Sunday, May 26, 2024

Artificial intelligence could lower nuclear energy costs

Unlike fossil fuel-fired power plants, nuclear power plants provide large amounts of low-carbon electricity. But the expense of running these plants has made it difficult for them to stay open.

Researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory are building systems that could make nuclear energy more competitive using artificial intelligence. Argonne is midway through a $1 million, three-year project to explore how smart, computerized systems could change the economics.

Funded by the DOE Office of Nuclear Energy’s Nuclear Energy Enabling Technologies program, the project aims to create a computer architecture that could detect problems early and recommend appropriate actions to human operators. The technology could save the nuclear industry more than $500 million a year, Roberto Ponciroli, a principal nuclear engineer at Argonne, and colleagues estimate.

A typical nuclear plant can hold hundreds of sensors, monitoring different parts to make sure they are working properly. The job of inspecting each sensor – and also the performance of system components such as valves, pumps, and heat exchangers – currently rests with staff who walk the plant floor. Instead, algorithms could verify data by learning how normal sensor functions and looking for anomalies.

After validating the plant’s sensors, the artificial intelligence system will then interpret the signals from them and recommend specific actions. At a nuclear plant, computers could detect problems and flag them to plant operators as early as possible, helping optimize control and avert more expensive repairs down the line. At the same time, computers could prevent unnecessary maintenance on equipment that doesn’t need it.

“The lower-level tasks that people do now can be handed off to algorithms,” said Richard Vilim, an Argonne senior nuclear engineer. “We’re trying to elevate humans to a higher degree of situational awareness so that they are observers making decisions.”

Partnering with industry to develop testing scenarios, Argonne engineers have built a computer simulation, or “digital twin,” of an advanced nuclear reactor. While the system is designed to serve new reactor technologies, Vilim said, it’s also flexible enough to be applied at existing nuclear plants.

Currently, researchers are validating their artificial intelligence concept on the simulated reactor, and so far, they have completed systems to control and diagnose its virtual parts. The remainder of the project will focus on the system’s decision-making ability – what it does with the diagnostic data. Because an autonomous nuclear plant requires these varied functions, the end product of the Argonne team’s work is a system architecture that stitches multiple algorithms together.