This National Science Foundation (NSF) Project Grant under the Geosciences program (CFDA 47.050) will deliver a transformative platform to enhance the resilience of rural electric power utilities against climate change and extreme weather events. The $250,000 award to Iowa State University of Science and Technology, spanning October 2024 to September 2027, will develop digital infrastructure to help utilities address challenges in maintaining electric power operations and service during...
The National Science Foundation Division of Electrical, Communications and Cyber Systems awarded Iowa State University a $500,714 Project Grant under the Engineering (47.041) federal grant program. The grant will support research from February 2021 through January 2026 to learn smart meter data to enhance distribution grid modeling and observability. Through this funding, Iowa State University researchers will analyze smart meter data to improve modeling of the electrical distribution system and...
The National Science Foundation (NSF) awarded a $289,837 CAREER grant under the Engineering program (CFDA 47.041) to South Dakota State University (SDSU) for the project "DECIPHERING LARGE-SCALE REAL OUTAGE DATA FOR CASCADING FAILURE ANALYSIS, PREVENTION, AND INTERVENTION". The research aims to develop a data-driven framework to better analyze, prevent, and intervene in cascading failures in complex engineered systems like power grids. Key activities include: Efficiently estimating...
The National Science Foundation awarded a $500,000 Project Grant to the University of Wisconsin-Madison through the Engineering (47.041) federal grant program. The grant will support research from March 2021 to February 2026 aimed at developing proactive approaches to distribution grid risk management. As the prime awardee, UW-Madison will leverage the funding to advance methods and technologies for identifying and addressing risks to the electric distribution system before outages or other...
This $295,149 Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) aims to address protection challenges arising from the increasing penetration of renewable energy in modern electric grids. The University of Denver is the prime recipient, and the project will run from August 1, 2024 to July 31, 2027. The project will explore novel model-driven and data-driven solutions to ensure dependable fault detection and secure relay operation for power grids...
This $220,000 National Science Foundation project grant under the Engineering program (CFDA 47.041) will support research at Kansas State University from July 2022 to June 2024 to leverage smart meter data for enhanced situational awareness of power distribution systems. The university will investigate fundamental approaches to effectively integrate advanced metering infrastructure data to increase operational awareness of distribution grids. Researchers will focus on integrating machine...
This Project Grant award of $240,000.00 from the National Science Foundation (NSF) under the Mathematical and Physical Sciences program (CFDA 47.049) supports collaborative research to develop novel topological and graph-based modeling techniques for integrating large-scale, distributed energy resources into power grid systems. The key objectives are to create a data-adaptive graph generation module, apply topological data analysis and higher-order network models, and design deep neural...
This National Science Foundation (NSF) Integrative Activities (CFDA 47.083) project grant for $762,500 awarded to Michigan State University aims to enhance the stability, resilience, and cybersecurity of the U.S. power grid. The project will acquire a real-time simulator to enable collaborative, multidisciplinary research on power grid dynamics, performance, and the development, testing, and validation of new solutions. Key focus areas include generating innovative solutions to enhance grid...
This five-year, $500,000 National Science Foundation project grant will support the development of new modeling and quantification techniques for interdependent power grid uncertainties at Syracuse University. Funded through NSF's Engineering Directorate under the CFDA 47.041 program, the grant aims to address challenges posed by increasing renewable energy resources and weather-related outages through hybrid stochastic models informed by machine learning, cascading failure analysis, and...
This $111,469 federal Project Grant awarded by the National Science Foundation (CFDA 47.049 - Mathematical and Physical Sciences) to Portland State University supports collaborative research on developing advanced topological modeling and machine learning techniques for the integration of ultra-high-dimensional distributed energy resources in wide-area power transmission networks. The key products and services to be delivered include: A data-adaptive graph generation module, topological data...