Project Grant 2420958

Award Date 7/1/25
Completion Date 6/30/28
Dollars Obligated $111K
Federal Grant Program
47.049
Assistance Type
Project Grant
Place of Performance
Portland, OR 97201, USA
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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 analysis techniques with multiple filtrations, higher-order network models, and deep neural network input layers to capture the ubiquitous, high-dimensional information structures and topological signatures of power systems.
  • An open-source software library providing topological summaries learned from multi-filtration of power system data, enabling new applications of machine learning and deep learning for large-scale power system analysis.
  • Training of students in cross-disciplinary research at the intersection of computer science, mathematics, data science, and electrical engineering.

This 3-year project, which commenced on Jul 1, 2025, aims to enhance the reliability, resiliency, and quality of power grids, lower energy costs, and reduce the impact of extreme weather events on power outages.

Generated 7/15/25, 8:02 AM