MIT's 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, “Training the Network Deployment Consortium (SGDC) and expansion of the HILLTOP+ platform”.
The grant was awarded through ARC's Appalachian Regional Initiative for Stronger Economies, which promotes regional economic transformation through multi-state collaboration.
Directed by Kalyan Veeramachaneniprincipal investigator and senior researcher at LIDS' Data to AI Group, the project will focus on creating AI-driven 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 from Ohio, Pennsylvania, West Virginia and Tennessee, to develop and deploy smart grid modeling services as part of 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 data sets. 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 1,000 additional homes adopted solar technologies, how that load might change throughout the day, and other similar eventualities, essential for future planning .
The generative AI models developed by Veeramachaneni and his team will provide data to modeling services based on the HILLTOP+ microgrid simulation platform, originally prototyped by MIT's Lincoln Laboratory. HILLTOP+ will be used to model and test new smart grid technologies in a virtual “safe space”, providing rural electric utilities with increased confidence in deploying smart grid technologies, including battery storage at scale of public services. 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 deploying these new technologies. “This project is a powerful example of how generative AI can transform an industry – in this case, the energy sector,” says Veeramachaneni. “To be useful, generative AI technologies and their development must be closely integrated with domain expertise. I am excited to collaborate with and work alongside experts in grid modeling to integrate the latest and greatest advances from my research group and push the boundaries of these technologies.
“This project demonstrates the power of collaboration and innovation, and we look forward to working with our collaborators to generate positive change in the energy sector,” said Satish Mahajan, principal investigator on the project at Tennessee Tech and professor of electricity and energy. engineering computer Science. Michael Aikens, director of the Center for Rural Innovation at Tennessee Tech, adds: “Together, we are taking meaningful steps toward a more sustainable and resilient future for the Appalachian region.