Project Grant 2045978
- This $260,000 National Science Foundation project grant will fund the development of data-enabled modeling, monitoring, and optimization algorithms targeting power system dynamics from 2022-2025. The University of Texas at Austin, through its parent organization the University of Texas System, will receive funding under the NSF Engineering program (CFDA 47.041) to correlate synchrophasor data and develop Gaussian process and stability-aware optimal power flow tools. Key outcomes will include...
- 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...
- The National Science Foundation awarded a $225,000 Project Grant under the Engineering (47.041) federal grant program to the University of Colorado from July 1, 2023 to June 30, 2026. The University will develop a physics-informed real-time optimal power flow model using machine learning techniques to provide close to optimal solutions for power plant outputs while considering dynamic constraints to avoid grid instabilities. Key activities include advancing techniques combining...
- 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 $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...
- 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 $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 National Science Foundation (NSF) CAREER project award under CFDA 47.041 (Engineering) aims to advance the autonomy of power grids by developing fundamental theory and strategies to enhance decision speed, resilience, and societal/sustainability awareness of distributed grid management models and algorithms. The $500,000 award, effective from March 1, 2025 to February 28, 2030, supports the University of Texas at Austin in addressing three critical research questions: leveraging agent...
- 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...
- The National Science Foundation awarded a $280,000 Project Grant to the University of Texas at Austin under the Engineering (47.041) federal grant program. The award will support research and development of grid-forming inverter technologies to advance the energy transition and increase renewable energy grid integration. Key deliverables include optimization of grid-forming voltage control loops; development of advanced functionalities for three-port microinverters integrating solar, storage and...
The National Science Foundation awarded a $154,573 project grant to the University of Houston System to support research titled "COLLABORATIVE RESEARCH: POWER SYSTEM FLEXIBILITY: METRIC, ASSESSMENT, AND ALGORITHM" from April 15, 2021 through March 31, 2024. The grant is part of NSF's Engineering program (CFDA 47.041), which seeks to improve quality of life and economic strength through engineering research and education. Under this award, the University of Houston will develop metrics and algorithms to assess power system flexibility to facilitate greater integration of renewable energy sources. Key products will include metrics to quantify a power system's ability to adapt to variability in electricity supply and demand, as well as algorithms to evaluate flexibility needs and options. Outcomes aim to support more cost-effective and reliable operation of power grids incorporating high levels of renewable resources.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $0 | 5/20/21 | ||
| Not listed | $154.6k | 4/2/21 |