US NREL investigates quantum computing in grid operations

US NREL investigates quantum computing in grid operations
Image: Atom Computing

The National Renewable Energy Laboratory (NREL) is partnering with US-based Atom Computing to explore how quantum computing can help optimise grid operations.

In the initiative Atom Computing’s atomic array quantum computing technologies have been incorporated into the NREL’s ARIES (Advanced Research on Integrated Energy Systems) research platform and its ‘hardware-in-the-loop’ testing to create what is described as “a first-of-a-kind quantum-in-the-loop” capability that can run certain types of optimisation problems on a quantum computer.

Initially, NREL and Atom Computing intend to explore how quantum computing can improve decision making on the re-routing of power between feeder lines that carry electricity from a substation to a local or regional service area in the event of switch or line downtime.

“Right now, operators primarily rely on their own experience to make this decision … but it doesn’t necessarily result in an optimal solution. We are evaluating how a quantum computer can provide better data to make these decisions,” says Dr Rob Hovsapian, a research advisor at NREL.

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He describes the new capability as an important step toward understanding how quantum computers can better balance energy loads across an electric grid.

“We are reaching the point where electric grids have more inputs and outputs than what our classical computing models can handle. By incorporating quantum computing into our testing platform, we can begin exploring how this technology could help solve certain problems.”

Optimisation problems such as managing supply chains and devising more efficient transportation routes are considered ‘killer applications’ for quantum computing as large-scale problems with numerous factors and variables involved.

Similarly power flows across an electricity grid, with multiple generators of variable weather and time dependent generation, which must then be routed and delivered to end users, is an example of a complex optimisation problem.

NREL’s ARIES platform is declared one of the most advanced in the US, allowing for research at the 20MW level, with the hardware-in-the-loop enabling testing at actual load levels to mirror real world conditions.