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Power shift: How CMU is helping shape America's energy evolution
As AI models grow more powerful, their appetite for energy also increases, straining an aging and outdated grid and prompting urgent questions about infrastructure, security and access. From reimagining AI data centers to modernizing and securing the electric grid, Carnegie Mellon University researchers are working on practical solutions to pressing challenges in how the U.S. produces, moves and secures energy.
The AI-energy connection
While AI drives economic growth and scientific breakthroughs, it's also straining the energy infrastructure that is currently in place. The good news? AI can help solve that problem.
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Zico Kolter
'As work across Carnegie Mellon shows, AI has the potential to drastically improve our energy consumption by assisting in developing more efficient techniques for grid operation, building better materials for batteries, and potentially even truly revolutionizing energy by accelerating the development of technologies like nuclear fusion,' said Zico Kolter, head of the Machine Learning Department in CMU's School of Computer Science. 'These are all big bets, to be clear, and advancing science is never a sure thing, but AI at its best can be a unique enabler of so many beneficial downstream technologies.'
Getting into the fast lane
Carnegie Mellon is pioneering the use of AI to modernize the electric grid to meet current and future needs.
'Transmission moves power from the locations where it is produced to the locations where it is needed, and the U.S. urgently needs more capacity,' said M. Granger Morgan, the Hamerschlag University Professor of Engineering at CMU. 'The Department of Energy predicts the country will need to more than double high-voltage transmission capacity over the next several decades. At the same time the construction of new long-distance transmission has stalled. Breaking the logjam that often makes it impossible to build new transmission capacity without placing an unacceptable burden on consumers' electric bills is a major challenge.'
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M. Granger Morgan
CMU researchers are developing 'AI fast lanes' — special lanes on the electricity "highway" just for clean energy projects that power AI and data centers. These fast lanes would let clean energy projects connect to the grid faster, ensure the electricity stays affordable and reliable, help protect the environment and make things fair for everyone. These innovations are crucial as the U.S. grid integrates more intermittent renewable sources like wind and solar.
Securing the future
As the grid becomes more digitized, security gaps widen — unless we address them. CMU's CyLab Security and Privacy Institute and Electrical and Computer Engineering department in the College of Engineering are working to stay ahead of the threat curve, using AI to anticipate and neutralize cyberattacks before they cause widespread disruption.
'AI-driven energy expansion is a prime opportunity to harden our infrastructure against cyber threats,' said Audrey Kurth Cronin, director of the Carnegie Mellon Institute for Strategy and Technology. 'Upgrading energy infrastructure for AI offers a once-in-a-generation opportunity to replace vulnerable legacy systems with inherently more defensible technologies.'
CMU researchers Lujo Bauer, Larry Pileggi and Vyas Sekar are calling on the research and policy communities to develop more comprehensive and accurate grid evaluation frameworks and datasets, and for updating threat models and grid resiliency requirements to match cyber attackers' realistic capabilities.
As part of their research, they interviewed 18 grid security specialists and analyzed four major threats, from overloading smart devices to taking over entire power plants. They found wide disagreement on how likely or dangerous these threats are.
'Our work has shown that inconsistencies in threat assessments occur because of ad hoc simulation and modeling methodologies, as well as dataset errors,' Sekar said. 'This shows the need for the creation of standardized public toolkits and datasets and for recommending ways to increase the accuracy of evaluations. This will enable us, as well as other researchers, to develop more rigorous foundations for securing tomorrow's electric energy grid.'
Policy that meets the moment
CMU's expertise extends beyond the labs and code to shape public policy through systems modeling, data-driven decision making and collaboration with government and industry.
Ramayya Krishnan, director of the AI Measurement Science and Engineering Center, has said CMU's ability to look at issues from a systems standpoint is what makes the university uniquely positioned to address the complex challenges and opportunities that lie at the intersection of energy and AI.
"That's our sweet spot," Krishnan said. "At CMU, we have strength in all the different layers. We have deep expertise in energy, deep expertise in AI and deep expertise in public policy, and we understand how these elements come together."
Carnegie Mellon University brings together experts across disciplines to address real-world challenges and create lasting impact. From advancing technology to improving lives, CMU is committed to research, innovation, and education that drives meaningful change in society, industry, and communities around the world.
