MIT’s Laboratory for Information and Decision Systems (LIDS) has been awarded $1,365,000 in funding from the Appalachian Regional Commission (ARC) to help its involvement with an revolutionary challenge, “Forming the Smart Grid Deployment Consortium (SGDC) and Expanding the HILLTOP+ Platform.”
The grant was made obtainable by ARC’s Appalachian Regional Initiative for Stronger Economies, which fosters regional financial transformation by multi-state collaboration.
Led by Kalyan Veeramachaneni, principal analysis scientist and principal investigator at LIDS’ Data to AI Group, the challenge will concentrate on creating AI-driven generative fashions for buyer load knowledge. Veeramachaneni and colleagues will work alongside a crew of universities and organizations led by Tennessee Tech University, together with collaborators throughout Ohio, Pennsylvania, West Virginia, and Tennessee, to develop and deploy smart grid modeling companies by the SGDC challenge.
These generative fashions have far-reaching functions, together with grid modeling and coaching algorithms for power tech startups. When the fashions are educated on current knowledge, they create extra, sensible knowledge that may increase restricted datasets or stand in for delicate ones. Stakeholders can then use these fashions to know and plan for particular what-if situations far past what might be achieved with current knowledge alone. For instance, generated knowledge can predict the potential load on the grid if a further 1,000 households had been to undertake photo voltaic applied sciences, how that load may change all through the day, and related contingencies important to future planning.
The generative AI fashions developed by Veeramachaneni and his crew will present inputs to modeling companies based mostly on the HILLTOP+ microgrid simulation platform, initially prototyped by MIT Lincoln Laboratory. HILLTOP+ can be used to mannequin and check new smart grid applied sciences in a digital “safe space,” offering rural electrical utilities with elevated confidence in deploying smart grid applied sciences, together with utility-scale battery storage. Energy tech startups will even profit from HILLTOP+ grid modeling companies, enabling them to develop and just about check their smart grid {hardware} and software program merchandise for scalability and interoperability.
The challenge goals to help rural electrical utilities and power tech startups in mitigating the dangers related to deploying these new applied sciences. “This project is a powerful example of how generative AI can transform a sector — in this case, the energy sector,” says Veeramachaneni. “In order to be useful, generative AI technologies and their development have to be closely integrated with domain expertise. I am thrilled to be collaborating with experts in grid modeling, and working alongside them to integrate the latest and greatest from my research group and push the boundaries of these technologies.”
“This project is 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 for the challenge at Tennessee Tech and a professor {of electrical} and laptop engineering. Tennessee Tech’s Center for Rural Innovation director, Michael Aikens, provides, “Together, we are taking significant steps towards a more sustainable and resilient future for the Appalachian region.”