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ORNL researchers modeled how hurricane cloud cover would affect solar energy generation as a storm followed 10 possible trajectories over the Caribbean and Southern U.S. Credit: Andy Sproles/ ORNL,U.S. Dept. of Energy

ORNL researchers modeled how hurricane cloud cover would affect solar energy generation as a storm followed 10 possible trajectories over the Caribbean and Southern U.S.

Sangkeun “Matt” Lee received the Best Poster Award at the Institute of Electrical and Electronics Engineers 24th International Conference on Information Reuse and Integration.

Lee's paper at the August conference in Bellevue, Washington, combined weather and power outage data for three states – Texas, Michigan and Hawaii –  and used a machine learning model to predict how extreme weather such as thunderstorms, floods and tornadoes would affect local power grids and to estimate the risk for outages. The paper relied on data from the National Weather Service and the U.S. Department of Energy’s Environment for Analysis of Geo-Located Energy Information, or EAGLE-I, database.

Kevin Robb, a staff scientist at the Department of Energy’s Oak Ridge National Laboratory, is taking what he learned from developing the Liquid Salt Test Loop—a key tool in deploying molten salt technology applications

Thanks in large part to developing and operating a facility for testing molten salt reactor (MSR) technologies, nuclear experts at the Energy Department’s Oak Ridge National Laboratory (ORNL) are now tackling the next generation of another type of clean energy—concentrating ...