Project Grant 2625248
- 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 $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...
- The National Science Foundation Division of Electrical, Communications and Cyber Systems awarded $199,984 to the University of Michigan-Dearborn on June 1, 2026, under the Engineering Research Initiation program (CFDA 47.041) to develop scalable machine learning frameworks for stability enhancement in inverter-dominated power systems. The project delivers physics-informed neural networks and federated learning methods to estimate real-time power system behavior and recommend corrective...
- This $225,000 National Science Foundation (NSF) Project Grant award under the CFDA 47.041 Engineering program aims to develop a physics-informed, real-time optimal power flow model using machine learning techniques. The project seeks to address gaps in providing close to optimal solutions for power plant outputs while considering practical dynamical constraints to avoid frequency fluctuations and grid instabilities. The key scientific and engineering contributions include: (1) advancements in...
- 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...
- The National Science Foundation Division of Electrical, Communications and Cyber Systems awarded the University of Southern California $300,000 on August 15, 2026, under the Engineering program (CFDA 47.041) to design network infrastructures for reliable wide-area control of power systems serving large electronic loads such as AI data centers, crypto mining centers, and high-performance computing centers. The award funds development of FRELCO (Fast, Resilient, Load-Aware, Cost-Optimal) grid...
- The National Science Foundation Division of Electrical, Communications and Cyber Systems awarded San Diego State University Foundation $550,000 on May 1, 2026, under the Engineering program (CFDA 47.041) to develop distributed intelligence systems for assessing and enforcing electromagnetic transient stability in electric power networks with heterogeneous energy resources. The project will deliver two distributed intelligence types: DI-1, a power-electronic interface that enforces stability...
- The National Science Foundation Division of Electrical, Communications and Cyber Systems awarded North Carolina State University $350,000 on August 15, 2026, under the Engineering program (CFDA 47.041) to design network infrastructures for reliable wide-area control of power systems serving large electronic loads such as AI data centers, crypto mining centers, and high-performance computing centers. The research will develop a massively deployable cyber-physical architecture called the FRELCO...
- 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 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...
The National Science Foundation Division of Electrical, Communications and Cyber Systems awarded the University of Denver $314,144 on August 15, 2026, for physics-grounded deep reinforcement learning research aimed at adaptive out-of-step protection in low-inertia power grids under the Engineering program (CFDA 47.041). The project develops an artificial intelligence framework that enables protective relays to continuously adapt their behavior based on real-time grid conditions rather than relying on predetermined fixed parameters. The work combines physics-based analysis of grid dynamics with machine learning while maintaining transparency and verifiability of protection decisions for engineers. The research addresses a critical threat to grid reliability: out-of-step conditions where loss of synchronization can cause permanent equipment damage and trigger cascading blackouts. As inverter-based resources expand and system inertia declines, these conditions become more likely and exceed the capabilities of existing protective relays. The project encompasses research and development activities, graduate student training through research participation, an NSF-funded undergraduate research program, and K-12 outreach in electrical engineering. Performance takes place in Denver, Colorado, with a period of performance extending through July 31, 2029. The award is classified as a Project Grant, an assistance type supporting investigator-initiated research rather than procurement contracting.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $314.1k | 8/10/26 |