– MIT LIDS applying generative AI to smart grid modelling
– Focus on creating AI-driven generative models for customer load data
– Project awarded $1.37 million in funding from the Appalachian Regional Commission with participants from across multiple states
The Laboratory for Information and Decision Systems (LIDS) at MIT is working on applying generative AI to smart grid modeling as part of the Smart Grid Deployment Consortium project led by Tennessee Tech University. The focus is on creating AI-driven generative models for customer load data to be used in the HILLTOP microgrid simulation platform for testing new smart grid technologies in rural electric utilities and energy tech startups in the Appalachian region of the US.
Kalyan Veeramachaneni, a principal research scientist at LIDS, highlights the transformational potential of generative AI in the energy sector and emphasizes the importance of integrating domain expertise in the development of these technologies. The project aims to leverage generative models to create realistic data that can predict the impact of new technologies on the grid, such as the adoption of solar technologies by households and how it would affect the grid load throughout the day.
Funded with $1.37 million from the Appalachian Regional Commission, the initiative involves participants from Ohio, Pennsylvania, West Virginia, and Tennessee. The goal is to advance the use of generative AI in smart grid modeling to enhance scalability, interoperability, and energy efficiency in the Appalachian region.