Scientists examine use of AI to lower nuclear energy cost

Business Technology

Notably, nuclear power plants generate large amounts of electricity without causing pollution to the planet. But the cost of operating nuclear power plants has made it difficult to keep them. In the U.S. clean energy economy, if nuclear energy has to play a role, costs must come down.

In a new development, scientists at the Argonne National Laboratory, U.S. Department of Energy are using AI, to devise systems that could make nuclear energy more competitive.

From operational perspective, nuclear power plants are expensive, firstly, they require uninterrupted monitoring and maintenance to ensure stable power generation and safety.

Currently, researchers at Argonne are mid-way of a three-year US$ 1 million project to find how computerized systems could change the production.

“At present, operation and maintenance costs conform to the large site crews and extensive upkeep of nuclear units,” stated one of the principal scientists at Argonne. The autonomous operation of nuclear power plants can help improve profitability, and also assist the concept of deployment of advanced reactors.

Meanwhile, the objective of the project is to develop a computer architecture for early detection of problems, and recommend appropriate action for human operators. If the technology is successful, it would result into savings of more than US$ 500 million a year for the nuclear industry.

Importantly, a typical nuclear plant is capable of handling hundreds of sensors, wherein all of them are aligned to monitor different parts to make sure they are functioning properly.

In fact, for work systems, where decisions are based on data, it is important to know that the data is reliable, stated the principal scientist.

Sensors, like any other part, can degrade. Therefore, it is crucial to know the functioning of sensors.

Edward Turner

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