Project Grant 2546893
- The National Science Foundation's Division of Electrical, Communications and Cyber Systems awarded Trustees of Boston University a $388,847 Project Grant (CFDA 47.041 - Engineering program) effective October 1, 2025, through September 30, 2028. The award supports the development of mathematical foundations, algorithms, and control strategies for online optimization of networked critical infrastructures—including power systems, transportation networks, and emerging computing platforms—operating...
- This NSF Engineering program (CFDA 47.041) grant awarded to Trustees of Boston University for $258,677 provides funding to develop real-time optimization and control approaches for distributed energy resources (DERs) in power grids. The research aims to overcome barriers to large-scale DER integration, including degraded power quality/reliability and the inability of existing optimization approaches to match power system dynamics. The project will create feedback-based online algorithms to...
- This $223,406 National Science Foundation project grant, awarded under the Engineering program (CFDA 47.041), will fund the development of novel optimization models and algorithms for the operation of future electric power systems at the Massachusetts Institute of Technology from January 2023 through February 2024. Specifically, the principal investigator will create efficient and robust algorithms for optimizing power flow and network topology to support the integration of renewable, demand...
- Federal Grant Award Summary This $392,839 Project Grant, awarded by the National Science Foundation (NSF) Directorate for Engineering (CFDA 47.041) and effective August 1, 2026 through July 31, 2029, supports research at Arizona State University to develop advanced analytical and control methods for large-scale nonlinear power systems. The project applies converse Lyapunov theory to create scalable algorithms that improve power grid stability analysis and control by exploiting network...
- 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 $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...
- The National Science Foundation (NSF) awarded a $484,965 project grant under the Engineering (CFDA 47.041) program to New York University (NYU) to develop transformative concepts and methodologies to enhance situational awareness of electric power distribution systems. The project aims to address challenges in integrating distributed renewable energy generation by enabling real-time tracking of distribution system operating states. Key objectives include learning-based continuous-time system...
- The National Science Foundation (NSF) awarded a $145,871 Project Grant under the NSF Engineering program (CFDA 47.041) to the Regents of the University of California at Riverside (UC Riverside) to develop novel data-driven control methods for the safe and secure operation of grid-edge resources (GERs) in modern power systems. The research aims to address the challenges and opportunities presented by the rapid proliferation of distributed energy resources, such as renewable generators, smart...
- 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...
- 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's Directorate for Engineering (CFDA 47.041) awarded $383,362 to the Trustees of Boston University on September 1, 2026, for a three-year research project (completion date: August 31, 2029) titled "Dynamic and Safe Optimization-Based Control for Reliable Power Grids." This award funds fundamental research to develop advanced control algorithms and analytical methods that enable electric power grids to operate safely and reliably under uncertain, real-time conditions. The research focuses on creating fast, optimization-based controllers that can enforce operational constraints, maintain system stability, and make autonomous decisions using only limited measurements, communication bandwidth, and computational resources—addressing critical needs as modern power grids face increasing demand from data centers, artificial intelligence applications, and advanced manufacturing. The project deliverables include the development of dynamic, optimization-based safety controllers for networked engineering systems with partially known dynamics and uncertain inputs, along with analytical tools to quantify tradeoffs between reliability, constraint satisfaction, and practical operational limitations. By enabling locally implementable control software that responds quickly to disturbances while operating within safe limits, this research advances the engineering foundations for reliable energy generation and transport services, supporting U.S. competitiveness in advanced computing and AI technologies that depend on grid resilience.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $383.4k | 6/29/26 |