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

PNNL’s integrated software systems (FRAMES, MEPAS, MetView, APGEMS, CAPP) allow users to assess the environmental fate and transport of contaminants—and the potential impacts on humans and the environment—in a systematic, holistic approach.

PNNL administers two research buoys for the U.S. Department of Energy that allows collection of wind meteorological and oceanographic data off the nation's coasts.

PNNL and the United States Geological Survey are partnering to develop a buoy-based radar system capable of measuring bird and bat abundances and behaviors at offshore locations.

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.

A software suite for working with neutron activation rates measured in a nuclear fission reactor, an accelerator-based neutron source, or any neutron field to determine the neutron flux spectrum using a generalized least-squares approach.

PNNL researchers developed and manage the online database Tethys to actively collects and curates information on the environmental effects of wind and marine energy.

PNNL wind energy experts led a project to review existing literature focusing on the technical evaluation of offshore wind energy transmission through potential points of interconnection at the West Coast.

Pacific Northwest National Laboratory and National Renewable Energy Laboratory conducted a two-year study to investigate the potential of floating offshore wind to help meet growing energy needs on the U.S. West Coast.