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.

A new set of resources from PNNL helps guide dam owners and operators through response and recovery actions in the wake of cybersecurity or unusual incidents.

HydroWIRES initiative helps water stakeholders reap the full benefit of hydropower’s superpower: versatility

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

By improving the Weather Research and Forecasting (WRF)-Solar model, this project aims to reduce forecast errors, improve sub-grid scale variability estimates, and more accurately estimate forecast uncertainty.

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.

Navigating the challenges of connecting hydropower to the electrical grid

This 18-month study will analyze how the region can meet its needs for reliable, resilient, and affordable energy along with decarbonization goals and other energy policies and priorities.

Cataloging and quantifying the economic value of non-traditional value streams in conversions of non-powered dams to hydroelectric facilities