Insider Brief
- IonQ and Oak Ridge National Laboratory demonstrated the use of a quantum-classical hybrid system to address the Unit Commitment problem in electricity generation scheduling.
- The project, part of the Department of Energy‘s GRID-Q initiative, optimized scheduling for 26 power generators over 24 time periods using IonQ’s 36-qubit Forte Enterprise quantum computer.
- IonQ’s results point to quantum computing’s potential for solving large-scale grid challenges as systems scale, with broader implications for industries like logistics and finance.
IonQ has taken a step toward solving one of the power industry’s most complex problems using quantum computing.
The Maryland-based company said this week it successfully applied its quantum-classical hybrid system to optimize electricity generation scheduling, known in the industry as the Unit Commitment problem. In a project with Oak Ridge National Laboratory and the U.S. Department of Energy, IonQ used its 36-qubit Forte Enterprise quantum computer alongside classical computers to find new solutions for managing 26 power generators across 24 time intervals, according to the company.
The Unit Commitment challenge involves deciding which power plants should run and when, in order to meet forecasted electricity demand at the lowest possible cost. The problem grows more complicated as grids integrate more renewable sources like solar and wind, which are not always predictable, alongside traditional generators such as nuclear and natural gas plants. Mistiming generation can lead to expensive oversupply or shortages.
IonQ’s work, part of the DOE’s broader GRID-Q project, marks a milestone in applying quantum tools to real-world energy systems. The project is led by Oak Ridge and includes academic and private sector partners. IonQ is one of just two quantum firms involved in the multi-year initiative focused on developing scalable quantum algorithms for grid optimization.
IonQ said its approach demonstrated the feasibility of using quantum devices to address grid scheduling problems that are traditionally handled with complex classical computing models. According to Oak Ridge, the test case shows that ion-trap quantum devices could play a role in managing future grids as quantum technology improves. The research team plans to continue testing the approach as IonQ scales its systems.
“This demonstration marks a significant milestone in applying quantum computing to real-world energy challenges. We are proud to be partnering on this ground-breaking work with ORNL and the DOE,” Niccolo de Masi, CEO of IonQ, said in a statement. “As our systems scale to thousands and millions of qubits, we expect to solve grid optimization challenges at a scale that classic computing methods cannot match.”
The company believes that systems with 100 to 200 high-accuracy qubits, which it expects by 2026, will be capable of solving grid-level Unit Commitment problems with more precision than current methods. Today, over 60% of energy used in U.S. electricity generation is lost before it reaches end users, according to the U.S. Energy Information Administration, making improved scheduling and optimization a potential source of major savings.
Beyond energy, IonQ said the same optimization techniques demonstrated here could benefit industries such as logistics, financial modeling, and manufacturing, where large-scale scheduling and resource allocation are core challenges.
This latest announcement builds on previous collaborations between IonQ and Oak Ridge. The two have partnered on quantum algorithm development, noise-tolerant computing, and hardware design. IonQ is also involved in a $22 million project with EPB of Chattanooga to improve grid operations using quantum methods.
Founded in 2015, IonQ has positioned itself as a leader in the race to bring quantum computing into practical use. Its quantum systems are already available on major cloud platforms including Amazon Web Services and Microsoft Azure. The company has partnered with firms ranging from NVIDIA to AstraZeneca.
According to IonQ, its goal is to deliver quantum computers with 2 million qubits by 2030, far beyond the dozens of qubits available today. The company also aims to play a leading role in developing quantum networking technology for the future quantum internet.
“This case study, completed by ORNL in partnership with IonQ, demonstrated the feasibility of using an ion-trapped quantum computing device to solve the Unit Commitment problem in the power grid,”” noted Suman Debnath, leader of ORNL’s contributions to the project. “As the quantum device scales, concurrent research is intended to test how the application performance can gain a quantum advantage.”
