A flexible arrangement for data center energy consumption, compared to an inflexible one, would produce cost savings of up to 5 percent in Texas, 4 percent in the Mid-Atlantic region, and 2 percent in the western U.S. states, a new study by researchers at the Massachusetts Institute of Technology found.
"The number of U.S. data centers is growing, largely to power artificial intelligence programs. That has led to concern about the environmental consequences of data centers — and their impact on the energy grid itself. What will happen if scores of new data centers come online?," a post on MIT's website asks. "A new study by MIT researchers indicates that the impact of data centers could vary significantly, depending on how their energy use is structured," the post by MIT writer Peter Dizikes notes.
Specifically, if data centers move a significant portion of their energy consumption to non-peak hours, it might actually help lower average energy costs.
The environmental impact, in terms of type of energy consumed, would differ by location, with some places likely seeing a greater buildout of renewables and others experiencing a relative increase in fossil fuel use, Dizikes notes.
“The key with data centers is: How can we add them to the network without adding a lot to our peak usage?” said Christopher Knittel, an economist in the MIT Sloan School of Management and co-author of a new paper detailing the study. “One way for data centers to do that — to add to average usage but not the peak usage — is if they provide some grid flexibility during those high-cost periods. And that’s what we’ve been interested in understanding.”
The paper finds that a flexible arrangement for data-center energy consumption, compared to an inflexible one, would produce cost savings of up to 5 percent in Texas, 4 percent in the Mid-Atlantic region, and 2 percent in the western U.S. states.
To achieve that, data centers would have to move more than 20 percent of their consumption -- sometimes more like 50 percent -- to non-peak hours.
The paper, “Flexible Data Centers Reduce Power System Costs But Can Increase Emissions,” was published in the journal iScience.
The authors are Juan Ramon L. Senga, a postdoc in MIT’s Center for Energy and Environmental Policy Research; Shen Wang, a postdoc in MIT’s Center for Energy and Environmental Policy Research; and Knittel, who is the George P. Schultz Professor at MIT Sloan and the associate dean for climate and sustainability at MIT.
To conduct the research, the scholars extensively simulated scenarios in which data centers expand, using the so-called “Gen X” model of the U.S. power grid, for a year’s worth of energy use, MIT said.
The study focused on the grid systems in three areas: Texas, the Mid-Atlantic region, and the “Western Interconnect,” comprising the 11 large western states in the lower 48 states of the U.S. The researchers studied these regions because they collectively host most of the country’s data centers -- about 82 percent of U.S. data centers by 2030, according to one analysis.
"A bit counterintuitively, the researchers found that adding data centers could lower energy costs in some scenarios," wrote Dizikes.
Typically, about 60 percent of grid expenses are fixed costs, like power lines, while about 40 percent consists of energy costs. Adding data centers to the grid could, in effect, apportion the fixed costs over a higher volume of energy use, MIT said.
"But there is a catch. Lower costs might only happen if data centers increase their average consumption faster than their peak-hours consumption, when energy is most expensive. As it happens, most data centers do have flexibility built into their energy-use patterns, since they usually run at about 80 percent capacity," wrote Dizikes.
In the study’s modeling, that flexibility often consists of shifting use from early-morning and early-evening peaks, to more midday energy consumption, when the energy load is lower and solar is at full capacity. The simulations show this makes a difference.
“There are two dimensions that data centers have to make decisions about,” Knittel says. “One is how much of their load in any one time period is flexible. And two, how many hours, plus or minus, can they move that computation?”
Additionally, data centers have different amounts of flexibility based on the types of AI-related computation they host, MIT said. Data centers being used for AI training data tend to consume energy at a steady rate, but as a result could provide more flexibility for shifting power loads compared to inference data centers, which are used more for online search queries. In the latter case, consumption is driven more by end-user Internet habits.
Overall, Knittel emphasizes, the magnitude of cost savings suggested by the study, ranging from 2 percent to 7 percent, is significant.
“Three percent is a big number,” Knittel says. “When you’re talking about the grid, 3 percent or 6 percent doesn’t sound like a lot. But when you’re multiplying it by 100 billion dollars, it becomes real money.”
The research received support from the Future Energy Systems Center of the MIT Energy Initiative.
