This $500,000 National Science Foundation (NSF) CAREER award for CFDA Program 47.041 (Engineering) to Arizona State University (ASU) aims to develop energy engineering solutions that account for the preferences and needs of diverse residential electricity consumers. The research will enable co-management of utility-owned and customer-owned distributed energy resources, such as rooftop solar, to transform how power distribution systems are operated. Key products and services to be delivered...
This National Science Foundation (NSF) Faculty Early Career Development (CAREER) Program grant award provides $508,455 to the University of Washington to support research that will leverage artificial intelligence technologies to enhance the resilience and efficiency of automated control systems in energy infrastructure. The project aims to develop an expert-guided, distributionally robust optimization framework that integrates reinforcement learning with mathematical optimization to improve...
This National Science Foundation (NSF) CAREER award provides $416,053 to Clarkson University to develop algorithms that manage the uncertainties of renewable energy generation in order to operate electric power systems reliably and cost-effectively. The project aims to enhance utility control room situational awareness, enable real-time assessment of transient instability risks, and redesign operating reserves to better account for the spatiotemporal variability of renewable sources like...
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...
This National Science Foundation (NSF) CAREER award, funded under the NSF Engineering program (CFDA 47.041), aims to investigate power system dynamics with large-scale integration of inverter-based resources (IBRs) through a multi-timescale modeling, simulation, and analysis framework. The $394,768 project, awarded to North Carolina State University, will establish a unified symbolic framework for device- and system-level modeling, develop advanced analytical methods for stability analysis,...
This National Science Foundation (NSF) CAREER project grant award, under the NSF Engineering (CFDA 47.041) program, aims to enhance electric power grid operators' situational awareness, improve dynamic model quality, and enable online controls for secure power system operation with high penetration of inverter-based resources (IBRs) such as solar, wind, and battery energy storage. The $397,111 award, granted to the University of Connecticut, will develop transformative changes to the use of...
This National Science Foundation (NSF) CAREER grant award under the Engineering program (CFDA 47.041) provides $517,612 to the University of Texas at Austin to develop new foundations of scalable and resilient distributed reinforcement learning for real-time autonomous cooperation in open multi-agent systems. The project aims to design new learning and control methods that enable agents to interact effectively in open systems, adapt gracefully in time-varying environments, and be resilient to...
This $260,000 National Science Foundation project grant will fund the development of data-enabled modeling, monitoring, and optimization algorithms targeting power system dynamics from 2022-2025. The University of Texas at Austin, through its parent organization the University of Texas System, will receive funding under the NSF Engineering program (CFDA 47.041) to correlate synchrophasor data and develop Gaussian process and stability-aware optimal power flow tools. Key outcomes will include...
The University of Texas at Austin received a $350,000 Project Grant award from the National Science Foundation Division of Electrical, Communications and Cyber Systems on September 1, 2021 to support work on "LEARNING-ENABLED MODELING, MONITORING, AND DECISION MAKING FOR DISTRIBUTION GRIDS." This award is part of NSF's Engineering (CFDA 47.041) program, which aims to improve quality of life and economic strength through engineering research and education. Specifically, the University...
This National Science Foundation (NSF) Project Grant award, under the NSF Engineering program (CFDA 47.041), provides $393,500 to Michigan State University to acquire a real-time simulator for studying power grid dynamics and developing solutions to enhance the stability, resilience, and cybersecurity of the U.S. power grid. The project aims to enable collaborative, multidisciplinary research to generate innovative solutions for hardening the power grid against extreme weather events, seismic...