Energy experts at PNNL are helping 56 states and territories deliver their state energy security plans (SESPs) through a transparent and collaborative review process.
Pacific Northwest National Laboratory, supported by the Department of Energy’s Grid Deployment Office, is leading a technical assistance initiative to help utilities test and deploy alternate GPS timing solutions.
Pacific Northwest National Laboratory is partnering with the U.S. Department of Homeland Security’s Cybersecurity and Infrastructure Security Agency to develop and operate the Control Environment Laboratory Resource
PNNL and ORNL are working together on Digital Twins to modernize the U.S. hydropower plant fleet, which will reduce operating costs, improve reliability, reduce downtime, enhance grid resiliency, and reduce environmental impacts.
In January 2024, CESER—in partnership with GDO, NASEO, and PNNL—created a set of state energy security cohorts to support the coordination and technical development of state energy security planning, assessment, and mitigation.
Physics-informed machine learning (PIML) is a modeling approach that harnesses the power of machine learning and big data to improve the understanding of coupled, dynamic systems.
PNNL combines AI and cloud computing with damage assessment tools to predict the path of wildfires and quickly evaluate the impact of natural disasters, giving first responders an upper hand.
The RD2C laboratory-directed research initiative seeks to develop resilient, adaptive, and intelligent sensing and control algorithms through the observational understanding and characterization of CPSs under adverse conditions.
