Project Grant 2308498
- This $349,969 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports the development of advanced algorithms and data analysis methods to enhance the monitoring, control, and overall performance of modern power distribution systems. Specifically, the project aims to integrate and analyze heterogeneous data from power grid infrastructure, such as advanced metering, supervisory control, and micro-phasor measurement systems,...
- 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...
- 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 $149,940 federal Project Grant award from the National Science Foundation's (NSF) Division of Mathematical Sciences will support research at Auburn University Montgomery (AUM) to develop a deeper understanding of the impact of "topological disturbances" on power grid networks. The research aims to rigorously analyze how changes to a power network's connectivity structure affect the full set of power flow solutions, leveraging the machinery of toric deformations and convex...
- This $500,000 National Science Foundation project grant funds the development of algorithms and computational tools to optimize electric power system planning and operations during extreme events such as wildfires and hurricanes. Awarded under the Engineering program (CFDA 47.041), the five-year award to the Georgia Tech Research Corporation from February 2022 to January 2027 aims to address computational challenges associated with power grid nonlinearities, uncertainties from renewable energy...
- This $100,000 National Science Foundation Project Grant supports research at the University of Washington to develop a new data-driven power systems control framework with stability guarantees. Funded under the NSF Engineering program (CFDA 47.041), the research aims to design reinforcement learning algorithms for inverter-based frequency and voltage control of power grids that provide formal stability assurances. Over the two-year period from March 2022 to February 2025, university...
- This $240,000 Project Grant was awarded on July 1, 2025 by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) federal grant program. The grant was awarded to the Regents of the University of California at Riverside to conduct collaborative research on simplicial-topological modeling for the integration of ultra-high-dimensional distributed energy resources into wide-area modern power systems. The research aims to develop new data-adaptive graph...
- This Project Grant from the National Science Foundation's $200,000 Engineering program (CFDA 47.041) will fund research at the University of California, San Diego to develop a new data-driven power systems control framework with stability guarantees. The three-year award beginning March 2022 aims to design reinforcement learning algorithms for inverter-based frequency and voltage control of power grids that provide formal stability through a novel approach bridging Lyapunov control theory and...
- 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 $150,000 project grant awarded by the National Science Foundation (CFDA 47.049 - Mathematical and Physical Sciences) to Iowa State University aims to develop novel dynamic grid optimization algorithms and modeling tools to effectively accommodate high penetration of renewable energy and ensure reliable power grid operation. The project will focus on addressing key challenges posed by the uncertainty of renewable energy resources and the stability concerns of power grids with high...
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 tighter bounds on flow analyses than traditional methods. It also intends to identify specific types of false data that could impact grid monitoring. The research extends optimization techniques for large-scale cyber-physical power systems to enhance monitoring, analysis, and controllability. Findings will be shared with Arkansas State University to encourage careers in STEM fields relevant to critical infrastructure protection.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $149.2k | 12/23/22 |