# Want to get a data center online quickly? Give it some flex. > Source: > Published: 2026-06-16 09:00:00+00:00 # Want to get a data center online quickly? Give it some flex. As the data-center boom puts pressure on the grid, some companies say the answer isn’t just more power plants but software that dials down centers’ energy-guzzling ways when demand spikes. At the end of a tense and scoreless first half of a soccer match between the English men’s team and rival Germany, millions of Brits let out a collective sigh and did what they so often do in moments of stress: They made tea. That wave of electric kettles clicking on, however, caused a different kind of stress: a huge and sudden increase in demand for electricity. But National Grid, which operates the local transmission network, was ready. Just as those kettles started heating up, an AI program sent instructions to a data center in London to slow down some of the facility’s power-hungry chips. This reduction helped make sure there was enough supply to match demand, staving off potential blackouts or damage to electrical hardware. For data centers, which normally guzzle power without consideration for anyone or anything else’s needs, it was a radical departure. It was also a simulation. In December 2025, engineers sought to test a new breed of data center built to be flexible about its electricity needs, so they re-created the energy demand facing the UK’s grid during a match from the 2020 Euro tournament. They wanted to see how their software, called Conductor, would have responded had it been online at the time. Conductor is the signature product of Emerald AI, a firm based in Washington, DC, that’s part of a wave of companies trying to figure out whether data centers can work within the confines of the existing electric grid. This year, Emerald is set to deploy Conductor in a new facility in the part of Virginia known as Data Center Alley, this time connected to the live grid. When overall demand spikes, Conductor will turn down the power used by the data center, while making sure its servers still carry out their timeliest and most important jobs. Emerald’s partners on the project—which include Nvidia and the giant data-center operator Digital Realty—bill it as one of the world’s first “power-flexible AI factories.” Demonstrating that data centers can participate in this kind of give-and-take could ease what many tech leaders identify as *the *bottleneck in getting facilities online: It takes far longer to get approval for, construct, and connect new power plants than to build data centers. PJM, the grid operator in Virginia and the largest one in the US, for instance, needs [eight years to bring new generation online](https://rmi.org/resources/pjms-speed-to-power-problem-and-how-to-fix-it/), according to RMI, an energy research and advocacy group. “We need to solve the energy equation,” says Josh Parker, head of sustainability at Nvidia. “AI factory flexibility is the bridge between the incredible demand for AI and the immediate limitations of our energy grid.” Speed, though, is only one of the issues. Once facilities do plug in, neighbors often criticize them for drawing too much electricity and contributing to rising prices. They say the data centers generate more noise than they do long-term jobs, contribute to pollution, and threaten to put people out of work. Organizers stalled over $150 billion worth of projects in 2025, according to [Data Center Watch](https://www.datacenterwatch.org/q1-2026), and policymakers alert to the public mood are starting to impose limitations on development. More than a dozen states are considering bans, and local moratoriums are in effect in places like Minneapolis and DeKalb County in Georgia. At the federal level, the GRID Act, a bipartisan bill in the US Senate, proposes to sever new data centers from public grids entirely. Some operators are already moving that way by trying to develop their own power generation. Rather than rushing to build new power plants, companies could find part of the solution to the crunch right under our noses—or, more precisely, in the transmission lines under our feet and above our heads. The existing system operates near its full capacity during only a small number of high-demand hours throughout the year. This means, some grid experts argue, that if data centers can limit the power they draw during those stretches, they won’t need to wait for big infrastructure upgrades or build their own off-grid generation. Indeed, a growing number of studies have shown there could be plenty of power available for data centers that can flex. A widely discussed [2025 report from researchers at Duke University](https://nicholasinstitute.duke.edu/publications/rethinking-load-growth) found that the US grid could offer an additional 76 gigawatts—about 5% of its entire capacity, and about enough to accommodate projected data-center growth in the US through 2030—to facilities that are willing to reduce their usage just 0.25% of the time. That’s about 22 hours a year. And when researchers from Princeton University and two grid-modernization companies looked at locations for new data centers in the PJM region, their [report](https://www.camus.energy/flexible-data-center-report), which was funded by Google, found that a 500-megawatt facility capable of flexing for less than 1% of the year could reach full operation three to five years faster than one that’s inflexible. Flexible power connections could also help data centers address some of their PR problems. By decreasing their draw at times of grid stress, for instance, they could avoid diverting power from where it’s most needed, thus boosting stability. By using existing capacity, they might be able to reduce the need for new fossil-fuel power plants and spread fixed costs over more electricity users, pushing prices down. The AI power pinch is attracting resources and research into strategies for grid flexibility overall, which could help negotiate a tricky period: Taken together with electric vehicles, air-conditioning, and other sectors, data centers are helping drive what analysts predict will be a [25% increase](https://www.icf.com/insights/energy/impact-rapid-demand-growth-us) in US electricity demand by 2030 compared with 2023 levels. Ideally, flexibility gives grid operators more control over the flow of electrons, making them leaders of a harmonious ensemble rather than hostages to inflexible electricity requirements. That will help them manage demand spikes across the entire system and deal more effectively with the intermittent nature of renewables like wind and solar. “Demand flexibility is incredibly useful for power grids,” says Johanna Mathieu, a grid expert at the University of Michigan. “It helps reduce electricity costs and improve grid reliability.” But while advocates see plenty of benefits, the concept brings complexity. For data centers, compromising on energy needs can be a hard sell. Flexibility requires utilities and grid operators, which tend to be operationally conservative, to change long-held practices. And some skeptics also say that flexibility distracts from the very real need to build more grid infrastructure faster, and could even pose risks to our electricity supply. Still, some technologists, grid operators, and utilities are hoping to show that flexibility works—not only in white papers or simulations but in real life. The poster children for data-center growth default toward *in*flexibility. Hyperscalers like Microsoft and Oracle have proposed enormous new centers, many of which would rely on off-grid, natural-gas-burning power plants. When xAI wanted to speed up the buildout of the Colossus site outside Memphis, Tennessee, it rolled up with gas turbines on flatbed trucks. The facility, now in operation, is facing blowback from regulators and residents about the spike it’s causing in emissions and other pollution. In any case, there aren’t enough gas turbines worldwide to meet the demand from data-center operators. One big obstacle for anyone demanding a lot of power is that our grids are mostly rigid. They’re designed to supply enough power to meet total demand when it’s highest, even if that’s for only a relatively small number of hours a year. That conservative approach is a simple route to reliability, but it means that the grid has quite a bit of headroom. “The grid is already overbuilt by a lot. If you were an airline running at 30% utilization, you would not buy more planes,” says Amit Narayan, the cofounder and CEO of GridCare, a company developing flexibility technologies, referring to a [2025 Stanford study](https://energy.stanford.edu/news/hidden-transmission-capacity-american-west) of transmission lines in western North America. “If you are running a grid at 30% utilization, there’s no scientific reason you can’t go to 60.” “If you were an airline running at 30% utilization, you would not buy more planes. If you are running a grid at 30% utilization, there’s no scientific reason you can’t go to 60.” To be fair, the idea of flexibility isn’t entirely foreign to grid operators. For decades, they’ve practiced a technique called demand response: When it looks as if demand will get too close to supply, as it might during a heat wave when many people turn on the AC at the same time, they call large commercial or industrial facilities and ask them to shut down parts of their operations. This method can help avoid the need to fire up so-called peaker plants, which run on fossil fuels, but it’s slow, imprecise, and hard to scale. In the 2000s, as the adoption of technologies like electric cars and solar panels presented new challenges, more internet-connected grids also provided new means of flexibility. Virtual power plants, or VPPs, offered a smarter, faster, more granular alternative. Electricity customers ranging from factories to homeowners with smart thermostats, solar panels, or big batteries would allow the utility to adjust their draw to help meet demand—often getting paid for their (frequently unnoticed) trouble. After the generative AI boom began with the release of ChatGPT in 2022, some companies began to see flexibility as a way to get data centers set up more easily, efficiently, and affordably. If they bring AI money into existing grids and reduce or defer the need for expensive upgrades, data centers could actually help spread out fixed costs so as to lower rates for other users. A study from Duke University published this past February, for instance, found that [flexibility could reduce rates by 0.5% to 2.8%](https://nicholasinstitute.duke.edu/articles/key-takeaways-data-center-flexibility-and-generation-capacity-over-next-decade). The trick is figuring out how data centers, notorious power hogs, can keep operating when their flexible connections are throttled. Flexibility specialists envision three possible ways. The simplest is for the new data center to install on-site backup power storage or generation to tap when the grid is maxed out—at their own expense, of course. A facility could also fill the gap by drawing on a VPP. The utility would turn down the electricity going to users who signed up for the VPP, and the data center would pay them for their flexibility. This method wouldn’t require any major infrastructure, but it would require the utility to have a big VPP program and to coordinate the exchange at a time when the grid was under stress. While VPPs exist to some extent in nearly 40 states, the rules governing them vary widely, and they are empowered to do more in some areas than in others. Finally, a data center could simply use less power at peak times. The conventional wisdom is that they won’t go for such limits, particularly when every number-crunching server can feel like a goose potentially laying little golden eggs. But some experts are betting that the value of getting up and running quickly is enough to change their minds. “There is a clear and growing trend,” says Ayse Coskun, chief scientist at Emerald AI. “Operators are increasingly willing to trade some level of flexibility for faster grid interconnection.” GridCare, a startup based in Silicon Valley, was one of the first companies to use flexibility to get data centers online quickly. Instead of looking at grids only in worst-case scenarios when electricity demand is highest, the company analyzes the system under all conditions, explains CEO Narayan, who studied smart grids at Stanford. It feeds every part of the grid—including power plants, lines, substations, and homes—into a generative AI model that creates a “digital twin” for different grid configurations. It then picks out results that could unlock capacity while maintaining reliability, and it feeds those into another model trained on the physics of electrical components like resistors and capacitors to make sure they’re realistic. GridCare found its first customer in the Silicon Forest, an area in the Pacific Northwest named for the trees that dominate the landscape and the IT industry that has more recently sprouted up there. The local grid needed more capacity to support more data centers. “Data centers wanted ‘speed to power,’” says Isaac Barrow, a manager of data-center relations at Portland General Electric, or PGE, the local power generator and distributor, “but transmission buildout is a long process that’s very costly.” In 2024, Aligned Data Centers came to PGE wanting to expand its operation in Hillsboro, Oregon, and PGE followed a recommendation from GridCare. Aligned will install a 31-megawatt battery, set to be in service in May 2027, and decrease its draw by up to that amount when the grid becomes congested. Bundled with other flexibility measures, that battery has allowed PGE to increase the capacity it can offer Aligned and other nearby operators by 80 megawatts without any new power plants. Though the buildout of data centers in Hillsboro has faced plenty of pushback from locals, Barrow points out that it could have the knock-on effect of lowering costs for ratepayers, because it spreads out the tab. Other companies are promoting different flavors of flexibility. Google [has been moving processing loads](https://cloud.google.com/blog/products/infrastructure/using-demand-response-to-reduce-data-center-power-consumption) from facilities in areas experiencing demand spikes to those in less stressed spots since 2023. It’s [signed agreements with five utilities](https://blog.google/innovation-and-ai/infrastructure-and-cloud/global-network/demand-response-data-center-milestone/), including the Tennessee Valley Authority and Indiana Michigan Power, that add as much as a gigawatt of flexibility. Voltus, a major VPP provider across the US and Canada, markets a “bring your own capacity” program in which a data-center company can fund a VPP nearby. The grid operator can use the VPP to decrease demand at busy times, and participants get a financial thank-you. “We can spin up new VPPs on the order of months,” says Emily Orvis, Voltus’s vice president of energy markets. In June, the company signed their [first such data-center deal](https://www.technologyreview.com/2026/06/03/1138350/virtual-power-plants-data-centers/): a three-year plan in which Google will bankroll a VPP in the PJM interconnection. Of all the approaches to flexibility, Emerald AI’s may be the most ambitious: asking data centers to dial into the grid’s needs. The company’s Conductor software, which can run on premises or in the cloud, builds on the research of chief scientist Coskun. Her group at Boston University showed in a pair of 2013 papers that a data center could watch the grid and help balance big power fluctuations, such as the intermittent effects of solar and wind power. By 2022, she and her colleagues had [tested their methods on a cluster of 36 research servers](https://www.bu.edu/peaclab/files/2024/08/zhang_TSUSC2022.pdf) and shown that the system could respect power limits without breaking the processes it was running. One of the most important questions for Conductor is deciding which AI processes can be slowed down to save energy without kneecapping performance. A lot of companies label their jobs by priority—a real-time chatbot query, for instance, might outrank something like a web search that’s part of a deep research project. When they don’t, Emerald AI tries to infer priority from the nature of the job. Conductor then analyzes the AI workload to determine how tweaking the power to a given processor will affect the performance and help meet the usage limits set by the grid operator. “The performance curve changes for different kinds of workloads,” says Coskun. “Each AI job is going to have a different location on that curve. Our intelligence is figuring out where you are on that curve.” Last year, Emerald AI began assessing the technology’s readiness for real-world use in a series of tests, raising the difficulty each time. The trials were carried out in partnership with the Data Center Flexible Load Initiative—a collaboration among tech companies like Google and Nvidia, utilities like Duke Energy, and grid operators like PJM that aims to [help establish a repeatable framework](https://www.epri.com/about/media-resources/press-release/rbbbpmk6zvt6exn9rgqlwlmrwhrhqwis) for power-flexible data centers. The first challenge was in Phoenix, a fast-growing computing hub. For the test, Conductor took control of a group of server racks laden with 256 Nvidia A100 GPUs—hardware that can use about as much power as around 170 US homes. When presented with a simulation of a busy grid, Conductor reduced the power to the chips by 25% for three hours, while maintaining acceptable computing performance. Emerald AI and its partners reported the results [in a paper in Nature Energy](https://www.nature.com/articles/s41560-025-01927-1) in December 2025. The next trial forced the system to juggle surprise grid fluctuations without advance warning and redirect AI jobs from a data center in Virginia to a less busy one in Chicago. Then, in London, Conductor took the reins of equipment beyond the main GPU processors and faced a more complicated mix of fluctuations, including very short and long bouts of congestion—plus the notorious teakettle effect. The progress so far shows that flexibility can work, at least in some situations, but only a small fraction of operators have pursued it as yet. “We’re just in the beginning innings of the game,” says Jesse Jenkins, one of the authors of the 2025 Princeton study and cofounder of Firma, a startup that works on data-center flexibility. “People are recognizing that this is a potential solution. The motivation is there; there are some bespoke examples. But there’s no uniform solution set that’s the default option, which is where we need to get.” While data centers are going up across the US, no place on Earth comes close to the accumulated computing muscle in Northern Virginia’s Data Center Alley. The region is home to around 500 compute-crunching facilities, which represent 13% of the entire world’s capacity; the next two hot spots, Beijing and Oregon, contain 6% each. There are proposals to build hundreds more facilities in Virginia, but [a government study found](https://jlarc.virginia.gov/landing-2024-data-centers-in-virginia.asp) that the state’s electricity demand will increase 183% (around 26 gigawatts) by 2040 if they all go forward, and supporting even half would be difficult. The power-flexible data center that Emerald AI, Nvidia, Digital Realty, and their partners are building in the suburb of Manassas could demonstrate how data centers can squeeze the power they need out of existing capacity. The facility, slated to come online later this year, is intended to give Conductor the chance to manage power at the largest scale yet and to respond to conditions on a live grid for the first time. In the UK demonstration, Conductor managed a 130-kilowatt AI cluster; in Manassas, it will pull the strings of a 96-megawatt hyperscale AI factory. Some degree of flex will play a key role as we transition away from fossil fuels and toward a future that has to juggle technologies like solar and wind power, batteries, and electric cars. For PJM, the Manassas facility points to a potential path through the current power crunch. “We think data-center flexibility, in different forms, will be essential for the reliable integration of data-center load over the short to mid term,” says Scott Baker, who manages demand-side markets at PJM. But not all grid experts are so sanguine. PJM’s market monitor, which oversees the grid operator, says there are no workarounds when it comes to adding capacity. “The notion that large amounts of data-center load can be added without adding new generation is magical thinking,” says Joseph Bowring, an economist and the head of PJM’s market monitor since 1999. One problem, he says, is that there’s no way to guarantee that a data center will actually take less power when demand is high. That is, absent any legal or regulatory push for flexibility or compliance, the utility won’t be able to step in to help prevent, say, a blackout. Utilities can rely on resources like power plants, but they can’t control or rely on data centers. “They do not want to be fully interruptible,” Bowring says of the facilities. Stephen Empedocles, an advisor for technology companies, views flexibility as more of a tool than a silver bullet. “These approaches are excellent for improving grid reliability and getting more out of the infrastructure we already have,” he says, “but they are optimization tools.” They’re not substitutes for the “generation, transmission, and distribution expansion that will still be required,” he continues. Flexibility advocates agree that over the long term, whether or not AI continues to boom, electrification will drive a need for more generation and transmission. Some degree of flex will play a key role in using grid infrastructure better as we transition away from fossil fuels and toward a future that has to juggle technologies like solar and wind power, batteries, and electric cars. A report published by the [International Renewable Energy Agency](https://www.irena.org/Publications/2026/Jan/Flexibility-for-a-secure-and-affordable-power-sector-transformation) in January 2026 found that grids around the world will need three times as much flexibility in 2030 as they had in 2019—and 10 times as much by 2050—to balance increasing demand with fluctuating supplies of renewable energy. The challenge of powering AI could provide just the spark we need to do the work of designing and building smarter, more flexible grids, says Coskun. “I think with a crisis like this, there’s no quick solution,” she says. “Sometimes a crisis like this creates an opportunity to do something differently.” *Amos Zeeberg is a freelance science and technology journalist based in Bucharest. He’s developing a book about technology networks, including electric grids.* ### Deep Dive ### Artificial intelligence ### 10 Things That Matter in AI Right Now MIT Technology Review's authoritative overview of the 10 technologies, emerging trends, bold ideas, and powerful movements in AI in 2026. ### A new US phone network for Christians aims to block porn and gender-related content Launching next week on T-Mobile's network, the cell plan takes a nuclear approach to online safety. ### Musk v. Altman week 1: Elon Musk says he was duped, warns AI could kill us all, and admits that xAI distills OpenAI’s models Musk kept his cool, and OpenAI’s lawyer bulldozed him with piercing questions about his motivations for suing the company. ### Three reasons why DeepSeek’s new model matters The long-awaited V4 is more efficient and a win for Chinese chipmakers. ### Stay connected ## Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more.