Collaborative Research: RII Track-2 FEC: STORM: Data-Driven Approaches for Secure Electric Grids

University Of Alaska Fairbanks Campus, Fairbanks AK

Investigators

Abstract

This project involves the jurisdictions of Maine, Alaska, South Dakota, and Puerto Rico. The proposed research, education, and workforce development activities will advance the nation’s smart grid technologies to support communities impacted by severe weather, such as hurricanes, blizzards, flooding, and rapid shifts in temperature. The project will benefit from experts in electrical, computer and civil engineering, economics, community and environmental resilience, climatology, and mathematics and statistics. Faculty and students will co-produce knowledge with community stakeholders, using convergent approaches that are critical to solving complex problems. Research and workforce development objectives are built around three intersecting themes: (1) Engagement of communities in local solutions for mitigating impacts of severe weather and knowledge translation for microgrid design; (2) Improvement of power grid resilience through accelerated big data modeling, estimation, and secure control frameworks, and (3) Development of regionally relevant cyber-physical research infrastructure for studying community engaged data-driven operation of power grids. Each theme will involve early-career and senior faculty to ensure effective mentoring. Research and workforce development activities are designed to develop pilot programs and data that will be useful to federal agencies and industry. The electric grid, among the most complex of human-made systems, is vital to U.S. security and quality of life. More frequent and intense extreme weather events as well as other anthropogenic threats, including physical and cyber-attacks, are testing the resilience of our nation’s critical infrastructure. STORM is built around three interrelated themes in response to this challenge. Theme 1 approaches are novel in terms of the co-production of research and knowledge among community members in geographically distinct regions; the co-design of solutions with an interdisciplinary team of researchers with social science and engineering backgrounds whose experiences span the study regions, and applications of lessons learned from each of the three study regions, to the others. Theme 2 seeks to mitigate the impact on the electric grid according to the community resilience goals during and after an extreme weather event. Theme 2’s new multi-microgrid system restoration strategy will prioritize critical loads at the community and individual levels based on a new multi-timescale predictive control and estimation framework that utilizes GFM inverters to provide optimal dynamic support during the process. Novel hardware Trojan prevention, detection, and mitigation techniques will advance cyber-attack resilience of the entire system during severe weather. Theme 3 seeks to develop regionally-relevant cyber-physical research infrastructure for studying community-engaged, data-driven operation of power grids. The new, regionally relevant synthetic power systems and data will be immensely valuable to the advancement of data science, machine learning, and artificial intelligence applied to the electric industry. STORM will benefit from strong existing partnerships including a successful Department of Energy EPSCoR project on modeling converter dominated power systems. STORM also builds upon senior personnel’s partnerships with Sandia National Laboratory, National Renewable Energy Laboratory, and Pacific Northwest National Laboratory. In addition, the project will leverage relationships with key industry/community partners (Kartorium, Kotzebue Electric Association, East River Electric Co-op, Missouri River Energy Services, National Rural Electric Cooperative Association, Siemens, Sioux Valley Energy, Sustainable Energy for Galena, and Versant Power). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.