This $315,000 federal Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) supports the development of new methods to robustly analyze and control large-scale networked systems with uncertain and variable delays. Specifically, the project will combine integral quadratic constraint and partial integral equation frameworks to enable accurate modeling and control of nonlinear systems with known and uncertain delay components. This work has direct applications...
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...
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...
This three-year $300,000 Project Grant from the National Science Foundation's Division of Electrical, Communications and Cyber Systems, under the Engineering (47.041) federal grant program, funds research at New York University to advance the mathematical foundations and develop new tools for real-time distributed optimization-based control of large-scale nonlinear uncertain systems. Specifically, the award supports three research tasks: 1) synthesizing distributed optimization algorithms robust...
This Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) aims to enhance electric power grid operators' situational awareness, improve dynamic model quality, and enable online controls to ensure secure power system operation with high penetration of inverter-based resources (IBRs) such as solar, wind, and battery energy storage. The $397,111 award, effective February 1, 2025 through January 31, 2030, will fund research to develop a generalized,...
This $300,000 National Science Foundation project grant supports research into distributed optimization-based control of large-scale nonlinear systems with uncertainties from 2022-2025. Funded under the NSF Engineering program (CFDA 47.041), the award to the University of California, San Diego will advance mathematical foundations for distributed optimization algorithms robust to uncertainties. Researchers will design tracking controllers for local systems to follow optimization-derived...
This $297,881 federal Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) supports collaborative research to advance the theory and algorithms for distribution control. The research aims to enable precision manufacturing of materials with desired properties and coordination/control of large autonomous agent swarms, promoting national prosperity and welfare. The project will address key challenges in nonlinear agent dynamics, inter-agent...
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...
Arizona State University was awarded a $500,000 Project Grant from the National Science Foundation Division of Electrical, Communications and Cyber Systems. The award is part of NSF's Engineering program (CFDA 47.041) to support CAREER: FAITHFUL, REDUCIBLE, AND INVERTIBLE LEARNING IN DISTRIBUTION SYSTEM FOR POWER FLOW. Under this five-year project grant awarded February 1, 2021 with a completion date of January 31, 2026, Arizona State University will conduct research at its Tempe, Arizona campus...
This $280,000 Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) will support the development of new theory and methods to address network-level uncertainty in the control of large-scale networked systems. The research will integrate random graph theory, particularly graphon theory, with structural system theory to model and understand uncertainty in the communication topology of multi-agent control systems. The key goals are to (1) formulate new...