The Laboratory for Information and Decision Systems (LIDS) at Massachusetts Institute of Technology (MIT) has received a grant of $1,365,000 from the Appalachian Regional Commission (ARC). The funding supports LIDS’s role in the “Forming the Smart Grid Deployment Consortium (SGDC) and Expanding the HILLTOP+ Platform” project. Made available through ARC’s Appalachian Regional Initiative for Stronger Economies program, which encourages economic transformation through multi-state cooperation, this grant will aid in creating Artificial Intelligence (AI)-driven generative models for customer load data.
Kalyan Veeramachaneni, the lead research scientist and principal investigator at LIDS’ Data to AI Group, will spearhead the project. As part of this initiative, he and his colleagues will join forces with Tennessee Tech University and other institutes from Ohio, Pennsylvania, West Virginia, and Tennessee. The collective objective is to devise and introduce smart grid modeling services via the SGDC project.
These generative models are game-changers with their extensive uses, such as grid modeling and algorithm training for energy tech startups. The models produce supplementary, realistic data upon training on existing data, making them useful for supplementing limited datasets or replacing sensitive ones. The utility of these models lies in their ability to predict specific scenarios beyond the realm of existing data, thereby aiding in strategic planning.
Veeramachaneni and his team’s generative AI models will serve as the foundation for modeling services based on the HILLTOP+ microgrid simulation platform. Initially created by MIT Lincoln Laboratory, HILLTOP+ will simulate and test novel smart grid technologies in a virtual safe environment. This will inspire confidence among rural electric utilities to implement smart grid technologies, including utility-scale battery storage. Moreover, the modeling services will also benefit energy tech startups by facilitating the virtual testing of their smart grid products for scalability and interoperability.
The project’s ultimate goal is helping rural electric utilities and energy tech startups reduce the risks involved in introducing new technologies. According to Veeramachaneni, this project is a prime example of how generative AI can revolutionize a sector, in this case, the energy sector.
Emphasizing the importance of collaboration and innovation, Satish Mahajan, the project’s lead investigator at Tennessee Tech, expressed an eagerness to collaborate with partners for bringing about positive changes in the energy sector. Michael Aikens, director of Tennessee Tech’s Center for Rural Innovation, added that these collective efforts are significant strides towards achieving a more sustainable and resilient future for the Appalachian region.
