The Grid Modernization Lab Consortium (GMLC) is developing solutions, strategies, and resources for better integrating equity and justice goals in electricity planning and operations.

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

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.

The E-COMP Initiative is creating new capabilities that enable the optimized design and operation of energy systems subject to multiple objectives and with high levels of power electronics.

To help regulators identify a clear pathway to implement policy targets or mandates, PNNL researchers have provided a self-assessment tool.

The Grid Storage Launchpad (GSL) is a national capability for energy storage research funded by the Department of Energy Office of Electricity and located on the Pacific Northwest National Laboratory (PNNL) campus in Richland, Washington

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 Pacific Northwest National Laboratory is developing a Port Electrification Handbook—a reference to aid maritime ports nationwide in their clean energy transition.

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.

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.

PNNL has developed a tool suite of interactive analytics that can be rapidly integrated into analyst workflows to empirically analyze and gain qualitative understanding of AI model performance jointly across dimensions.

Visual Sample Plan (VSP) is a software tool that supports the development of a defensible sampling plan based on statistical sampling theory and the statistical analysis of sample results to support confident decision making.

Pacific Northwest National Laboratory and National Renewable Energy Laboratory conducted a two-year study to investigate the potential of floating offshore wind to help meet growing energy needs on the U.S. West Coast.