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

A report on the projected effects of climate change on federal hydropower through the end of the twenty-first century.

New report examining multiple decades of climate and hydropower generation data provides insights into resilience of the western hydropower fleet.

The Flow Tradeoff Tool is a free, comprehensive software toolkit designed to evaluate trade-offs between hydropower energy production and environmental flows.

Researchers are bridging hydropower data gaps for unrivaled forecasting precision to support grid resilience.

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.