CX-102022: Day-Ahead Probabilistic Forecasting of Net-Load and Demand Response Potentials with High Penetration of Behind-the-Meter Solar-plus-Storage

Award Number: DE-EE0009357, CX(s) Applied: A9, Solar Energy Technologies Office, Location(s): NC, Office(s): Golden Field Office

Office of NEPA Policy and Compliance

January 26, 2021

Award Number: DE-EE0009357
CX(s) Applied: A9
Solar Energy Technologies Office
Location(s): NC
Office(s): Golden Field Office

The U.S. Department of Energy (DOE) is proposing to provide federal funding to North Carolina State University (NCSU) to develop net-load forecasting models for behind-the-meter solar and energy storage applications. Machine learning algorithms would be developed and tested through application to existing data sets. The project would be completed over three Budget Periods (BPs), with a Go/No-Go Decision Point in between each BP.

CX-102022: Day-Ahead Probabilistic Forecasting of Net-Load and Demand Response Potentials with High Penetration of Behind-the-Meter Solar-plus-Storage (199.34 KB)