Project Grant 2523935
Award Date 9/15/25
Completion Date 8/31/27
Dollars Obligated $150K
Federal Agency
Federal Grant Program
Assistance Type
Project Grant
Place of Performance
Ames, IA 50011, USA
Similar Awards
- This Project Grant award from the National Science Foundation (NSF) under the Mathematical and Physical Sciences program (CFDA 47.049) provides $299,999 in funding to the Texas A&M Engineering Experiment Station (Tees) to develop novel dynamic grid optimization algorithms and modeling tools to effectively accommodate high penetration of renewable energy and ensure reliable grid operation. The research aims to address the critical challenges of uncertainty and stability arising from the...
- 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...
- The National Science Foundation (NSF) awarded a $250,000 Project Grant under the Engineering program (CFDA 47.041) to the University of Vermont & State Agricultural College (UVM) to develop a generalized distributed framework for solving large-scale power grid problems. The project aims to advance the state-of-the-art in nonlinear programming, physics-inspired graph-partitioning, and combinatorial optimization to enable fast and robust simulations and optimizations of the future power...
- 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 $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 National Science Foundation (NSF) CAREER grant (CFDA 47.041 - Engineering) awarded to Trustees of Dartmouth College provides $397,111 in funding from September 1, 2025 through January 31, 2030. The project aims to enhance electric power grid operators' situational awareness, improve dynamic model quality, and enable online controls to ensure secure power system operation with high penetration of inverter-based resources (IBRs) such as solar, wind, and battery energy storage. The research...
- This three-year, $110,155 project grant from the National Science Foundation's Division of Mathematical Sciences aims to develop new mathematical methods, computer models, and algorithms for electric grid operational planning under the Mathematical and Physical Sciences program (CFDA 47.049). Specifically, the University of Chicago researchers will contribute a general methodology, including novel mathematical models, theory, and algorithms, to systematically account for non-Gaussian error...
- This three-year, $290,000 National Science Foundation project grant supports research at The Pennsylvania State University to develop new mathematical methods, computer models, and algorithms for electric grid operational planning under non-Gaussian uncertainties in renewable energy forecasts. Funded through NSF's Mathematical and Physical Sciences program (CFDA 47.049), the research directly addresses challenges in integrating intermittent renewable resources like wind and solar power into...
- This Project Grant from the National Science Foundation Division of Mathematical Sciences provides $429,158 to develop computational tools for modeling, prediction and control of distributed and reconfigurable renewable energy systems. Funded under the Mathematical and Physical Sciences program (CFDA 47.049), key outcomes include noise-resilient identification methods for transient dynamics, stochastic models integrating statistical closure with topology-aware data, and optimal control...
- This Project Grant award from the National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) program provides $365,897 to the Regents of the University of Michigan - University of Michigan-Dearborn to enhance grid reliability and stability through the integration of distributed energy resources. Key goals include developing fundamental knowledge to assess real-world power grid reliability, novel control algorithms to improve grid stability, and a shared platform for...