PNNL researchers say that offshore wind energy can add value to the electric grid, beyond just the power it can produce, if locations and strategies are optimized.
PNNL’s longstanding grid and buildings capabilities are driving two projects that test transactive energy concepts on a grand scale and lay the groundwork for a more efficient U.S. energy system.
PNNL researchers have shown an improved binarized neural network can deliver a low-cost and low-energy computation to help the performance of smart devices and the power grid.
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.
Researchers at PNNL have developed a bacteria testing system called OmniScreen that combines biological and synthetic chemistry with machine learning to hunt down pathogens before they strike.
PNNL is one of the collaborating partners on a new grid-scale solar and energy storage installation near the PNNL campus in a project led by Energy Northwest.
PNNL’s new Smart Power Grid Simulator, or Smart-PGSim, combines high-performance computing and artificial intelligence to optimize power grid simulations without sacrificing accuracy.
The MIT-sponsored competition encourages community approaches to developing new solutions for analyzing graphs and sparse data; PNNL has placed a winner in each year.
In a new video series, PNNL is highlighting six scientific and technical experts in the national security domain throughout the fall. Each was promoted to scientist and engineer level 5 earlier this year.
James A. Ang, a PNNL computing expert, was recently invited to moderate a panel in a virtual workshop focused on federally funded research and development on software for heterogeneous computing.
PNNL researchers established an Internet of Things Common Operating Environment (IoTCOE) laboratory to explore the risks associated with IoT connectivity to the internet, the energy grid and other critical infrastructures.
Lauren Charles, a PNNL senior data scientist, has joined the editorial board of Pathogens. Pathogens is an international peer-reviewed open access journal of pathogens and pathogen-host interaction.
PNNL researchers used machine learning to develop a tool for a nonprofit to identify orthopedic implants in X-ray images to improve surgical speed and accuracy.
The American Society for Quality (ASQ) has recognized Laboratory Fellow and Pacific Northwest National Laboratory (PNNL) Statistician Greg Piepel with the William G. Hunter Award.
PNNL team has developed and implemented a generalizable computational framework to study the resilience of the multilayered London Rail Network to the compound threat of intense flooding and a targeted cyberattack.