The models were built and deployed by NOAA's Environmental Modeling Center in coordination with the National Weather Service. A spokesperson for the service, Erica Grow Cei, ...

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...

In recent years, power consumption by machine learning technologies, represented by deep learning and generative artificial ...

With such increased predictive knowledge of solar systems, these anomaly detectors can significantly reduce costs of O&M, a major component of project economics in solar development. There is great ...

The software tool developed by Stony Brook University uses self-supervised learning to detect long-term solar equipment damage weeks or years before manual inspections find it.

US researchers say a self-supervised machine-learning tool can identify long-term physical defects in solar assets weeks or years before conventional inspections, potentially reducing operations and ...

Using AI and machine learning as transformative solutions for semiconductor device modeling and parameter extraction.

CHENNAI: THE Tamil Nadu Power Distribution Corporation Limited (TNPDCL) secured the top prize among discoms for innovation at the national conference on use of AI and machine learning in power ...

There is more than one way to describe a water molecule, especially when communicating with a machine learning (ML) model, says chemist Robert DiStasio. You can feed the algorithm the molecule's ...

Reinforcement learning algorithm enables hydraulic power without power switching complications, enabling improved energy ...

Artificial intelligence can transform healthcare workflows, but it is energy intensive, and organizations need to be prepared for a change in energy needs.