PNNL has developed a next-generation electrical resistivity tomography system for DOE that uses E4D software and AI-enhanced modeling to produce real-time subsurface images that help guide environmental remediation decisions.
To improve our ability to “see” into the subsurface, scientists need to understand how different mineral surfaces respond to electrical signals at the molecular scale.
There are many ways that researchers at PNNL bring unique perspectives to the field of distributed wind. One is the fact that PNNL's distributed wind projects are all led by women.
The Distributed Wind Market Report provides market statistics and analysis, along with insights into market trends and characteristics of wind technologies used as distributed energy resources.
An evaluation of models and prediction tools for distributed wind turbines has unearthed data that can help potential users make the most informed decisions on upfront investments.
PNNL wind energy experts have published the Distributed Wind Market Report: 2022 Edition, supplying key findings that can help businesses, communities, and homeowners make informed decisions.