Project Grant 2329536
Award Date
1/1/24
Completion Date
12/31/26
Dollars Obligated
$397K
Federal Agency
Division of Electrical, Communications and Cyber Systems
Federal Grant Program
47.041
Assistance Type
Project Grant
Place of Performance
Raleigh, NC 27607, USA
Similar Awards
This $200,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of a novel AI-surrogate enhanced cyberinfrastructure to accelerate power grid simulations. The project, led by North Carolina State University, aims to address the urgent need for more efficient computational models to meet real-time decision-making demands in power grid planning and operations. The key innovations...
This $393,890 National Science Foundation (NSF) Engineering program (CFDA 47.041) project grant, awarded to the University of Texas at Austin (UT Austin) on March 1, 2025, aims to advance the autonomy of power grids by developing novel machine learning and artificial intelligence-enabled strategies. The key objectives are to: Enhance decision-making speed for individual power grid agents through neural approximators that map optimization inputs to feasible outputs, eliminating the need for...
This National Science Foundation (NSF) CAREER grant under CFDA 47.041 "Engineering" provides $394,768 to North Carolina State University to investigate power system dynamics with large-scale integration of inverter-based resources. The project aims to establish a unified framework for modeling, analyzing, and simulating the interaction between fast network transients, switched power converters, and slow electromechanical dynamics in converter-dominated power systems. Key objectives...
This $350,000 federal Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) aims to develop a new reduced-order dynamic modeling paradigm for accurately representing the impacts of massive distributed energy resource (DER) integration in carbon-neutral power systems. The project, awarded to Arizona State University, will leverage tools in dynamic systems, nonlinear system identification, and machine learning to create physics-based and machine...
This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CFDA 47.070) program provides $199,996 to the College of William & Mary to develop a novel AI-surrogate enhanced cyberinfrastructure for accelerating power grid simulations. The key innovations include: Program-behavior analysis to identify optimal code regions for AI surrogate replacement Semi-automatic AI surrogate construction that incorporates domain-specific physical...
This National Science Foundation project grant of $300,000 supports research at the University of Tulsa to develop a decentralized artificial intelligence framework for distribution system fault detection, identification, and power restoration. Under the NSF Engineering program (CFDA 47.041), the university will create a graph capsule network to recognize spatial and temporal patterns in distribution systems and identify fault types and locations. Researchers will also devise a novel...
The University of Tennessee received a three-year, $350,000 Project Grant from the National Science Foundation's Engineering program (CFDA 47.041) to develop artificial intelligence-assisted algorithms for automatic electric power grid modeling. The university will create models of realistic U.S. electric grids under various operating scenarios involving conventional and renewable energy sources. This will help identify and mitigate risks to electric grids by significantly reducing model...
This $500,000 National Science Foundation (NSF) CAREER award, under the Engineering program (CFDA 47.041), aims to improve the computational efficiency of economics-driven transmission planning for electric power systems by up to three orders of magnitude. The project, awarded to the University of Missouri System's Missouri University of Science & Technology, will develop a multi-faceted framework that integrates innovations in modeling, simulation, computing, and design to transform lengthy...
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...
The National Science Foundation (NSF) provided a $400,000 Project Grant from its Engineering program (CFDA 47.041) to Tufts University for a 3-year collaborative research effort to develop new techniques for modeling complex cyber-physical systems. The project aims to combine data-driven machine learning approaches with physics-based modeling to create abstract yet quantitative models that can improve human interaction with engineered systems, including critical infrastructure like energy...