The MIT Laboratory for Information and Decision Systems (LIDS) has received $1,365,000 in funding from the Appalachian Regional Commission (ARC) to support its participation in an innovative project, “Formation of the Smart Grid Deployment Consortium ( SGDC) and expansion of the HILLTOP+ platform”.
The grant was made available through ARC's Appalachian Regional Initiative for Stronger Economies, which fosters regional economic transformation through multi-state collaboration.
Directed by Kalyan VeeramachaneniSenior Research Scientist and LIDS Principal Investigator Data to the ai group, the project will focus on creating ai-powered generative models for customer load data. Veeramachaneni and his colleagues will work alongside a team of universities and organizations led by Tennessee tech University, including collaborators in Ohio, Pennsylvania, West Virginia and Tennessee, to develop and implement smart grid modeling services through the SGDC project.
These generative models have wide-ranging applications, including network modeling and training algorithms for energy technology startups. When models are trained on existing data, they create additional, realistic data that can augment limited data sets or replace sensitive ones. Stakeholders can then use these models to understand and plan for specific what-if scenarios far beyond what could be achieved with existing data alone. For example, the data generated can predict the potential load on the grid if an additional 1,000 homes adopted solar technologies, how that load might change throughout the day, and similar contingencies vital for future planning.
The generative ai models developed by Veeramachaneni and his team will provide insights for modeling services based on the HILLTOP+ microgrid simulation platform, originally prototyped by MIT Lincoln Laboratory. HILLTOP+ will be used to model and test new smart grid technologies in a virtual “safe space,” giving rural electric utilities greater confidence in deploying smart grid technologies, including utility-scale battery storage . Energy technology startups will also benefit from HILLTOP+ network modeling services, allowing them to virtually develop and test their smart grid hardware and software products for scalability and interoperability.
The project aims to help rural electric utilities and energy technology startups mitigate the risks associated with the deployment of these new technologies. “This project is a powerful example of how generative ai can transform a sector, in this case the energy sector,” says Veeramachaneni. “To be useful, generative ai technologies and their development must be closely integrated with expertise in the field. “I am delighted to collaborate with network modeling experts and work alongside them to integrate the latest and greatest from my research group and push the boundaries of these technologies.”
“This project is a testament to the power of collaboration and innovation, and we look forward to working with our collaborators to drive positive change in the energy sector,” says Satish Mahajan, principal investigator of the project at Tennessee tech and professor of electrical and computer engineering. Tennessee tech Rural Innovation Center Director Michael Aikens adds, “Together, we are taking important steps toward a more sustainable and resilient future for the Appalachian region.”
