The ESOLab has been named as one of several grant awardees under the Solar Energy Technologies Office of the Department of Energy – Energy Efficiency and Renewable Energy program. As principal investigator, Dr. Wagner will lead a team including researchers at the National Renewable Energy Lab and at industry partner BrightSource Energy.
The project leverages artificial intelligence and machine learning techniques to model a number of concentrating solar thermal power (CSP) plant operations in order to assist human operators in their decisions, especially during variable cloudiness conditions. The machine learning techniques will be applied to extensive, high-resolution, inferred DNI data, cloud profile and vector data, and related solar field thermal collection data in order to develop prescriptive models to optimize solar field collection under variable conditions while minimizing long-term receiver damage and other negative effects. The project will validate the method at an operating CSP facility and publish methodological details for broader use.
A full list of awards under the AI/ML topic can be found on EERE’s website.
Read the full article at: https://www.energy.gov/eere/solar/solar-energy-technologies-office-fiscal-year-2020-funding-program-seto-2020