The project received an Innovative and Novel Computational Impact on Theory and Experiment (INCITE) award, a highly competitive U.S. Department of Energy Office of Science program.
Pacific Northwest National Laboratory researchers used machine learning to explore the largest water clusters database, identifying—with the most accurate neural network—important information about this life-essential molecule.
PNNL has earned “Best Paper” at an international resilience conference for research on hydropower’s capabilities and constraints in the event of extreme events, like hurricanes and rolling blackouts.
Pumped-storage hydropower offers the most cost-effective storage option for shifting large volumes of energy. A PNNL-led team wrote a report comparing cost and performance factors for 10 storage technologies.
Researchers at PNNL used key metrics to develop visualizations that show how the combined effects of climate change on hydropower and load influence the frequency, duration, and severity of power shortfalls.
