HMC Contributes to FAIRification of PAINT Database Published in Nature Energy

A recently published article in Nature Energy introduces PAINT, the first freely accessible operational database for solar power tower plants. The database provides real-world operational data from the Jülich Solar Tower test power plant and creates a valuable basis for developing new AI methods, digital twins, and more efficient solar thermal energy systems.

Solar power tower plants use movable mirrors, known as heliostats, to direct sunlight onto a receiver at the top of a central tower. The generated heat can be stored, converted into electricity, or used in industrial processes. This makes the technology highly relevant for the energy transition, especially as stored heat can help provide energy when sunlight is not immediately available.

Until now, however, researchers have lacked openly available real-world operational data to develop, compare, and test new methods for safer and more efficient plant operation. PAINT addresses this gap by providing a structured and freely accessible dataset from the Jülich Solar Tower, including operational data from 2021 to 2024, information on heliostat positions and movements, image data, mirror surface measurements, and weather data.

HMC is proud to have supported our colleague Nicolas Blumenröhr from HMC Hub FAIR Data Commons, who supported the FAIRification of the PAINT database. This included the development of FAIR Digital Objects to make metadata and data structures more machine-actionable, interoperable, and reusable. These contributions help to facilitate data discovery, access, iterpretation, and integration into secondary use cases such as AI workflows and digital twin applications.

The publication is also a strong example of collaboration within the Helmholtz ecosystem. Together with Helmholtz AI, one of HMC’s sister platforms and partners from KIT and DLR, the work connects domain-specific energy research with research data management, AI-readiness, and FAIR data practices.

By making high-quality operational data openly available and reusable, PAINT provides a foundation for further research on solar tower power plants and supports the development of data-driven methods for the energy transition.

Original publication:
Kaleb Phipps, Mathias Kuhl, Marie Weiel, Marlene Busch, Jan Lewen, Nicolas Blumenröhr, Daniel Maldonado Quinto, Charlotte Debus, Felix Göhring, Oliver Kaufhold, Achim Streit, Robert Pitz-Paal, Markus Götz & Max Pargmann: The PAINT Database for Operational Concentrating Solar Power Plant Data Following FAIR Data Principles. Nature Energy, 2026. DOI: 10.1038/s41560-026-02070-1.