A project led by the Department of Energy’s SLAC National Accelerator Laboratory will combine artificial intelligence with massive amounts of data and industry experience from a dozen U.S. partners to identify places where the electric grid is vulnerable to disruption, reinforce those spots in advance and recover faster when failures do occur.
A project led by the Department of Energy’s SLAC National Accelerator Laboratory will combine artificial intelligence with massive amounts of data and industry experience from a dozen U.S. partners to identify places where the electric grid is vulnerable to disruption, reinforce those spots in advance and recover faster when failures do occur.
The eventual goal is an autonomous grid that seamlessly absorbs routine power fluctuations from clean energy sources like solar and wind and quickly responds to disruptive events – from major storms to eclipse-induced dips in solar power – with minimal intervention from humans.
“This project will be the first of its kind to use artificial intelligence and machine learning to improve the resilience of the grid,” said Sila Kiliccote, director of SLAC’s Grid Integration, Systems and Mobility lab, GISMo, and principal investigator for the project. “While the approach will be tested on a large scale in California, Vermont and the Midwest, we expect it to have national impact, and all the tools we develop will be made available either commercially or as open source code.”
Read more at DOE / SLAC National Accelerator Laboratory
Image Credit: Jvimal via Wikimedia Commons
