Project Grant DESC0013818

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...

Coolcad Electronics, LLC received a $200,000 Project Grant award from the Department of Energy Office of Science on June 27, 2022 to support development of low-cost hybrid SiC/GaN-based single-stage microinverters with integrated planar magnetics technology. The project aims to deliver this technology by March 26, 2023. The award is being made through the Office of Science Financial Assistance Program (CFDA #81.049), which supports basic research to deliver scientific discoveries and tools...

This National Science Foundation (NSF) Project Grant awarded under the Mathematical and Physical Sciences program (CFDA 47.049) provides $350,000 to the University of California, Santa Barbara (UCSB) for a 3-year project to develop new tools and frameworks for optimizing the operation and benefits of battery energy storage systems (BESS) in modern power grids. The project will create stochastic modeling approaches to address short-term BESS operations, BESS bidding strategies for ancillary...

The University of South Florida received a $350,000 project grant award from the National Science Foundation to develop dynamic model identification techniques for inverter-based distributed energy resources. Funded under the NSF Engineering program (CFDA 47.041), this three-year award running from May 2021 through April 2024 aims to improve understanding and control of inverters that interface distributed generation systems such as solar panels to the electric grid. By advancing inverter...

This three-year, $110,851 project grant from the National Science Foundation's Computer and Information Science and Engineering program aims to develop a cyber resilient 5G-enabled virtual power system to address growing power demands. Specifically, the awardee, Texas A&M University-Kingsville, will design and implement a smart artificial intelligence-based microinverter for pole-mounted solar power systems with energy storage, connected to low-voltage distribution networks. Data from the...

This $249,980 National Science Foundation (NSF) EAGER project grant awarded to North Dakota State University (NDSU) aims to develop a novel network-based framework for analyzing and mitigating sub-synchronous oscillations in inverter-dominated power grids. The project will provide new insights into the mechanisms driving these oscillations, which can jeopardize grid stability and reliability as renewable energy sources with inverters are increasingly integrated. The framework is expected to...

This Project Grant from the National Science Foundation's $200,000 Engineering program (CFDA 47.041) will fund research at the University of California, San Diego to develop a new data-driven power systems control framework with stability guarantees. The three-year award beginning March 2022 aims to design reinforcement learning algorithms for inverter-based frequency and voltage control of power grids that provide formal stability through a novel approach bridging Lyapunov control theory and...

New Mexico State University (NMSU), through its Office of Sponsored Programs, has been awarded a $200,000 project grant from the National Science Foundation to develop machine learning solutions for operating power distribution grids with high levels of inverter-based energy resources. The two-year award, made under the Engineering (47.041) federal grant program, will support research objectives including developing sample-efficient hybrid learning techniques combining deep reinforcement...

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...

The National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems awarded the University of Texas at Austin a $250,000 Project Grant under the NSF Engineering program (CFDA 47.041) to develop novel learning-based approaches for estimating the flexibility amount of grid edge resources (GERs) and designing equitable resource coordination and management methods. The project aims to transform the management of flexible energy resources in distribution electricity...