SETO 2020 – Artificial Intelligence Applications in Solar Energy
Wenyuan Tang, NC State University Assistant Professor and FREEDM Faculty, received funding from the U.S. Department of Energy under a program created to support projects that will improve the affordability, reliability, and value of solar technologies on the U.S. grid and tackle emerging challenges in the solar industry. The SETO 2020 program funds projects that advance early-stage photovoltaic (PV), concentrating solar-thermal power (CSP), and systems integration technologies, and reduce the non-hardware costs associated with installing solar energy systems. Dr. Tang will be the Principal Investigator and lead of team of researchers to develop a system to predict the electric load in areas with large amounts of solar energy and enable more efficient grid operation.
Project Name: Day-Ahead Probabilistic Forecasting of Net-Load and Demand Response Potentials with High Penetration of Behind-the-Meter Solar-plus-Storage
Project Summary: This project leverages artificial intelligence and machine learning techniques to predict the electric load in areas with large amounts of solar energy and enable more efficient grid operation. The technology will also be able to forecast the capacity available to the grid from electric loads that can be turned on or off depending on the balance between electric demand and generation. Recent advances in artificial intelligence can enhance the accuracy of net-load forecasting, the observability of net-load variability, and the understanding of the coupling between net-load and demand response potentials. The two models under development for addressing hybrid probabilistic forecasting can provide better spatiotemporal information.