Jul 28, 2023 - Climate

How quantum computers will be used to improve our electrical grid

Illustration of a computer chip as an atom.

Illustration: Aïda Amer/Axios

Some of the most powerful computers in the world are being unleashed to help keep your lights on.

Details: Atom Computing, a California-based company building quantum computers, last week announced it's working with Golden's National Renewable Energy Laboratory (NREL) on a project to optimize the country's electrical grid.

  • The project is based out of NREL's Boulder campus.

Why it matters: The research could be useful in helping avoid major issues like blackouts by improving the grid's resiliency at a time when demand for electricity is increasing.

  • Products like electric vehicles are putting additional strain on the grid, and power-generating resources like wind and solar mean those grids are more complex.

The big picture: The country's electrical grid is in desperate need of modernization, facing increased strain from energy needs to keep people cool with hot temperatures this summer, reports Axios' Emily Peck.

Zoom in: Rob Hays, CEO of Atom Computing, tells us his company's tech is being used by an NREL platform that allows testing on a simulation of the country's power grid.

Details: The initial research phase will look at how quantum computing can improve the time it takes to reroute power between feeder lines, which carry electricity. Right now, those are human decisions.

  • "We are evaluating how a quantum computer can provide better data to make these decisions," Rob Hovsapian, a research advisor at NREL, said in a statement.

The intrigue: Hays tells us the company is building quantum computers for NREL with systems that can be scaled up faster than other types of quantum computers.

Of note: These computers use qubits (quantum bits) as their fundamental unit, allowing them to process information in a fraction of the time it would take a classic computer.

  • The more qubits a computer has, the more useful it is in helping solve complex problems.
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