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This project leverages a specialized AI foundation model, GridFM, to accelerate electric grid scenario simulations from months down to 24 hours, enabling rapid adaptation to fluctuating loads and new power sources. By pooling resources from national labs, utilities, and IBM Research, the initiative aims to reframe AI as a critical tool for enhancing grid reliability rather than a computational burden. The open-source approach via the Linux Foundation Energy further ensures broad collaboration and refinement of this high-fidelity modeling platform.
Brookhaven Lab to model electric grids with a $14.2M AI
Brookhaven National Laboratory will lead a three-year, $14.2M project using artificial intelligence to model ways to better manage electric grids. The project will pool resources from research institutes such as BNL and Stony Brook University, private entities like IBM Research, and utilities including LIPA and Con Edison.
Brookhaven National Laboratory will lead a three-year project funded by a $14.2 million investment to develop an artificial intelligence platform for electric grid management. The project will pool resources from institutions including Stony Brook University and companies such as IBM Research, alongside utilities LIPA and Con Edison, to rapidly model grid scenarios. Researchers aim to simulate billions of possibilities within…
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