This $295,149 Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) aims to address protection challenges arising from the increasing penetration of renewable energy in modern electric grids. The University of Denver is the prime recipient, and the project will run from August 1, 2024 to July 31, 2027. The project will explore novel model-driven and data-driven solutions to ensure dependable fault detection and secure relay operation for power grids...
This $275,000 Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) aims to develop new techniques for fault detection in inverter-dominated power systems. The project will design auxiliary signal-based fault detection schemes to improve reliability in power grids with high penetration of renewable energy resources like wind and solar, which can pose challenges for conventional detection methods. The research will characterize the necessary auxiliary...
This Project Grant award from the National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) program provides $365,897 to the Regents of the University of Michigan - University of Michigan-Dearborn to enhance grid reliability and stability through the integration of distributed energy resources. Key goals include developing fundamental knowledge to assess real-world power grid reliability, novel control algorithms to improve grid stability, and a shared platform for...
This $274,995 federal Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) aims to develop new techniques for fault detection in inverter-dominated power systems. The project, titled "Collaborative Research: Auxiliary Signal-Based Fault Detection in Inverter-Dominated Power Systems," will create innovative fault detection schemes that leverage auxiliary signals injected by inverters to distinguish normal operation from faults. The research will...
The National Science Foundation (NSF) awarded a $484,965 project grant under the Engineering (CFDA 47.041) program to New York University (NYU) to develop transformative concepts and methodologies to enhance situational awareness of electric power distribution systems. The project aims to address challenges in integrating distributed renewable energy generation by enabling real-time tracking of distribution system operating states. Key objectives include learning-based continuous-time system...
This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $181,004 to Purdue University to develop data-enabled and physics-informed modeling, monitoring, and optimization solutions targeting power system dynamics. The project aims to leverage synchrophasor data and machine learning to improve the understanding and stability of interconnected power grids, supporting the rapid decarbonization and deployment of flexible, distributed energy...
This $360,000 National Science Foundation project grant supports research to advance graph signal processing techniques for electric power distribution system monitoring and control from July 2022 through June 2025. Funded under the NSF Engineering program (CFDA 47.041), the awardee Cornell University will develop a novel mathematical approach incorporating physical grid modeling into machine learning algorithms. The approach interprets system states as graph signals to extract features...
This Project Grant award of $199,940.00 from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program is supporting research by Rensselaer Polytechnic Institute (RPI) to develop algorithms that can quickly predict and rectify large-scale disruptions in power systems. The key objectives are: 1) Quickly and reliably detect ambient-level anomalies in power systems and distinguish them from random noise; 2) Localize any detected anomalies; and 3) Determine the...
The University of South Florida was awarded a $299,717 project grant from the National Science Foundation Division of Electrical, Communications and Cyber Systems to develop a graph signal processing framework for situational awareness in smart grids. The goal of this three-year project grant, awarded September 1, 2021 and set to be completed by August 31, 2024, is to improve situational awareness capabilities for smart grid operators through new signal processing techniques applied to...
This National Science Foundation (NSF) Integrative Activities (CFDA 47.083) program grant award of $762,500.00 to Michigan State University will fund the acquisition of a real-time simulator to enhance the stability, resilience, and cybersecurity of the U.S. power grid. The simulator will enable collaborative, multidisciplinary research to study power grid dynamics, develop new solutions, and test technologies for hardening the grid against extreme weather events, cyber-attacks, and other...