PNNL’s pioneering CETC project with regional universities demonstrates transactive controls among multiple commercial buildings and devices for energy efficiency and grid reliability.

The Data-Model Convergence (DMC) Initiative is a multidisciplinary effort to create the next generation of scientific computing capability through a software and hardware co-design methodology.

To help regulators identify a clear pathway to implement policy targets or mandates, PNNL researchers have provided a self-assessment tool.

The Grid Storage Launchpad (GSL) is a national capability for energy storage research funded by the Department of Energy Office of Electricity and located on the Pacific Northwest National Laboratory (PNNL) campus in Richland, Washington

PNNL deploys advanced drone systems to tackle the nation’s most pressing challenges in energy, environmental remediation, and national security.

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 is working on behalf of the U.S. Department of Energy to create a prototype system that enables homes to help provide services to the power grid while delivering economic benefits to residents.

PNNL creates immersive software experiences to meet a variety of challenges. One such challenge in science, technology, engineering, and mathematics (STEM) education is providing quality computer science education for all students.