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.
Scientists are pioneering approaches in the branch of artificial intelligence known as machine learning to design and train computer software programs that guide the development of new manufacturing processes.
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.
PNNL researchers developed a new model to help power system operators and planners better evaluate how grid-forming, inverter-based resources could affect the system stability.
PNNL's Tegan Emerson was invited to be one of two plenary speakers at the inaugural AIM 2022 congress. The Minerals, Metals & Materials Society organized AIM 2022 to connect materials and manufacturing researchers from around the world.
Recognizing how innovation and clean technologies at the very edge of the grid can work together to transition the electricity system, PNNL takes a multidisciplinary approach to advancing and integrating renewable energy solutions.
Working on puzzles with her grandpa helped instill Emilie Purvine’s interest in math from an early age. That interest later turned to being co-captain for her high school math team, a degree in mathematics, and eventually a career at PNNL.
Anika Halappanavar’s research into COVID-19 misinformation earned her recognition by the Washington State Academy of Sciences as one of the state’s top high school researchers.