Novel Applications for Synchronized Power Instrumentation seeks to improve electric grid resilience, reliability, security, and affordability.

Researchers at PNNL have developed an interpretable, lightweight AI model that can easily predict weld microstructure features using only basic machine sensor inputs.

PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.

PNNL will engage with transmission planners and other regional partners through technical assistance and listening sessions with the goal of exploring opportunities to integrate equity into transmission planning.

This is the first time a flow battery with 24-hour discharge capacity will be deployed and tested in a field environment.

ExaGO, a power grid simulation and optimization platform developed at PNNL is the first of its kind to run on Frontier.

A new version of the Department of Energy’s Technical Resilience Navigator allows users to prioritize resilience solutions based on both risk reduction and emissions impact.

Researchers studied water cycling to assess the achievability of net-zero water usage at military installations in the Pacific Islands.