PNNL electrical engineer Samrat Acharya led a team that earned the 2024 IEEE Innovative Smart Grid Technologies Conference Best Paper Award.

A new iron-based aqueous flow battery shows promise for grid energy storage applications.

In 2006, battery research was practically non-existent at PNNL. Today, the lab is lauded for its battery research. How did PNNL go from a new player to a leader in state-of-the-art storage for EVs and the grid?

Results of the PR100 study outline near- and short-term strategies for Puerto Rico to achieve a renewable power grid by 2050.

Visual Sample Plan, a free software tool developed at PNNL that boosts statistics-based planning, has been recognized with a 2024 Federal Laboratory Consortium Award.

Understanding the risk of compound energy droughts—times when the sun doesn’t shine and the wind doesn’t blow—will help grid planners understand where energy storage is needed most.

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

Researchers created a methodology to design custom network topologies that improve the execution time for scientific applications.

Battery energy storage systems are being proposed in municipalities across the U.S. PNNL researchers can help community planners guide safe siting and operations.

Tumeo will lead the ChemComp project, which was awarded for Exploratory Research in Extreme Scale Science

PNNL celebrates World Energy Storage Day (September 22) by introducing you to some of our best and brightest in this area.

Stinis will serve as a principal investigator on two of the four projects selected for funding by the Advanced Scientific Computing Research program.

Researchers unveil user-friendly software to keep complex projects on budget and on schedule.

PNNL’s Grid Storage Launchpad delivers tomorrow’s energy storage solutions today.

PNNL energy storage experts express need for continued investment in developing and deploying long-duration energy storage.

The Rapid Assessment of Platform Technologies to Expedite Response project aims to prepare against future pandemics.

The award was given at the 29th International Conference on Information, Communication and Automation Technologies.

Zhijie (Jay) Xu will apply his expertise in multiscale modeling to this editorial role.

PNNL researchers present challenges and opportunities for fusing graph neural networks with deep reinforcement learning.

ACMD staff contributed to 30 years of atmospheric data collection for the Department of Energy’s Atmospheric Radiation Measurement user facility.