impact of such standards on infrastructure construction costs is approximately zero. By contrast, wage standards can help to address a key constraint on clean energy buildout: companies’ struggle to recruit a skilled and stable workforce in a tight labor market. More than 80% of solar firms, for example, report difficulties in finding qualified workers. Wage standards offer a proven solution, helping companies attract and retain the workforce needed for on-time project completion.
In addition to labor standards and support for CBAs, a clean energy abundance agenda also should expand on the IRA’s incentives to invest in low-income communities. Such policies spur clean energy deployment in neighborhoods the market would otherwise deem unprofitable. Indeed, since enactment of the IRA, 75% of announced clean energy investments have been in low-income counties. That buildout is a deliberate outcome of the “everything bagel” approach. If we want clean energy abundance for all, not just the wealthy, we need to wield — not withdraw — such incentives.
Crafting an agenda for clean energy abundance requires precision, not abstraction. We need to add industrial policies that offer a foundation for clean energy growth. We need to end parochial policies that deter buildout on behalf of private interests. And we need to build on labor and equity policies that enable workers and communities to reap material rewards from clean energy expansion. Differentiating between those needs will be essential for Democrats to build a clean energy plan that actually delivers abundance.
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Current conditions: A cluster of storms from Sri Lanka to Southeast Asia triggered floods that have killed more than 900 so far • A snowstorm stretching 1,200 miles across the northern United States blanketed parts of Iowa, Illinois, and South Dakota with the white stuff • In China, 31 weather stations broke records for heat on Sunday.
The in-house market monitor at the PJM Interconnection filed a complaint last week to the Federal Energy Regulatory Commission urging the agency to ban the nation’s largest grid operator from connecting any new data centers that the system can’t reliably serve. The warning from the PJM ombudsman comes as the grid operator is considering proposals to require blackouts during periods when there’s not enough electricity to meet data centers’ needs. The grid operator’s membership voted last month on a way forward, but no potential solution garnered enough votes to succeed, Heatmap’s Matthew Zeitlin wrote. “That result is not consistent with the basic responsibility of PJM to maintain a reliable grid and is therefore not just and reasonable,” Monitoring Analytics said, according to Utility Dive.
The push comes as residential electricity prices continue climbing. Rates for American households spiked by an average of 7.4% in September compared to the same month in 2024, according to new data from the Energy Information Administration.

The Environmental Protection Agency made some big news on Wednesday, just before much of the U.S. took off for Thanksgiving: It’s delaying a rule that would have required oil and gas companies to start reducing how much methane, a potent greenhouse gas, is released from their operations into the atmosphere. The regulation would have required oil and gas companies to start reducing how much methane, a potent greenhouse gas, is released from their operations into the atmosphere. Drillers were supposed to start tracking emissions this year. But the Trump administration is instead giving companies until January 2027 as it considers repealing the measure altogether.
The New York Power Authority, the nation’s second largest government-owned utility after the federal Tennessee Valley Authority, is staffing up in preparation for its push to build at least a gigawatt of new nuclear power generation. On Monday morning, NYPA named Todd Josifovski as its new senior vice president of nuclear energy development, tasking the veteran atomic power executive with charting the strategic direction and development of new reactor projects. Josifovski previously hailed from Ontario Power Generation, the state-owned utility in the eponymous Canadian province, which is building what is likely to be North America’s first small modular reactor project. (As Matthew wrote when NYPA first announced its plans for a new nuclear plant, the approach mirrors Ontario’s there.) NYPA is also adding Christopher Hanson, a former member of the Nuclear Regulatory Commission whom President Donald Trump abruptly fired from the federal agency this summer, as a senior consultant in charge of guiding federal financing and permitting.
The push comes as New York’s statewide grid reaches “an inflection point” as surging demand, an aging fleet, and a lack of dispatchable power puts the system at risk, according to the latest reliability report. “The margin for error is extremely narrow, and most plausible futures point to significant reliability shortfalls within the next ten years,” the report concluded. “Depending on demand growth and retirement patterns, the system may need several thousand megawatts of new dispatchable generation over that timeframe.”
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Zillow, the country’s largest real estate site, removed a feature from more than a million listings that showed the risks from extreme weather, The New York Times reported. The website had started including climate risk scores last year, using data from the risk-modeling company First Street. But real estate agents complained that the ratings hurt sales, and homeowners protested that there was no way to challenge the scores. Following a complaint from the California Regional Multiple Listing Service, which operates a private database of brokers and agents, Zillow stopped displaying the scores.
The European Commission unveiled a new plan to replace fossil fuels in Europe’s economy with trees. By adopting the so-called Bioeconomy Strategy, released Thursday, the continent aims to remove fossil fuels in products Politico listed as “plastics, building materials, chemicals, and fibers” with organic materials that regrow, such as trees and crops. Doing so, the bloc argued, will help to preserve Europe’s “strategic autonomy” by making the continent less dependent on imported fuels.
Canada, meanwhile, is plowing ahead with its plans to strengthen itself against the U.S. by turning into an energy superpower. Already, the Trans Mountain pipeline is earning the federal coffers nearly $1.3 billion, based on my back-of-the-napkin conversion of the Canadian loonies cited in this Globe and Mail story to U.S. dollars. Now Prime Minister Mark Carney’s government is pitching a new pipeline from Alberta to the West Coast for export to Asia, as the Financial Times reported.
Swapping bunker fuel-burning engines for nuclear propulsion units in container ships could shave up to $68 million off annual shipping expenses, a new report found. If small modular reactors designed to power a cargo vessel are commercialized within four years as expected, the shipping companies could eliminate $50 million in fuel costs each year and about $18 million in carbon penalties. That’s according to data from Lloyd’s Register and LucidCatalyst report for the Singaporean maritime services company Seaspan Corporation.
If it turns out to be a bubble, billions of dollars of energy assets will be on the line.
The data center investment boom has already transformed the American economy. It is now poised to transform the American energy system.
Hyperscalers — including tech giants such as Microsoft and Meta, as well as leaders in artificial intelligence like OpenAI and CoreWeave — are investing eyewatering amounts of capital into developing new energy resources to feed their power-hungry data infrastructure. Those data centers are already straining the existing energy grid, prompting widespread political anxiety over an energy supply crisis and a ratepayer affordability shock. Nothing in recent memory has thrown policymakers’ decades-long underinvestment in the health of our energy grid into such stark relief. The commercial potential of next-generation energy technologies such as advanced nuclear, batteries, and grid-enhancing applications now hinge on the speed and scale of the AI buildout.
But what happens if the AI boom buffers and data center investment collapses? It is not idle speculation to say that the AI boom rests on unstable financial foundations. Worse, however, is the fact that as of this year, the tech sector’s breakneck investment into data centers is the only tailwind to U.S. economic growth. If there is a market correction, there is no other growth sector that could pick up the slack.
Not only would a sudden reversal in investor sentiment make stranded assets of the data centers themselves, which will lose value as their lease revenue disappears, it also threatens to strand all the energy projects and efficiency innovations that data center demand might have called forth.
If the AI boom does not deliver, we need a backup plan for energy policy.
An analysis of the capital structure of the AI boom suggests that policymakers should be more concerned about the financial fundamentals of data centers and their tenants — the tech companies that are buoying the economy. My recent report for the Center for Public Enterprise, Bubble or Nothing, maps out how the various market actors in the AI sector interact, connecting the market structure of the AI inference sector to the economics of Nvidia’s graphics processing units, the chips known as GPUs that power AI software, to the data center real estate debt market. Spelling out the core financial relationships illuminates where the vulnerabilities lie.

First and foremost: The business model remains unprofitable. The leading AI companies ― mostly the leading tech companies, as well as some AI-specific firms such as OpenAI and Anthropic ― are all competing with each other to dominate the market for AI inference services such as large language models. None of them is returning a profit on its investments. Back-of-the-envelope math suggests that Meta, Google, Microsoft, and Amazon invested over $560 billion into AI technology and data centers through 2024 and 2025, and have reported revenues of just $35 billion.
To be sure, many new technology companies remain unprofitable for years ― including now-ubiquitous firms like Uber and Amazon. Profits are not the AI sector’s immediate goal; the sector’s high valuations reflect investors’ assumptions about future earnings potential. But while the losses pile up, the market leaders are all vying to maximize the market share of their virtually identical services ― a prisoner’s dilemma of sorts that forces down prices even as the cost of providing inference services continues to rise. Rising costs, suppressed revenues, and fuzzy measurements of real user demand are, when combined, a toxic cocktail and a reflection of the sector’s inherent uncertainty.
Second: AI companies have a capital investment problem. These are not pure software companies; to provide their inference services, AI companies must all invest in or find ways to access GPUs. In mature industries, capital assets have predictable valuations that their owners can borrow against and use as collateral to invest further in their businesses. Not here: The market value of a GPU is incredibly uncertain and, at least currently, remains suppressed due to the sector’s competitive market structure, the physical deterioration of GPUs at high utilization rates, the unclear trajectory of demand, and the value destruction that comes from Nvidia’s now-yearly release of new high-end GPU models.
The tech industry’s rush to invest in new GPUs means existing GPUs lose market value much faster. Some companies, particularly the vulnerable and debt-saddled “neocloud” companies that buy GPUs to rent their compute capacity to retail and hyperscaler consumers, are taking out tens of billions of dollars of loans to buy new GPUs backed by the value of their older GPU stock; the danger of this strategy is obvious. Others including OpenAI and xAI, having realized that GPUs are not safe to hold on one’s balance sheet, are instead renting them from Oracle and Nvidia, respectively.
To paper over the valuation uncertainty of the GPUs they do own, all the hyperscalers have changed their accounting standards for GPU valuations over the past few years to minimize their annual reported depreciation expenses. Some financial analysts don’t buy it: Last year, Barclays analysts judged GPU depreciation as risky enough to merit marking down the earnings estimates of Google (in this case its parent company, Alphabet), Microsoft, and Meta as much as 10%, arguing that consensus modeling was severely underestimating the earnings write-offs required.
Under these market dynamics, the booming demand for high-end chips looks less like a reflection of healthy growth for the tech sector and more like a scramble for high-value collateral to maintain market position among a set of firms with limited product differentiation. If high demand projections for AI technologies come true, collateral ostensibly depreciates at a manageable pace as older GPUs retain their marketable value over their useful life — but otherwise, this combination of structurally compressed profits and rapidly depreciating collateral is evidence of a snake eating its own tail.
All of these hyperscalers are tenants within data centers. Their lack of cash flow or good collateral should have their landlords worried about “tenant churn,” given the risk that many data center tenants will have to undertake multiple cycles of expensive capital expenditure on GPUs and network infrastructure within a single lease term. Data center developers take out construction (or “mini-perm”) loans of four to six years and refinance them into longer-term permanent loans, which can then be packaged into asset-backed and commercial mortgage-backed securities to sell to a wider pool of institutional investors and banks. The threat of broken leases and tenant vacancies threatens the long-term solvency of the leading data center developers ― companies like Equinix and Digital Realty ― as well as the livelihoods of the construction contractors and electricians they hire to build their facilities and manage their energy resources.
Much ink has already been spilled on how the hyperscalers are “roundabouting” each other, or engaging in circular financing: They are making billions of dollars of long-term purchase commitments, equity investments, and project co-development agreements with one another. OpenAI, Oracle, CoreWeave, and Nvidia are at the center of this web. Nvidia has invested $100 billion in OpenAI, to be repaid over time through OpenAI’s lease of Nvidia GPUs. Oracle is spending $40 billion on Nvidia GPUs to power a data center it has leased for 15 years to support OpenAI, for which OpenAI is paying Oracle $300 billion over the next five years. OpenAI is paying CoreWeave over the next five years to rent its Nvidia GPUs; the contract is valued at $11.9 billion, and OpenAI has committed to spending at least $4 billion through April 2029. OpenAI already has a $350 million equity stake in CoreWeave. Nvidia has committed to buying CoreWeave’s unsold cloud computing capacity by 2032 for $6.3 billion, after it already took a 7% stake in CoreWeave when the latter went public. If you’re feeling dizzy, count yourself lucky: These deals represent only a fraction of the available examples of circular financing.
These companies are all betting on each others’ growth; their growth projections and purchase commitments are all dependent on their peers’ growth projections and purchase commitments. Optimistically, this roundabouting represents a kind of “risk mutualism,” which, at least for now, ends up supporting greater capital expenditures. Pessimistically, roundabouting is a way for these companies to pay each other for goods and services in any way except cash — shares, warrants, purchase commitments, token reservations, backstop commitments, and accounts receivable, but not U.S. dollars. The second any one of these companies decides it wants cash rather than a commitment is when the music stops. Chances are, that company needs cash to pay a commitment of its own, likely involving a lender.
Lenders are the final piece of the puzzle. Contrary to the notion that cash-rich hyperscalers can finance their own data center buildout, there has been a record volume of debt issuance this year from companies such as Oracle and CoreWeave, as well as private credit giants like Blue Owl and Apollo, which are lending into the boom. The debt may not go directly onto hyperscalers’ balance sheets, but their purchase commitments are the collateral against which data center developers, neocloud companies like CoreWeave, and private credit firms raise capital. While debt is not inherently something to shy away from ― it’s how infrastructure gets built ― it’s worth raising eyebrows at the role private credit firms are playing at the center of this revenue-free investment boom. They are exposed to GPU financing and to data center financing, although not the GPU producers themselves. They have capped upside and unlimited downside. If they stop lending, the rest of the sector’s risks look a lot more risky.

A market correction starts when any one of the AI companies can’t scrounge up the cash to meet its liabilities and can no longer keep borrowing money to delay paying for its leases and its debts. A sudden stop in lending to any of these companies would be a big deal ― it would force AI companies to sell their assets, particularly GPUs, into a potentially adverse market in order to meet refinancing deadlines. A fire sale of GPUs hurts not just the long-term earnings potential of the AI companies themselves, but also producers such as Nvidia and AMD, since even they would be selling their GPUs into a soft market.
For the tech industry, the likely outcome of a market correction is consolidation. Any widespread defaults among AI-related businesses and special purpose vehicles will leave capital assets like GPUs and energy technologies like supercapacitors stranded, losing their market value in the absence of demand ― the perfect targets for a rollup. Indeed, it stands to reason that the tech giants’ dominance over the cloud and web services sectors, not to mention advertising, will allow them to continue leading the market. They can regain monopolistic control over the remaining consumer demand in the AI services sector; their access to more certain cash flows eases their leverage constraints over the longer term as the economy recovers.
A market correction, then, is hardly the end of the tech industry ― but it still leaves a lot of data center investments stranded. What does that mean for the energy buildout that data centers are directly and indirectly financing?
A market correction would likely compel vertically integrated utilities to cancel plans to develop new combined-cycle gas turbines and expensive clean firm resources such as nuclear energy. Developers on wholesale markets have it worse: It’s not clear how new and expensive firm resources compete if demand shrinks. Grid managers would have to call up more expensive units less frequently. Doing so would constrain the revenue-generating potential of those generators relative to the resources that can meet marginal load more cheaply — namely solar, storage, peaker gas, and demand-response systems. Combined-cycle gas turbines co-located with data centers might be stranded; at the very least, they wouldn’t be used very often. (Peaker gas plants, used to manage load fluctuation, might still get built over the medium term.) And the flight to quality and flexibility would consign coal power back to its own ash heaps. Ultimately, a market correction does not change the broader trend toward electrification.
A market correction that stabilizes the data center investment trajectory would make it easier for utilities to conduct integrated resource planning. But it would not necessarily simplify grid planners’ ability to plan their interconnection queues — phantom projects dropping out of the queue requires grid planners to redo all their studies. Regardless of the health of the investment boom, we still need to reform our grid interconnection processes.
The biggest risk is that ratepayers will be on the hook for assets that sit underutilized in the absence of tech companies’ large load requirements, especially those served by utilities that might be building power in advance of committed contracts with large load customers like data center developers. The energy assets they build might remain useful for grid stability and could still participate in capacity markets. But generation assets built close to data center sites to serve those sites cheaply might not be able to provision the broader energy grid cost-efficiently due to higher grid transport costs incurred when serving more distant sources of load.
These energy projects need not be albatrosses.
Many of these data centers being planned are in the process of securing permits and grid interconnection rights. Those interconnection rights are scarce and valuable; if a data center gets stranded, policymakers should consider purchasing those rights and incentivizing new businesses or manufacturing industries to build on that land and take advantage of those rights. Doing so would provide offtake for nearby energy assets and avoid displacing their costs onto other ratepayers. That being said, new users of that land may not be able to pay anywhere near as much as hyperscalers could for interconnection or for power. Policymakers seeking to capture value from stranded interconnection points must ensure that new projects pencil out at a lower price point.
Policymakers should also consider backstopping the development of critical and innovative energy projects and the firms contracted to build them. I mean this in the most expansive way possible: Policymakers should not just backstop the completion of the solar and storage assets built to serve new load, but also provide exigent purchase guarantees to the firms that are prototyping the flow batteries, supercapacitors, cooling systems, and uninterruptible power systems that data center developers are increasingly interested in. Without these interventions, a market correction would otherwise destroy the value of many of those projects and the earnings potential of their developers, to say nothing of arresting progress on incredibly promising and commercializable technologies.
Policymakers can capture long-term value for the taxpayer by making investments in these distressed projects and developers. This is already what the New York Power Authority has done by taking ownership and backstopping the development of over 7 gigawatts of energy projects ― most of which were at risk of being abandoned by a private sponsor.
The market might not immediately welcome risky bets like these. It is unclear, for instance, what industries could use the interconnection or energy provided to a stranded gigawatt-scale data center. Some of the more promising options ― take aluminum or green steel ― do not have a viable domestic market. Policy uncertainty, tariffs, and tax credit changes in the One Big Beautiful Bill Act have all suppressed the growth of clean manufacturing and metals refining industries like these. The rest of the economy is also deteriorating. The fact that the data center boom is threatened by, at its core, a lack of consumer demand and the resulting unstable investment pathways is itself an ironic miniature of the U.S. economy as a whole.
As analysts at Employ America put it, “The losses in a [tech sector] bust will simply be too large and swift to be neatly offset by an imminent and symmetric boom elsewhere. Even as housing and consumer durables ultimately did well following the bust of the 90s tech boom, there was a one- to two-year lag, as it took time for long-term rates to fall and investors to shift their focus.” This is the issue with having only one growth sector in the economy. And without a more holistic industrial policy, we cannot spur any others.
Questions like these ― questions about what comes next ― suggest that the messy details of data center project finance should not be the sole purview of investors. After all, our exposure to the sector only grows more concentrated by the day. More precisely mapping out how capital flows through the sector should help financial policymakers and industrial policy thinkers understand the risks of a market correction. Political leaders should be prepared to tackle the downside distributional challenges raised by the instability of this data center boom ― challenges to consumer wealth, public budgets, and our energy system.
This sparkling sector is no replacement for industrial policy and macroeconomic investment conditions that create broad-based sources of demand growth and prosperity. But in their absence, policymakers can still treat the challenge of a market correction as an opportunity to think ahead about the nation’s industrial future.
With more electric heating in the Northeast comes greater strains on the grid.
The electric grid is built for heat. The days when the system is under the most stress are typically humid summer evenings, when air conditioning is still going full blast, appliances are being turned on as commuters return home, and solar generation is fading, stretching the generation and distribution grid to its limits.
But as home heating and transportation goes increasingly electric, more of the country — even some of the chilliest areas — may start to struggle with demand that peaks in the winter.
While summer demand peaks are challenging, there’s at least a vision for how to deal with them without generating excessive greenhouse gas emissions — namely battery storage, which essentially holds excess solar power generated in the afternoon in reserve for the evening. In states with lots of renewables on the grid already, like California and Texas, storage has been helping smooth out and avoid reliability issues on peak demand days.
The winter challenge is that you can have long periods of cold weather and little sun, stressing every part of the grid. The natural gas production and distribution systems can struggle in the cold with wellheads freezing up and mechanical failure at processing facilities, just as demand for home heating soars, whether provided by piped gas or electricity generated from gas-fired power plants.
In its recent annual seasonal reliability assessment, the North American Reliability Corporation, a standard-setting body for grid operators, found that “much of North America is again at an elevated risk of having insufficient energy supplies” should it encounter “extreme operating conditions,” i.e. “any prolonged, wide-area cold snaps.”
NERC cited growing electricity demand and the difficulty operating generators in the winter, especially those relying on natural gas. In 2021, Winter Storm Uri effectively shut down Texas’ grid for several days as generation and distribution of natural gas literally froze up while demand for electric heating soared. Millions of Texans were left exposed to extreme low temperatures, and at least 246 died as a result.
Some parts of the country already experience winter peaks in energy demand, especially places like North Carolina and Oregon, which “have winters that are chilly enough to require some heating, but not so cold that electric heating is rare,” in the words of North Carolina State University professor Jeremiah Johnson. "Not too many Mainers or Michiganders heat their homes with electricity,” he said.
But that might not be true for long.
New England may be cold and dark in the winter, but it’s liberal all year round. That means the region’s constituent states have adopted aggressive climate change and decarbonization goals that will stretch their available renewable resources, especially during the coldest days, weeks, and months.
The region’s existing energy system already struggles with winter. New England’s natural gas system is limited by insufficient pipeline capacity, so during particularly cold days, power plants end up burning oil as natural gas is diverted from generating electricity to heating homes.
New England’s Independent System Operator projects that winter demand will peak at just above 21 gigawatts this year — its all-time winter peak is 22.8 gigawatts, summer is 28.1 — which ISO-NE says the region is well-prepared for, with 31 gigawatts of available capacity. That includes energy from the Vineyard Wind offshore wind project, which is still facing activist opposition, as well as imported hydropower from Quebec.
But going forward, with Massachusetts aiming to reduce emissions 50% by 2030 (though state lawmakers are trying to undo that goal) and reach net-zero emissions by 2050 — and nearly the entire region envisioning at least 80% emissions reductions by 2050 — that winter peak is expected to soar. The non-carbon-emitting energy generation necessary to meet that demand, meanwhile, is still largely unbuilt.
By the mid 2030s, ISO-NE expects its winter peak to surpass its summer peak, with peak demand perhaps reaching as high as 57 gigawatts, more than double the system’s all-time peak load. Those last few gigawatts of this load will be tricky — and expensive — to serve. ISO-NE estimates that each gigawatt from 51 to 57 would cost $1.5 billion for transmission expansion alone.
ISO-NE also found that “the battery fleet may be depleted quickly and then struggle to recharge during the winter months,” which is precisely when “batteries may be needed most to fill supply gaps during periods of high demand due to cold weather, as well as periods of low production from wind and solar resources.” Some 600 megawatts of battery storage capacity has come online in the last decade in ISO-NE, and there are state mandates for at least 7 more gigawatts between 2030 and 2033.
There will also be a “continued need for fuel-secure dispatchable resources” through 2050, ISO-NE has found — that is, something to fill the role that natural gas, oil, and even coal play on the coldest days and longest cold stretches of the year.
This could mean “vast quantities of seasonal storage,” like 100-hour batteries, or alternative fuels like synthetic natural gas (produced with a combination of direct air capture and electrolysis, all powered by carbon-free power), hydrogen, biodiesel, or renewable diesel. And this is all assuming a steady buildout of renewable power — including over a gigawatt per year of offshore wind capacity added through 2050 — that will be difficult if not impossible to accomplish given the current policy and administrative roadblocks.
While planning for the transmission and generation system of 2050 may be slightly fanciful, especially as the climate policy environment — and the literal environment — are changing rapidly, grid operators in cold regions are worried about the far nearer term.
From 2027 to 2032, ISO-NE analyses “indicate an increasing energy shortfall risk profile,” said ISO-NE planning official Stephen George in a 2024 presentation.
“What keeps me up at night is the winter of 2032,” Richard Dewey, chief executive of the neighboring New York Independent System Operator, said at a 2024 conference. “I don’t know what fills that gap in the year 2032.”