Automatic heliostat learning for in situ concentrating solar power plant metrology with differentiable ray tracing.

ABSTRACT: Concentrating solar power plants are a clean energy source capable of competitive electricity generation even during night time, as well as the production of carbon-neutral fuels, offering a complementary role alongside photovoltaic plants. In these power plants, thousands of mirrors (heliostats) redirect sunlight onto a receiver, potentially generating temperatures exceeding 1000°C. Practically, such efficient temperatures are never attained. Several unknown, yet operationally crucial parameters, e.g., misalignment in sun-tracking and surface deformations can cause dangerous temperature spikes, necessitating high safety margins. For competitive levelized cost of energy and large-scale deployment, in-situ error measurements are an essential, yet unattained factor. To tackle this, we introd

SUBMITTER: Pargmann M 

PROVIDER: S-EPMC11324880 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature