CX-102011: Graph-Learning-Assisted State and Event Tracking for Solar-Penetrated Power Grids with Heterogeneous Data Sources

Award Number: DE-EE0009356, CX(s) Applied: A9, Solar Energy Technologies Office, Location(s): MA, Office(s): Golden Field Office

Office of NEPA Policy and Compliance

January 21, 2021
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Award Number: DE-EE0009356
CX(s) Applied: A9
Solar Energy Technologies Office
Location(s): MA
Office(s): Golden Field Office

The U.S. Department of Energy (DOE) is proposing to provide federal funding to Northeastern University (NEU) to develop machine learning measurement software for solar photovoltaic (PV) distribution system applications. The software would interpret raw data from PV systems to provide state estimates and real-time model feedback. Existing PV system data would be used for algorithm development and modeling. The project would be completed over three Budget Periods (BPs), with a Go/No-Go Decision Point in between each BP.