Project Grant 2527653
- 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 $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 National Science Foundation (NSF) CAREER grant, awarded under the Engineering program (CFDA 47.041), aims to enhance power system stability and safety in the presence of large-scale inverter-based resources (IBRs) by leveraging their emerging grid-forming control (GFM) mode. The $500,167 project, awarded on October 1, 2025 and running through September 30, 2030, will develop a set-theoretic analysis framework with sparsity formulations to increase scalability and sample guidance to reduce...
- The National Science Foundation (NSF) awarded a $350,000 Project Grant to Northeastern University under the Engineering program (CFDA 47.041) to develop a robust and efficient state estimator that can trace the fast dynamics of inverter-based renewable energy sources. The project aims to enable effective control feedback signals and facilitate the integration of these renewable sources into power grids, resulting in cleaner, less costly, and more reliable energy delivery. Key aspects of the...
- This Project Grant award of $1,233,079.00 from the National Science Foundation (NSF) Engineering Directorate (CFDA 47.041) aims to develop a comprehensive theoretical framework for modeling, designing, sensing, and controlling the post-fault stability of future power systems with varying levels of inverter-based resources and synchronous generators. The key products and services to be delivered under this grant include: Establishing the theoretical foundations of energy functions for...
- 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 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 (NSF) Engineering program (CFDA 47.041) awarded a $129,783 Project Grant to Mississippi State University to explore the foundation and take initial steps toward establishing a taxonomy of optimal control architectures and design algorithms for power electronic converters used to integrate diverse energy systems, such as solar photovoltaics, wind, and battery energy storage, into the electricity network. The project aims to develop transformative control...
- 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...
- The National Science Foundation (NSF) awarded a $250,000 Project Grant to Carnegie Mellon University (CMU) under the Engineering program (CFDA 47.041). The grant supports the development of a "Collaborative Research: Scalable Circuit Theoretic Framework for Large Grid Simulations and Optimizations" project. The project aims to create a generalized distributed framework for solving large-scale power grid problems that are both fast and robust, enabling transformative changes in future...
The National Science Foundation (NSF) awarded a $500,304 Project Grant to the University of Colorado (CU) for the "Scalable Wide-Area Control for Frequency & Voltage Stability in Inverter-Dominant Power Systems" project under the NSF Engineering program (CFDA 47.041). The project, running from October 1, 2025 to September 30, 2028, aims to develop computationally efficient methods for the analysis and control of power networks through a novel framework for voltage and frequency control that leverages the unique properties of inverter-based resources. Key objectives include advancing the theory of scalable control design for large-scale, multi-time-scale systems, identifying critical communication links and sensor measurements in power networks with high inverter-based resource penetration, and creating simulation models for large-scale power networks to enable transparent research and consistent testing of control methods. The project will provide research opportunities for PhD students and undergraduates, develop a new course on wide-area control in power systems, and conduct K-12 outreach to introduce power network concepts.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $500.3k | 8/18/25 |