Junjian Qi Receives NSF Grants of $689,506 for Smart Grid Research
These projects will support two Ph.D. students and one undergraduate student per year
The first one is a transferred CAREER award entitled “Deciphering Large-Scale Real Outage Data for Cascading Failure Analysis, Prevention, and Intervention.” This is a five-year project with a total budget of $470,136. Each year, the project will support one Ph.D. student and one undergraduate student. The goal of this CAREER project is to initiate a new data-driven research direction for studying cascading failure and power system resilience. Qi will develop systematic, transformative theoretical foundations and algorithmic techniques for data-driven cascading failure analysis, prevention and intervention. He will also develop tools to analyze, prevent and finally intervene cascading failures. Network science, statistical inference, data science and deep learning will be seamlessly integrated with power system domain knowledge in order to obtain a unique solution to a very challenging problem.
Qi said, “We expect that the CAREER project will also greatly advance the applied mathematics and computational scientific applications, and benefit related research areas such as network science, statistical inference, data science and deep learning through the resolving of the very unique and challenging cascading failure problem.”
The second grant is a newly awarded EPCN project entitled “Collaborative Research: Advanced and Highly Integrated Power Conversion Systems for Grid Stability and Resiliency.” This is a three-year project collaborating with the University of Central Florida with a total budget of $500,000; and Qi’s share as $219,370. It will support one Ph.D. student each year. In this project, Qi and his team will develop and deploy a novel design of a highly efficient, modulator, distributed controlled, and scalable power system with the capability for integration and coordination of photovoltaic, local energy storage, and a bidirectional smart microinverter. The research will address challenges including state-of-charge control of energy storage, photovoltaic smoothing, maximum power point tracking, and energy arbitrage. Moreover, his team will formulate a novel optimization problem for coordinating multiple three-port inverters considering optimal trade-off between voltage regulation and reactive power sharing and technical constraints on voltage and reactive power.
Qi said, “The smart, highly integrated system to be developed will enable higher penetration of solar generation into the grid and potentially disrupt the conventional energy system by delivering an integrated, efficient and reliable solar energy solution.”