Project Grant 2523943
- This $220,000 National Science Foundation project grant under the Engineering program (CFDA 47.041) will support research at Kansas State University from July 2022 to June 2024 to leverage smart meter data for enhanced situational awareness of power distribution systems. The university will investigate fundamental approaches to effectively integrate advanced metering infrastructure data to increase operational awareness of distribution grids. Researchers will focus on integrating machine...
- 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 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 $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 $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...
- The National Science Foundation (NSF) awarded a $159,860 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) program to the Trustees of the Stevens Institute of Technology in Hoboken, New Jersey. This 3-year grant supports the development of efficient algorithms to rigorously quantify uncertainties in state estimation and network topology identification for smart electricity distribution systems. The project aims to enable more accurate modeling and secure, cost-effective...
- 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 from the National Science Foundation's Division of Mathematical Sciences, under the Mathematical and Physical Sciences program (CFDA 47.049), provides $276,203 to Southern Methodist University to develop new computational techniques for solving core mathematical equations modeling large-scale power systems. Key products include fast and accurate screening techniques for high-degree contingency analysis using state-of-the-art algebraic multigrid on weighted graph Laplacians....
- 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 $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 $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, to improve situational awareness and enable more informed decision-making by utility operators. The project is implementing a novel framework based on optimal transport theory, which is expected to provide more robust state estimation and control capabilities that can better handle the stochastic, dynamic, and non-Euclidean nature of real-world power systems data. This research, conducted by Kansas State University, seeks to advance national prosperity and welfare through reduced energy costs, improved system reliability, and a transition to a more resilient and sustainable energy future.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $350.0k | 8/6/25 |