Project Grant 2319242
Award Date
10/1/23
Completion Date
9/30/27
Dollars Obligated
$374K
Federal Agency
Division of Computing and Communication Foundations
Awardee
Drexel University (XF3XM9642N96)
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Philadelphia, PA 19104, USA
Similar Awards
This National Science Foundation grant, awarded under the Computer and Information Science and Engineering program (CFDA 47.070), provides $370,440 to the Illinois Institute of Technology (IIT) for a 4-year collaborative research project titled "Towards Verified Robustness and Safety in Power System-Informed Neural Networks." The project aims to enhance the security and reliability of power systems by optimizing neural network verification techniques tailored to the characteristics...
This National Science Foundation (NSF) Project Grant award of $200,000 to Kansas State University, under the Mathematical and Physical Sciences program (CFDA 47.049), aims to develop and validate deep-learning-enabled distributed stochastic algorithms to solve large-scale, stochastic security-constrained unit commitment problems within power systems. The project will focus on designing a holistic, three-stage, deep neural network-based machine learning approach, developing solution strategies...
This National Science Foundation award of $102,289 provides funding for a one-year project grant to The University of New Mexico titled "MRI: Acquisition of a Network Emulator for Cyber Security Research of Electric Power Grids." The goal is to purchase a co-simulation tool to model cyber-physical systems and conduct cybersecurity research on critical infrastructure like power grids. This tool will enable researchers to study cyberattacks in a digital twin platform without risking an...
The National Science Foundation (NSF) awarded a $145,871 Project Grant under the NSF Engineering program (CFDA 47.041) to the Regents of the University of California at Riverside (UC Riverside) to develop novel data-driven control methods for the safe and secure operation of grid-edge resources (GERs) in modern power systems. The research aims to address the challenges and opportunities presented by the rapid proliferation of distributed energy resources, such as renewable generators, smart...
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) awarded a $1,200,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) federal grant program to the University of Texas at Austin. The grant, running from June 1, 2024 to May 31, 2027, aims to develop theoretical frameworks and practical algorithms for learning data-driven models and control strategies in networked cyber-physical systems, with a focus on power distribution systems. Key areas of work include designing...
This $149,178 project grant from the National Science Foundation's Computer and Information Science and Engineering program aims to improve power system surveillance through convex relaxation techniques. Funded under the American Rescue Plan Act, the grant supports research at the University Corporation to strengthen the dependability and robustness of the electric power grid. The project will develop more efficient convex relaxation-based approaches to power system state estimation to provide...
This three-year project grant from the National Science Foundation's Division of Computing and Communication Foundations, under the Computer and Information Science and Engineering program (CFDA 47.070), provides $280,000 to the University of Rhode Island to develop programmable in-network security measures for resilient smart grids. Specifically, the university will create an in-network cyberattack detection system with customizable packet inspection, a self-healing system to automatically...
This $200,000 Project Grant from the National Science Foundation Division of Mathematical Sciences will support research at Wayne State University to develop stochastic algorithms for early detection and risk prediction of hidden contingencies in modern power systems. Funded under the NSF's Mathematical and Physical Sciences program (CFDA 47.049), which aims to strengthen the scientific enterprise through increasing knowledge and understanding of major national problems, this three-year award...
This $200,000 National Science Foundation project grant supports the development of data-driven power systems control with stability guarantees. Funded through the NSF Engineering program (CFDA 47.041), the award to Carnegie Mellon University will support three thrusts of collaborative research over a 30-month period ending February 2025. The research aims to design a new framework integrating reinforcement learning algorithms with Lyapunov stability theory to provide stability guarantees for...