New approach allows nonexperts to optimize control of a building's energy systems without adding computing power or proprietary software.

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.

Ken Geelhood is a nuclear engineer who is studying how the challenging conditions of a nuclear reactor affect the reliability of fuel.

PNNL data scientists Ján Drgoňa and Draguna Vrabie are working to reduce deployment costs of advanced energy control systems for buildings.

The PNNL-developed VOLTTRON™ software platform’s advancement has benefited from a community-driven approach. The technology has been used in buildings nationwide, including most recently on a university campus.

PNNL employs deep learning strategies to advance Model Predictive Control (MPC), a highly promising solution for intelligent building operations.

PNNL’s Intelligent Load Control technology manages and adjusts electricity use in buildings when there’s peak demand on the power grid.

A PNNL technology enables automated Economic Dispatch, which coordinates the use of energy in a manner that enhances distributed generation, efficiency, renewables, and grid reliability.

The U.S. Nuclear Regulatory Commission, U.S. Army Corps of Engineers, and PNNL partnered to complete—in record time—an environmental impact statement for the nation’s first small modular nuclear reactor, to be sited at Clinch River, Tenn.

Researchers used novel methods to safely create and analyze plutonium samples. The approaches could prove influential in future studies of the radioactive material, benefitting research in legacy, national security and nuclear fuels.

PNNL provides gateway to nuclear innovation for small business