Project Grant 2624229
- Federal Grant Award Summary The University of Washington received a $300,000 Project Grant from the National Science Foundation (NSF) Directorate for Engineering (CFDA 47.041), awarded October 1, 2026, with completion scheduled for September 30, 2029. This collaborative research initiative develops a unified modeling, analysis, and control framework for understanding interactions between large-scale data centers and electric power systems. The project addresses a critical infrastructure gap by...
- Grant Award Summary Arizona State University (ASU) received a $392,839 Project Grant from the National Science Foundation (NSF) Directorate for Engineering (CFDA 47.041) effective August 1, 2026, through July 31, 2029. The project, titled "A Converse Lyapunov Theory for Scalable Analysis and Control of Nonlinear Power Systems," delivers research and analytical methods designed to improve power grid stability and reliability at scale. The research outputs include new theoretical...
- This $350,000 federal Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) aims to develop a new reduced-order dynamic modeling paradigm for accurately representing the impacts of massive distributed energy resource (DER) integration in carbon-neutral power systems. The project, awarded to Arizona State University, will leverage tools in dynamic systems, nonlinear system identification, and machine learning to create physics-based and machine...
- Federal Grant Award Summary The National Science Foundation (NSF) Directorate for Engineering awarded $383,362 to Boston University under CFDA 47.041 (Engineering) for a three-year project (September 1, 2026–August 31, 2029) focused on developing dynamic, optimization-based control methods for reliable electric power grids. The research will create fast control algorithms capable of real-time decision-making using limited measurements, communication, and computational resources. The primary...
- Federal Project Grant Award Summary Arizona State University received a $600,000 Project Grant award from the National Science Foundation's Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070), effective August 1, 2025, through July 31, 2028. The award funds research on water- and carbon-aware design of chiplet-based systems with reconfigurability for artificial intelligence applications in datacenters. The project...
- Federal Grant Award Summary Lehigh University was awarded $518,881 under the National Science Foundation (NSF) Directorate for Engineering (CFDA 47.041) on July 15, 2026, for a Project Grant titled "Stability at the Edge: Cyber-Physical Risks and Control of Hyperscale Data Centers in Future Inverter-Dominated Grids." The three-year project, concluding June 30, 2029, will deliver a comprehensive multi-timescale modeling and control framework designed to assess the interaction between...
- Federal Grant Award Summary The National Science Foundation (NSF) Directorate for Engineering (CFDA 47.041) awarded $199,984 to the University of Michigan-Dearborn as of June 1, 2026, for an Engineering Research Initiation (ERI) project titled "Scalable Machine Learning Frameworks for Stability Enhancement in Inverter-Dominated Power Systems." The project, which extends through May 31, 2028, will develop physics-informed machine learning solutions to enhance the stability and...
- Arizona State University was awarded a three-year $360,000 project grant from the National Science Foundation Division of Electrical, Communications and Cyber Systems under the Engineering (47.041) federal grant program. The grant aims to improve situational awareness of distributed energy resources throughout the electric power system by leveraging advanced sensors and data science methods. Specifically, the university will develop new algorithms to extract useful information from high-fidelity...
- Federal Project Grant Summary San Diego State University Research Foundation received a $550,000 CAREER award from the National Science Foundation (NSF) Directorate for Engineering (CFDA 47.041), effective May 1, 2026 through April 30, 2031, to develop distributed intelligence solutions for enhancing the stability and resilience of electric power networks with heterogeneous energy resources (EERs). The project will deliver two primary products: DI-1, a power-electronic interface capable of...
- Federal Project Grant Award Summary The National Science Foundation (NSF) Directorate for Engineering awarded Cornell University $583,747 on July 15, 2026, to investigate resource colocation as an alternative paradigm for integrating large electrical loads into the power grid. The project, which operates through June 30, 2029, develops scientific foundations, engineering methods, and economic frameworks to understand how pairing large loads—such as artificial intelligence (AI) data centers and...
Arizona State University, through its Office of Research and Sponsored Projects Administration (Orspa), received a $200,000 Project Grant from the National Science Foundation (NSF) Directorate for Engineering (CFDA 47.041) effective October 1, 2026, with completion targeted for September 30, 2029. This collaborative research initiative develops unified modeling, analysis, and control frameworks to characterize the interactions between data center power-electronic systems and the electric grid. The primary deliverables include reduced-order models of data-center power systems that characterize how internal converters, control loops, and energy-storage elements shape the electrical load and impedance presented to the grid, addressing a critical gap in current planning and operational tools that employ overly simplified representations of data center behavior. The research directly addresses the challenge that artificial intelligence and advanced computing systems create rapidly fluctuating electrical loads that existing grid models fail to capture adequately. By revealing how internal power-electronic systems transform computing workload variations into effective grid-level demand, this project will advance the scientific foundation for reliable integration of large-scale data centers into the electrical infrastructure while supporting workforce development at the intersection of computing and energy systems. The collaborative framework comprises three interconnected research thrusts focused on modeling, analysis, and control approaches that enhance grid stability and reliability in an era of expanding computational demands.Federal Project Grant Award Summary
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $200.0k | 7/14/26 |