Project Grant 2229075
Award Date 1/1/23
Completion Date 12/31/25
Dollars Obligated $200K
Federal Agency
Federal Grant Program
Assistance Type
Project Grant
Place of Performance
Richmond, VA 23284, USA
Similar Awards
- This $200,000 project grant from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) will fund research at Clarkson University to develop a holistic quantum-inspired framework for power system state estimation. The framework aims to address cybersecurity risks and operational challenges in decentralized grids through four main activities: 1) Designing a quantum network architecture and protocols for smart grid communications and key distribution. 2)...
- This Project Grant from the National Science Foundation's Division of Mathematical Sciences, under the Mathematical and Physical Sciences program (CFDA 47.049), provides $203,751 to Kennesaw State University Research And Service Foundation, Inc. for research activities related to developing a holistic quantum-inspired framework for power system state estimation. Specifically, the awardee will conduct four main research activities: 1) designing a quantum network architecture for key...
- This $199,986 National Science Foundation project grant supports the development of variational quantum algorithms to efficiently solve time-dependent nonlinear differential equations for very high-dimensional transient stability simulation and N-K contingency analysis problems in large-scale power systems with renewable energy sources. Funded under the NSF's $47.041 million Engineering program, the research aims to realize an exponential advantage over classical algorithms through new...
- This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) aims to develop quantum computing technology to enable a seamless transition between grid-following and grid-forming controls for inverter-based resources in renewable energy systems. The $275,000 project, with a period of performance from January 1, 2025 to December 31, 2027, will be conducted by Clemson University. The key objectives are to design variational quantum algorithms that can...
- The National Science Foundation (NSF) awarded a Project Grant of $275,000 under the Engineering program (CFDA 47.041) to The Pennsylvania State University (Penn State) to develop quantum computing algorithms for optimizing the efficiency, reliability, and resilience of renewable energy systems. The project, titled "Collaborative Research: Variational Quantum Technology for Seamless Transition Between Grid-Following and Grid-Forming Controls for Inverter-Based Resources," aims to design...
- The National Science Foundation (NSF) awarded a $300,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to The Pennsylvania State University (Penn State) to establish a quantum computing training program for power system engineers. The goal of this 2-year project is to create a training program that synthesizes knowledge from power engineering and quantum computing, enabling trainees to develop quantum algorithms to address complex challenges in...
- 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 $299,900 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports research by Virginia Polytechnic Institute & State University (Virginia Tech) on renewable energy integration and grid resiliency. The project focuses on developing new mathematical frameworks and computational strategies to enhance the modeling, monitoring, and analysis of power networks. This work aims to improve the management of...
- 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 National Science Foundation (NSF) Project Grant award, funded under the NSF Engineering (CFDA 47.041) program, aims to develop quantum computing-inspired algorithms to address optimization challenges in critical infrastructure systems, with a focus on power systems. The $449,922 award to Louisiana State University (LSU), to be completed by September 30, 2026, will integrate machine learning and distributed computing with quantum computing techniques to enable the solution of complex...