Project Grant 2523881
- The National Science Foundation (NSF) awarded a $1,500,000 Project Grant titled "ASCENT: BOOSTING CYBER AND PHYSICAL RESILIENCE OF POWER ELECTRONICS-DOMINATED DISTRIBUTION GRIDS IN ENERGY SPACE" to the San Diego State University Research Foundation under the NSF Directorate for Engineering (CFDA 47.041) program. The project aims to develop an innovative sensing and control system to enhance the cyber-physical resilience of power distribution systems with a high penetration of power...
- 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...
- This Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) provides $199,542 to Purdue University to develop reaction mechanisms and experimental validation frameworks to mitigate the impact of sophisticated cyber attacks on smart power distribution systems. The key objectives are to: 1) investigate vulnerabilities of load tap changers (LTCs) in power distribution systems to cyber attacks targeting voltage collapse; 2) design primary and backup reaction...
- 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 $199,964 federal Project Grant awarded by the National Science Foundation (NSF) Engineering program (CFDA 47.041) will fund research at the University of California, Santa Barbara (UCSB) to address challenges and opportunities presented by the rapid proliferation of grid-edge resources (GERs) in modern power systems. The project aims to develop novel data-driven control strategies and advance the understanding of GER behavior to ensure the safe and secure operation of these distributed...
- 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...
- 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 Project Grant award of $111,469, provided by the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049), aims to develop advanced modeling and analysis techniques for integrating ultra-high-dimensional distributed energy resources into wide-area power transmission networks. The project at Portland State University will create a data-adaptive graph generation module, apply topological data analysis with multiple filtrations, and develop higher-order...
- This $375,000 project grant from the National Science Foundation's Engineering program (CFDA 47.041) funds research at Texas A&M Engineering Experiment Station to develop a Strategic Holistic Framework for Intrusion Prevention using Multi-modal Data in Power Systems (SHIELD). The three-year project aims to strengthen national power grid protection against cyber-physical attacks through novel intrusion detection and prevention methods. Researchers will fuse cyber and physical power system...
This Project Grant award, valued at $599,943.00 and provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), aims to enhance the security and resilience of cyber-physical power systems against sophisticated cyber-attacks. The key products and services to be delivered through this funding include: 1) Developing advanced machine learning and optimization-based tools to detect and mitigate stealthy cyber-attacks on critical electric power grid infrastructure; 2) Creating a framework that tightly integrates power system physics with state-of-the-art computational methods to improve anomaly detection, identify infeasible operating state transitions, and reconstruct the true system state; and 3) Providing workforce development opportunities to engage a diverse range of students in STEM disciplines related to this research. This award was granted to The University Corporation, a non-profit organization affiliated with California State University, Northridge, to conduct this multi-year project from September 2025 through August 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $599.9k | 8/7/25 |