As countries around the world seek to reduce their carbon emissions, what if there were a way they could generate significantly more power from one of the fastest-growing sources of renewable energy, without the need to buy any expensive new equipment or clear more land?

Scientists at MIT say they’ve figured out how to do just that with wind power.

After testing complicated computer models, they’ve shown that adjusting the rotor blades of turbines at a wind farm — a change that would reduce the efficiency of an individual turbine if it stood alone — can significantly increase the overall power produced by the wind farm.

Typically, wind farm operators focus on achieving the maximum efficiency of individual turbines. Each turbine has its own sensors that measure the direction and speed of the wind, enabling their blades to rotate as close to the wind as possible and capture the maximum amount of energy.

But now scientists have found that, actually, they would be better off orienting the blades of some turbines at a sub-optimal angle to the wind, so each turbine generates slightly less bumpy air, known as a turbulent wake, for turbines downwind. Changing the angle of the blades reduces how much a turbine disturbs the flow of air to those behind it, ultimately increasing their collective output.

If existing wind farms around the world used this method, which the scientists published this month in the journal Nature Energy, the additional electricity could together power the equivalent of 3 million homes in the United States and generate nearly a billion dollars in additional revenue each year for the industry, they said.

Given that wind last year accounted for more than 9 percent of the nation’s electricity, as well as an increasing share of the overall energy portfolio of Massachusetts, squeezing more power from such renewable energy projects could make a significant difference in reducing emissions, the scientists said.

That will become even more important as the state races to reduce its emissions by 50 percent below 1990 levels by the end of the decade, as required by a law passed last year, and the Biden administration seeks to live up to its pledge to cut the nation’s emissions by a similar amount.

“Given the scale of wind deployment needed to achieve state and federal climate goals, we need optimal wind farm performance to ensure efficient, rapid decarbonization,’’ said Michael Howland, an assistant professor of civil and environmental engineering at MIT, and the paper’s lead author. “Our method resulted in significant energy gains over standard industry operations, and, importantly, it can be instituted with minimal cost.’’

Howland and his colleagues’ formula relies on a special kind of physics that allows them to predict the amount of power each turbine can produce, based on wind speed and direction, and the angle in which the rotor blades are facing. Without requiring any new hardware or changes in the location of the steel towers, their method helps find the ideal orientation of the blades.

Modern turbines are designed to detect wind speed and direction, enabling their nacelle — the top portion of the turbine that connects the blades to the tower — to rotate around the tower to better catch the wind. Typically, their software moves them to be as close to the wind as possible.

The scientists say their algorithm shows that more energy is produced by wind farms when some turbines are pointed at closer to a 20-degree angle away from where they would be most efficient if they were operating independently. That change in angle means less impact on the turbines downwind, increasing their overall energy output. Reducing wake turbulence throughout a wind farm improves the collective performance, as the scientists’ algorithm allows wind farms to steer the turbulent wake in the most efficient way possible through a warren of turbines.

In several months of testing their ideas at a wind farm in India, the scientists said, their model increased electricity output by as much as 32 percent, under optimal wind conditions.

“The computer model was able to accurately predict the real wind farm power gain, resulting from the collective control approach that we implemented at the farm, for most conditions that we studied,’’ Howland said.

But his team found there were times when there wasn’t a benefit of collective control. On some days, when winds were too strong or blowing in the wrong direction, they let the turbines operate independently. Over the course of several months of testing their algorithm in India, the scientists found that the overall energy output from the turbines they studied increased by an average of about 1.2 percent.

“We are not talking about huge increases in power for any given turbine, but when multiplied over many turbines in a wind farm, and over many farms, it could become very significant,’’ said Charles Meneveau, a professor of mechanical engineering at Johns Hopkins University in Baltimore, who wasn’t involved in the research but studies the physics of wind flows.

He added: “I definitely think industry should implement such control strategies to experiment with them and see what works.’’

Julie Lundquist, an associate professor of atmospheric and oceanic sciences at the University of Colorado in Boulder who also wasn’t involved in the study, said one potential concern about such “wake steering’’ of air through a wind farm is that it could stress the turbines — each of which costs millions of dollars to build — and potentially shorten their service lives.

“Considerations of the loads on turbine structures is important,’’ she said.

The authors of the paper called for additional studies that would look closer at the impact of their algorithm on turbines, but they said their research suggests there’s “no risk of catastrophic failures.’’

“There could be long-term, cyclical failures,’’ Howland said. “We need improved studies to model the loads.’’

Howland, however, said the benefits of the method appear to outweigh the potential downsides.

Among those benefits: Their algorithm could allow developers to build smaller, more densely arranged wind farms, using less land or ocean bottom, to produce more electricity, he said. Building fewer turbines would save developers millions of dollars on land and equipment, while smaller footprints could make it easier to obtain permits.

Howland estimated that a 1.2 percent increase in the electricity produced by the world’s wind farms would be equivalent to the installation of 3,600 new turbines, amounting to about $950 million in additional revenue per year for the industry.

The benefits for offshore wind could be even greater, Howland said, noting that the impact of wake turbulence to downwind turbines can be greater on the ocean than on land.

“That’s why we need to develop these approaches and adopt them as soon as possible,’’ he said.

Officials at Vineyard Wind and Mayflower Wind, both of which are planning to build wind farms in the waters off southern New England in the coming years, said they’re interested in learning more about the research.

“[Our] technical team is reviewing the data and will consider it when looking at construction options, when those are determined,’’ said Daniel Hubbard, general counsel for Mayflower Wind, which has leased more than 127,000 acres of federal waters south of Martha’s Vineyard to build a massive wind farm.

Ben Hallissy, an aerospace engineer at the US Department of Energy’s Wind Energy Technologies Office, said similar modeling by the federal government is “showing incredible results.’’

“Any technology that can increase energy production in a cost-efficient way can mean more clean energy generation, and more money for plant operators,’’ he said.

Howland urged wind developers to review the MIT research and consider adopting the team’s suggestions before they build new wind farms.

“It’s critically important we do this now, as we embark on building much more offshore wind,’’ he said. “We need to ensure that our future wind farms maximize efficiency to increase the pace of decarbonization.’’

David Abel can be reached at david.abel@globe.com. Follow him on Twitter @davabel.