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) Engineering program awarded a $135,956 project grant to South Dakota State University (SDSU) to develop a highly efficient, modular, and scalable power system that integrates photovoltaic, energy storage, and smart micro-inverter technologies. The goal is to create a novel power conversion system architecture and control capabilities to enable greater penetration of solar energy into the electric grid and support grid stability and resilience. The key...
The National Science Foundation awarded a $280,000 Project Grant to the University of Texas at Austin under the Engineering (47.041) federal grant program. The award will support research and development of grid-forming inverter technologies to advance the energy transition and increase renewable energy grid integration. Key deliverables include optimization of grid-forming voltage control loops; development of advanced functionalities for three-port microinverters integrating solar, storage and...
This $270,000 Project Grant from the National Science Foundation's Engineering program (CFDA 47.041) supports the development of grid-forming inverter technologies to advance the energy transition and increase renewable energy grid integration. A joint team from the University of Texas at Austin and the University of Central Florida will optimize grid-forming voltage control, develop advanced three-port microinverters with black start and islanded operation capabilities, and design innovative...
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 National Science Foundation (NSF) Engineering program project grant to the University of Tennessee aims to develop a unified multi-timescale modeling and simulation framework for analyzing the complex dynamics of inverter-dense power grids integrating renewable energy resources. The $350,257 award, with a project period from Mar 1, 2024 to Feb 28, 2027, will establish heterogeneous multiscale methods and semi-analytical solution techniques to enable accurate and efficient power system...
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 $275,000 Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) aims to develop new techniques for fault detection in inverter-dominated power systems. The project will design auxiliary signal-based fault detection schemes to improve reliability in power grids with high penetration of renewable energy resources like wind and solar, which can pose challenges for conventional detection methods. The research will characterize the necessary auxiliary...
This Project Grant award, valued at $397,111 and provided by 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 key research objectives include developing a generalized observability theory for...
This $394,768 National Science Foundation (NSF) Engineering Program (CFDA 47.041) grant awarded to North Carolina State University (NC State) aims to investigate power system dynamics with large-scale integration of inverter-based resources (IBRs). The project will develop a unified framework to model, analyze, and simulate fast network transients, switched converters, and slow electromechanical dynamics in converter-dominated power systems. Key deliverables include: 1) establishing a symbolic...