Aerial Solar Thermal Radiometric Observer ("ASTRO")

Solar Dynamics (SD) proposes to incorporate artificial intelligence (AI) to quickly identify and catalog the status of each of the of collector components over the hundreds of thousands of components spread across large Concentrated Solar Power (CSP) fields. SD will extend our baseline aerial surveying technology to automate accurate technical assessment and rapid problem cataloging. This system will identify, assess, and catalog each component without interrupting normal plant operation. The system will use AI models to both identify solar receivers with lost vacuum or hydrogen infiltration from radiometric infrared images, and report directly observable issues such as broken mirrors or ball joint binding from visual images. Furthermore, information gathered from aerial surveying can feed additional post-processing to assess the optical performance of collectors in order to diagnose areas for improvement. For example, video files can be captured in such a way that the still images would be a direct input to the “Distant Observer” technology that has been developed by the National Renewable Energy Laboratory. Other analysis could include the detection of mirror soiling and heat transfer fluid leaks. Our team is well suited to propose this project. SD personnel have led development, design, and operations of some of the largest CSP power plants in the world. In addition, SD has built and deployed a baseline aerial survey system that is in need of further development.