The Grid Modernization Lab Consortium (GMLC) is developing solutions, strategies, and resources for better integrating equity and justice goals in electricity planning and operations.
A multi-institution research team led by PNNL is addressing curb usage management challenges in large urban areas by developing a city-scale dynamic curb use simulation tool and an open-source curb management platform.
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.
GeoBOSS is a software library that combines the data-handling capabilities of Spark and the user-friendliness of Python to simplify geospatial analytics and the transition between small-scale research and large-scale operational projects.
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
IrrigationViz is a visual decision-support tool that provides users with high-level estimates for irrigation modernization projects, such as concrete lining for a canal or replacing a canal with a pipeline.
PNNL is leading a consortium that provides funding opportunities to the automotive industry for accelerating new lightweight technologies in on-highway vehicles.
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.
PNNL combines AI and cloud computing with damage assessment tools to predict the path of wildfires and quickly evaluate the impact of natural disasters, giving first responders an upper hand.
Powered by few-shot learning, the Sharkzor AI-driven, scalable web application makes it possible to quickly characterize and sort electron microscopy images used to analyze radioactive materials.
National laboratories, industry and academia are collaborating to provide electric vehicle manufacturers with batteries that are more reliable, high-performing, safe, and less expensive.