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Modern electric grids are increasingly exposed to disruptions that can occur simultaneously. Cyberattacks, equipment failures, extreme weather, wildfires and physical attacks can each affect electricity delivery, but several incidents happening at once create a much more complicated problem. Grid operators must rapidly understand how one failure will affect another while deciding how to prevent outages from spreading.
A new research project funded by the U.S. Air Force Research Laboratory (AFRL) will explore whether quantum computing can make that analysis faster. Under a two-year, $7 million contract, Eaton will work with Infleqtion and Pennsylvania State University to develop tools combining quantum computing, machine learning and advanced visualization to identify vulnerabilities and help operators respond to complex disruptions.
The project focuses on what power engineers call contingency analysis. Before a failure occurs, operators simulate different combinations of damaged transmission lines, generators and other grid components to determine whether electricity can continue flowing safely. Current North American reliability standards include N-2 planning, which requires transmission systems to remain operational following two successive failures.
According to Interesting Engineering, the new research aims to examine scenarios involving several failures occurring at once. The difficulty is computational: as more possible failures are added, the number of combinations that must be evaluated increases rapidly. Quantum computing is being investigated as a way to process these complex scenarios more efficiently than conventional methods alone.
Rather than replacing existing computers, the project will use a hybrid quantum-classical approach. Conventional computing systems will continue handling tasks they perform efficiently, while quantum processors will be tested on optimization problems where they may offer advantages. Machine-learning algorithms will help identify patterns and prioritize vulnerabilities, while visualization tools will present the results in a form grid operators can use during planning or emergencies.
The company will provide quantum hardware, while researchers will develop new algorithms, optimize quantum circuits and investigate methods for reducing computational errors, which is a significant limitation of current quantum machines. The technologies will be evaluated across different quantum hardware rather than being designed around a single processor.
The defense implications are significant because electricity infrastructure supports military installations, communications networks, transportation systems and other critical services. A coordinated cyberattack or physical disruption affecting several grid components simultaneously could create cascading consequences. Faster contingency analysis could help operators identify vulnerable combinations beforehand and determine how to reroute power or respond when several systems fail together.
At the end of the 24-month program, the team plans to demonstrate a proof of concept using currently available quantum hardware. The project will test whether quantum-enabled analysis can move beyond laboratory experiments and provide practical support for grid planning, everyday operations and emergency response.
