This NSF Engineering program (CFDA 47.041) grant award of $181,004 to Purdue University, awarded on October 1, 2024, aims to develop data-enabled and physics-informed modeling, monitoring, and optimization solutions targeting power system dynamics. The project will explore innovative approaches to leverage synchrophasor data for power grid dynamic modeling, Gaussian process-based inference of grid dynamic signals, and stability-aware optimal power flow solutions. The research results will also...
This National Science Foundation (NSF) CAREER grant, awarded under the Engineering program (CFDA 47.041), provides $258,677 to Boston University to develop feedback-based online algorithms for power grid optimization and control. The project aims to overcome technological and operational barriers associated with large-scale integration of distributed energy resources (DERs) in power grids. Key products and services to be delivered include: Real-time optimization architectures that tightly...
This $330,000 National Science Foundation project grant supports research at Purdue University from November 2022 through July 2025 to develop analytics and a prototype system for adaptive, human-centric coordination of demand-side flexibility at scale in electric power distribution networks. The goal is to enable actionable demand-side flexibility through adequate representation of consumer constraints and interactions with the energy system and provider. Researchers will develop learning...
This National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems Federal Project Grant, awarded under CFDA 47.041 Engineering program, provides $350,000 to Arizona State University to develop advanced dynamic modeling and stability assessment tools for distribution power systems with high penetration of distributed energy resources (DERs). The key objectives are to: 1) identify and model critical nonlinear dynamics missing from existing load models, 2) create...
This $395,896 federal Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) supports research at Purdue University to develop the conceptual and algorithmic foundations for grid-responsive electrified transportation systems. The overarching goal is to enable monetization of the spatiotemporal flexibility in electric vehicle (EV) charging loads to provide valuable grid services, thereby accelerating the decarbonization of both transportation and...
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...
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 $199,964 federal Project Grant awarded by the National Science Foundation (NSF) Engineering program (CFDA 47.041) will fund research at the University of California, Santa Barbara (UCSB) to address challenges and opportunities presented by the rapid proliferation of grid-edge resources (GERs) in modern power systems. The project aims to develop novel data-driven control strategies and advance the understanding of GER behavior to ensure the safe and secure operation of these distributed...
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 $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...