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A new report demonstrates how to power the computing boom with (mostly) clean energy.
After a year of concerted hand-wringing about the growing energy needs of data centers, a report that dropped just before the holidays proposed a solution that had been strangely absent from the discussion.
AI companies have seemingly grasped for every imaginable source of clean energy to quench their thirst for power, including pricey, left-field ideas like restarting shuttered nuclear plants. Some are foregoing climate concerns altogether and ordering up off-grid natural gas turbines. In a pithily named new analysis — “Fast, scalable, clean, and cheap enough” — the report’s authors make a compelling case for an alternative: off-grid solar microgrids.
An off-grid solar microgrid is a system with solar panels, batteries, and small gas generators that can work together to power a data center directly without connecting to the wider electricity system. It can have infinite possible configurations, such as greater or smaller numbers of solar panels, and more or less gas-generated capacity. The report models the full range of possibilities to illustrate the trade-offs in terms of emission reductions and cost.
An eclectic group of experts got together to do the research, including staffers from the payment company Stripe, a developer called Scale Microgrids, and Paces, which builds software to help renewable energy developers identify viable sites for projects. They found that an off-grid microgrid that supplied 44% of a data center’s demand from solar panels and used a natural gas generator the rest of the time would cost roughly $93 per megawatt-hour compared to about $86 for large, off-grid natural gas turbines — and it would emit nearly one million tons of CO2 less than the gas turbines. A cleaner system that produced 90% of its power from solar and batteries would cost closer to $109 per megawatt-hour, the authors found. While that’s more expensive than gas turbines, it’s significantly cheaper than repowering Three Mile Island, the fabled nuclear plant that Microsoft is bringing back online for an estimated $130 per megawatt-hour.
One challenge with solar microgrids is that they require a lot of land for solar panels. But a geospatial analysis showed that there’s more than enough available land in the U.S. southwest — primarily in West Texas — to cover estimated energy demand growth from data centers through 2030. This shouldn’t be taken as a recommendation, per se. The paper doesn’t interrogate the need for data centers or the trade-offs of building renewable power for AI training facilities versus to serve manufacturing or households. The report is just an exercise in asking whether, if these data centers are going to be developed, could they at least add as few emissions as possible? Not all hyperscalers care about climate, and those that do might still prioritize speed and scale over their net-zero commitments. But the authors argue that it’s possible to build these systems more quickly than it would be to install big gas turbines, which currently have at least three-year lead times to procure and fall under more complicated permitting regimes.
Before the New Year, I spoke with two of the authors — Zeke Hausfather from Stripe and Duncan Campbell from Scale Microgrids — about the report. Stripe doesn’t build data centers and has no plans to, but Hausfather works for a unit within the company called Stripe Climate, which has a “remit to work on impactful things,” he told me. He and his colleagues got interested in the climate dilemma of data centers, and enlisted Scale Microgrids and Paces to help investigate. Our conversation has been lightly edited for clarity.
Why weren’t off-grid solar microgrids really being considered before?
Zeke Hausfather: As AI has grown dramatically, there’s been much more demand for data centers specifically focused on training. Those data centers have a lot more relaxed requirements. Instead of serving millions of customer requests in real time, they’re running these incredibly energy intensive training models. Those don’t need to necessarily be located near where people live, and that unlocks a lot more potential for solar, because you need about 50 times more land to build a data center with off-grid solar and storage than you would to build a data center that had a grid connection.
The other change is that we’re simply running out of good grid connections. And so a lot of the conversation among data center developers has been focused on, is there a way to do this with off-grid natural gas? We think that it makes a lot more sense, particularly given the relaxed constraints of where you can build these, to go with solar and storage, gas back-up, and substantially reduce the emissions impact.
Duncan Campbell: It was funny, when Nan [Ransohoff, head of climate at Stripe] and Zeke first reached out to me, I feel like they convinced me that microgrids were a good idea, which was the first time this ever happened in my life. They were like, what do you think about off-grid solar and storage? Oh, the energy density is way off, you need a ton of land. They’re like, yeah, but you know, for training, you could put it out in the desert, it’s fine, and hyperscalers are doing crazy things right now to access this power. We just went through all these things, and by the end of the call, I was like, yeah, we should do this study. I wasn’t thinking about it this way until me, the microgrids guy, spoke to the payments company.
So it’s just kind of against conventional logic?
Campbell: Going off-grid at all is wild for a data center operator to consider, given the historical impulse was, let’s have 3x more backup generators than we need. Even the off-grid gas turbine proposals out there feel a little nuts. Then, to say solar, 1,000 acres of land, a million batteries — it’s just so unconventional, it’s almost heretical. But when you soberly assess the performance criteria and how the landscape has shifted, particularly access to the grid being problematic right now, but also different requirements for AI training and a very high willingness to pay — as we demonstrate in our reference case with the Three Mile Island restart — it makes sense.
Hausfather: We should be clear, when we talk about reliability, a data center with what we model, which is solar, batteries, and 125% capacity backup gas generators, is still probably going to achieve upwards of 99% reliability. It’s just not gonna be the 99.999% that’s traditionally been needed for serving customers with data centers. You can relax some of the requirements around that.
Can you explain how you went about investigating what it would mean for data centers to use off-grid solar microgrids?
Campbell: First we just built a pretty simple power flow model that says, if you’re in a given location, the solar panel is going to make this much power every hour of the year. And if you have a certain amount of demand and a certain amount of battery, the battery is going to charge and discharge these times to make the demand and supply match. And then when it can’t, your generators will kick on. So that model is just for a given solar-battery-generator combo in a given location. Then what we did is made a huge scenario suite in 50-megawatt increments. Now you can see, for any level of renewable-ness you want, here’s what the [levelized cost of energy] is.
Hausfather: As you approach 100%, the costs start increasing exponentially, which isn’t a new finding, but you’re essentially having to overbuild more and more solar and batteries in order to deal with those few hours of the year where you have extended periods of cloudiness. Which is why it makes a lot more sense, financially, to have a system with some gas generator use — unless you happen to be in a situation where you can actually only run your data center 90% of the time. I think that’s probably a little too heretical for anyone today, but we did include that as one of the cases.
Did you consider water use? Because when you zoom in on the Southwest, that seems like it could be a constraint.
Hausfather: We talked about water use a little bit, but it wasn’t a primary consideration. One of the reasons is that how data centers are designed has a big effect on net water use. There are a lot of designs now that are pretty low — close to zero — water use, because you’re cycling water through the system rather than using evaporative cooling as the primary approach.
What do you want the takeaway from this report to be? Should all data centers be doing this? To what extent do you think this can replace other options out there?
Hausfather: There is a land rush right now for building data centers quickly. While there’s a lot of exciting investment happening in clean, firm generation like the enhanced geothermal that Fervo is doing, none of those are going to be available at very large scales until after 2030. So if you’re building data centers right now and you don’t want to cause a ton of emissions and threaten your company’s net-zero targets or the social license for AI more broadly, this makes a lot of sense as an option. The cost premium above building a gas system is not that big.
Campbell: For me, it’s two things. I see one purpose of this white paper being to reset rules of thumb. There’s this vestigial knowledge we have that this is impossible, and no, this is totally possible. And it seems actually pretty reasonable.
The second part that I think is really radical is the gigantic scale implied by this solution. Every other solution being proposed is kind of like finding a needle in a haystack — if we find this old steel mill, we could use that interconnection to build a data center, or, you know, maybe we can get Exxon to make carbon capture work finally. If a hyperscaler just wanted to build 10 gigawatts of data centers, and wanted one plan to do it, I think this is the most compelling option. The scalability implied by this solution is a huge factor that should be considered.
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The widely circulating document lists more than 68 activities newly subject to upper-level review.
The federal government is poised to put solar and wind projects through strict new reviews that may delay projects across the country, according to a widely circulating document reviewed by Heatmap.
The secretarial order authored by Interior Secretary Doug Burgum’s Deputy Chief of Staff for Policy Gregory Wischer is dated July 15 and states that “all decisions, actions, consultations, and other undertakings” that are “related to wind and solar energy facilities” will now be required to go through multiple layers of political review from Burgum’s office and Interior’s Office of the Deputy Secretary.
This new layer of review would span essentially anything Interior and its many subagencies would ordinarily be consulted on before construction on a project can commence — a milestone crucial for being able to qualify for federal renewable energy tax credits under the One Big Beautiful Bill Act. The order lists more than 68 different activities newly subject to higher-level review, including some basic determinations as to whether projects conform with federal environmental and conservation laws, as well as consultations on compliance with wildlife protection laws such as the Endangered Species Act. The final item in the list sweeps “any other similar or related decisions, actions, consultations, or undertakings” under the order’s purview, in case there was any grey area there.
In other words, this order is so drastic it would impact projects on state and private lands, as well as federal acreage. In some cases, agency staff may now need political sign-offs simply to tell renewables developers whether they need a permit at all.
“This is the way you stall and kill projects. Intentionally red-tape projects to death,” former Biden White House clean energy adviser Avi Zevin wrote on Bluesky in a post with a screenshot of the order.
The department has yet to release the document and it’s unclear whether or when it will be made public. The order’s existence was first reported by Politico; in a statement to that news outlet, the department did not deny the document’s existence but attacked leakers. “Let’s be clear: leaking internal documents to the media is cowardly, dishonest, and a blatant violation of professional standards,” the statement said.
Interior’s press office did not immediately respond to a request for comment from Heatmap about when this document may be made public. We also asked whether this would also apply to transmission connected to solar and wind. You had better believe I’ll be following up with the department to find out, and we’ll update this story if we hear back from them.
Two former Microsoft employees have turned their frustration into an awareness campaign to hold tech companies accountable.
When the clean energy world considers the consequences of the artificial intelligence boom, rising data center electricity demand and the strain it’s putting on the grid is typically top of mind — even if that’s weighed against the litany of potential positive impacts, which includes improved weather forecasting, grid optimization, wildfire risk mitigation, critical minerals discovery, and geothermal development.
I’ve written about a bunch of it. But the not-so-secret flip side is that naturally, any AI-fueled improvements in efficiency, data analytics, and predictive capabilities will benefit well-capitalized fossil fuel giants just as much — if not significantly more — than plucky climate tech startups or cash-strapped utilities.
“The narrative is a net impact equation that only includes the positive use cases of AI as compared to the operational impacts, which we believe is apples to oranges,” Holly Alpine, co-founder of the Enabled Emissions Campaign, told me. “We need to expand that conversation and include the negative applications in that scoreboard.”
Alpine founded the campaign alongside her partner, Will Alpine, in February of last year, with the goal of holding tech giants accountable for the ways users leverage their products to accelerate fossil fuel production. Both formerly worked for Microsoft on sustainability initiatives related to data centers and AI, but quit after what they told me amounted to a string of unfulfilled promises by the company and a realization that internal pressure alone couldn’t move the needle as far as they’d hoped.
While at Microsoft, they were dismayed to learn that the company had contracts for its cloud services and suite of AI tools with some of the largest fossil fuel corporations in the world — including ExxonMobil, Chevron, and Shell — and that the partnerships were formed with the explicit intent to expand oil and gas production. Other hyperscalers such as Google and Amazon have also formed similar cloud and AI service partnerships with oil and gas giants, though Google burnished its sustainability bona fides in 2020 by announcing that it would no longer build custom AI tools for the fossil fuel industry. (In response to my request for comment, Microsoft directed me to its energy principles, which were written in 2022, while the Alpines were still with the company, and to its 2025 sustainability report. Neither addresses the Alpines’ concerns directly, which is perhaps telling in its own right.)
AI can help fossil fuel companies accelerate and expand fossil fuel production throughout all stages of the process, from exploration and reservoir modeling to predictive maintenance, transport and logistics optimization, demand forecasting, and revenue modeling. And while partnerships with AI hyperscalers can be extremely beneficial, oil and gas companies are also building out their own AI-focused teams and capabilities in-house.
“As a lot of the low-hanging fruit in the oil reserve space has been plucked, companies have been increasingly relying on things like fracking and offshore drilling to stay competitive,” Will told me. “So using AI is now allowing those operations to continue in a way that they previously could not.”
Exxon, for example, boasts on its website that it’s “the first in our industry to leverage autonomous drilling in deep water,” thanks to its AI-powered systems that can determine drilling parameters and control the whole process sans human intervention. Likewise, BP notes that its "Optimization Genie” AI tool has helped it increase production by about 2,000 oil-equivalent barrels per day in the Gulf of Mexico, and that between 2022 and 2024, AI and advanced analytics allowed the company to increase production by 4% overall.
In general, however, the degree to which AI-enabled systems help expand production is not something companies speak about publicly. For instance, when Microsoft inked a contract with Exxon six years ago, it predicted that its suite of digital products would enable the oil giant to grow production in the Permian Basin by up to 50,000 barrels by 2025. And while output in the Permian has boomed, it’s unclear how much Microsoft is to thank for that as neither company has released any figures.
Either way, many of the climate impacts of using AI for oil and gas production are likely to go unquantified. That’s because the so-called “enabled emissions” from the tech sector are not captured by the standard emissions accounting framework, which categorizes direct emissions from a company’s operations as scope 1, indirect emissions from the generation of purchased energy as scope 2, and all other emissions across the value chain as scope 3. So while tailpipe emissions, for example, would fall into Exxon’s scope 3 bucket — thus requiring disclosure — they’re outside Microsoft’s reporting boundaries.
According to the Alpines’ calculations, though, Microsoft’s deal with Exxon plus another contract with Chevron totalled “over 300% of Microsoft’s entire carbon footprint, including data centers.” So it’s really no surprise that hyperscalers have largely fallen silent when it comes to citing specific numbers, given the history of employee blowback and media furor over the friction between tech companies’ sustainability targets and their fossil fuel contracts.
As such, the tech industry often ends up wrapping these deals in broad language highlighting operational efficiency, digital transformation, and even sustainability benefits —- think waste reduction and decreasing methane leakage rates — while glossing over the fact that at their core, these partnerships are primarily designed to increase oil and gas output.
While none of the fossil fuel companies I contacted — Chevron, Exxon, Shell, and BP — replied to my inquiries about the ways they’re leveraging AI, earnings calls and published corporate materials make it clear that the industry is ready to utilize the technology to its fullest extent.
“We’re looking to leverage knowledge in a different way than we have in the past,” Shell CEO Wael Sawan said on the company’s Q2 earnings call last year, citing AI as one of the tools that he sees as integral to “transform the culture of the company to one that is able to outcompete in the coming years.”
Shell has partnered since 2018 with the enterprise software company C3.ai on AI applications such as predictive maintenance, equipment monitoring, and asset optimization, the latter of which has helped the company increase liquid natural gas production by 1% to 2%. C3.ai CEO Tom Siebel was vague on the company’s 2025 Q1 earnings call, but said that Shell estimates that the partnership has “generated annual benefit to Shell of $2 billion.”
In terms of AI’s ability to get more oil and gas out of the ground, “it’s like getting a Kuwait online,” Rakesh Jaggi, who leads the digital efforts at the oil-services giant SLB, told Barron’s magazine. Kuwait is the third largest crude oil producer in OPEC, producing about 2.9 million barrels per day.
Some oil and gas giants were initially reluctant to get fully aboard the AI hype train — even Exxon CEO Darren Woods noted on the company’s 2024 Q3 earnings call that the oil giant doesn’t “like jumping on bandwagons.” Yet he still sees “good potential” for AI to be a “part of the equation” when it comes to the company’s ambition to slash $15 billion in costs by 2027.
Chevron is similarly looking to AI to cut costs. As the company’s Chief Financial Officer Eimear Bonner explained during its 2024 Q4 earnings call, AI could help Chevron save $2 to $3 billion over the next few years as the company looks towards “using technology to do work completely differently.” Meanwhile, Saudi Aramco’s CEO Amin Nasser told Bloomberg that AI is a core reason it’s been able to keep production costs at $3 per barrel for the past 20 years, despite inflation and other headwinds in the sector.
Of course, it should come as no surprise that fossil fuel companies are taking advantage of the vast opportunities that AI provides. After all, the investors and shareholders these companies are ultimately beholden to would likely revolt if they thought their fiduciaries had failed to capitalize on such an enormous technological breakthrough.
The Alpines are well aware that this is the world we live in, and that we’re not going to overthrow capitalism anytime soon. Right now, they told me they’re primarily running a two-person “awareness campaign,” as the general public and sometimes even former colleagues are largely in the dark when it comes to how AI is being used to boost oil and gas production. While Will said they’re “staying small and lean” for now while they fundraise, the campaign has support from a number of allies including the consumer rights group Public Citizen, the tech worker group Amazon Employees for Climate Justice, and the NGO Friends of the Earth.
In the medium term, they’re looking toward policy shifts that would require more disclosure and regulation around AI’s potential for harm in the energy sector. “The only way we believe to really achieve deep change is to raise the floor at an international or national policy level,” Will told me. As an example, he pointed to the EU’s comprehensive regulations that categorize AI use cases by risk level, which then determines the rules these systems are subject to. Police use of facial recognition is considered high risk, for example, while AI spam filters are low risk. Right now, energy sector applications are not categorized as risky at all.
“What we would advocate for would be that AI use in the energy sector falls under a high risk classification system due to its risk for human harm. And then it would go through a governance process, ideally that would align with climate science targets,” Will told me. “So you could use that to uplift positive applications like AI for methane leak detection, but AI for upstream scenarios should be subject to additional scrutiny.”
And realistically, there’s no chance of something like this being implemented in the U.S. under Trump, let alone somewhere like Saudi Arabia. And even if such regulations were eventually enacted in some countries, energy markets are global, meaning governments around the world would ultimately need to align on risk mitigation strategies for reigning in AI’s potential for climate harm.
As Will told me, “that would be a massive uphill battle, but we think it’s one that’s worth fighting.”
A longtime climate messaging strategist is tired of seeing the industry punch below its weight.
The saga of President Trump’s One Big Beautiful Bill Act contains at least one clear lesson for the clean energy industry: It must grow a political spine and act like the trillion-dollar behemoth it is. And though the logic is counterintuitive, the new law will likely provide an opportunity to build one.
The coming threat to renewable energy investment became apparent as soon as Trump won the presidency again last fall. The only questions were how much was vulnerable, and through what mechanisms.
Still, many clean energy leaders were optimistic that Trump’s “energy abundance” agenda had room for renewables. During the transition, one longtime Republican energy lobbyist told Utility Dive that Trump’s incoming cabinet had a “very aggressive approach towards renewables.” When Democratic Senator John Hickenlooper introduced would-be Secretary of Energy Chris Wright at the fracking executive’s confirmation hearing, he vouched for Wright’s clean energy cred. Even Trump touted Wright’s experience with solar.
At least initially, the argument made sense. After all, energy demand is soaring, and solar, wind, and battery storage account for 95% of new power projects awaiting grid connection in the U.S. In red states like Texas and Oklahoma, clean energy is booming because it’s cheap. Just a few months ago, the Lone Star State achieved record energy generation from solar, wind, and batteries, and consumers there are saving millions of dollars a day because of renewables. The Biden administration funneled clean energy and manufacturing investment into red districts in part to cultivate Republican support for renewables — and to protect those investments no matter who is president.
As a result, for the past six months, clean energy executives have absorbed advice telling them to fly below the radar. Stop using the word “climate” and start using words like “common sense” when you talk to lawmakers. (As a communications and policy strategist who works extensively on climate issues, I’ve given that specific piece of advice.)
But far too many companies and industry groups went much further than tweaking their messaging. They stopped publicly advocating for their interests, and as a result there has been no muscular effort to pressure elected officials where it counts: their reelection campaigns.
This is part of a broader lack of engagement with elected officials on the part of clean energy companies. The oil and gas industry has outspent clean energy on lobbying 2 to 1 this year, despite the fact that oil and gas faces a hugely favorable political environment. In the run up to the last election, the fossil fuel industry spent half a billion dollars to influence candidates; climate and clean energy advocates again spent just a fraction, despite having more on the line. My personal preference is to get money out of politics, but you have to play by the rules as they exist.
Even economically irresistible technologies can be legislated into irrelevance if they don’t have political juice. The last-minute death of the mysterious excise tax on wind and solar that was briefly part of the One Big Beautiful Bill Act was a glaring sign of weakness, not strength — especially given that even the watered-down provisions in the law will damage the economics of renewable energy. After the law passed, the President directed the Treasury Department to issue the strictest possible guidance for the clean energy projects that remain eligible for tax credits.
The tech industry learned this same lesson over many years. The big tech companies started hiring scores of policy and political staff in the 2010s, when they were already multi-hundred-billion dollar companies, but it wasn’t until 2017 that a tech company became the top lobbying spender. Now the tech industry has a sophisticated influence operation that includes carrots and sticks. Crypto learned this lesson even faster, emerging almost overnight as one of the most aggressive industries shaping Washington.
Clean energy needs to catch up. But lobbying spending isn’t a panacea.
Executives in the clean energy sector sometimes say they are stuck between a rock and a hard place. Democrats and the segment of potentially supportive Republicans at the local and federal levels talk and think about clean energy differently. And the dissonance makes it challenging to communicate honestly with both parties, especially in public.
The clean energy industry should recognize that the safest ground is to criticize and cultivate both parties unabashedly. The American political system understands economic self interest, and there are plenty of policy changes that various segments of the clean energy world need from both Democrats and Republicans at the federal and state levels. Democrats need to make it easier to build; Republicans need to support incentives they regularly trumpet for other job-creating industries.
The quality of political engagement from clean energy companies and the growing ecosystem of advocacy groups has improved. The industry, disparate as it is, has gotten smarter. Advocates now bring district-by-district data to policymakers, organize lobby days, and frame clean energy in terms that resonate across the aisle — national security, economic opportunity in rural America, artificial intelligence, and the race with China. That’s progress.
But the tempo is still far too low, and there are too many carrots and too few sticks. The effects of President Trump’s tax law on energy prices might create some leverage. If the law damages renewable energy generation, and thereby raises energy prices as energy demand continues to rise, Americans should know who is responsible. The clean energy sector has to be the messenger, or at least orchestrate the messaging.
The campaigns write themselves: Paid media targeting members of Congress who praised clean energy job growth in their districts and then voted to gut jobs and raise prices; op-eds in local papers calling out that hypocrisy by name; energy workers showing up at town halls demanding their elected officials fight for an industry that’s investing billions in their communities; activating influencers to highlight the bright line between Trump’s law and higher electricity bills; and more.
If renewable energy is going to grow consistently in America, no matter which way the political wind blows, there must be a political cost to crossing the sector. Otherwise it will always be vulnerable to last-minute backroom deals, no matter how “win-win” its technology is.