More than 100 million smart meters have been installed in the U.S. to record and communicate electric consumption, voltage, and current to consumers and grid operators. LLNL has developed GridDS to help make the most of this data.
Topic: Critical Infrastructure
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LLNL’s cyber programs work across a broad sponsor space to develop technologies addressing sophisticated cyber threats directed at national security and civilian critical infrastructure.
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Highlights include power grid challenges, performance analysis, complex boundary conditions, and a novel multiscale modeling approach.
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Highlights include response to the COVID-19 pandemic, high-order matrix-free algorithms, and managing memory spaces.
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AI/ML | Biology/Biomedicine | Computational Math | Computational Science | Critical Infrastructure | Cyber Security | Data Movement and Memory | Data Science | Deep Learning | Discrete Mathematics | Emerging Architectures | HPC Systems and Software | Open-Source Software | Performance, Portability, and Productivity | Resource and Workflow Management
LLNL bested more than two dozen teams to place first overall in Challenge 1 of the DOE Grid Optimization Competition, aimed at developing a more reliable, resilient, and secure U.S. electrical grid.
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Responding to a DOE grid optimization challenge, an LLNL-led team developed the mathematical, computational, and software components needed to solve problems of the real-world power grid.
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