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

PNNL is contributing analytics expertise to a first-of-its-kind electric vehicle carsharing program in rural Hood River, Oregon.

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

The Data-Model Convergence (DMC) Initiative is a multidisciplinary effort to create the next generation of scientific computing capability through a software and hardware co-design methodology.

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

PNNL and collaborators have established a national heat pump and heat pump water heater partnership to help drive adoption of these energy-saving technologies in both residential and commercial buildings.

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.

FEMP's operations and maintenance (O&M) resources offer federal agencies technology- and management-focused guidance to improve energy and water efficiency and ensure safer and more reliable operations.

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 data scientists and engineers will be presenting at NeurIPS, the Thirty Fourth Conference on Neural Information Processing Systems, and the co-located Women in Machine Learning workshop, WiML.

The user-friendly Project Schedule Visualizer software developed at PNNL helps users readily identify and understand the impacts of updates to the schedule, budget, and risks associated with large, complex projects that cross departments.

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.