Scholarlink

<p>Integrating renewable energy is critical for maintaining grid stability while striving towards global climate goals. Concentrating solar power tower plants offer a promising solution but their competitiveness is currently hindered by high operational costs, limited data availability and slow adoption of emerging technologies. To address these barriers, here we introduce PAINT, a FAIR (findable, accessible, interoperable and reusable) open-access database for operational solar tower plant data. PAINT provides 849 GB of high-resolution data collected over multiple years from the Jülich solar tower plant, including heliostat properties, calibration and deflectometry measurements and fine-grained weather data. The database is organized using the SpatioTemporal Asset Catalog metadata specification and supports the development of digital twins, artificial intelligence-based calibration methods, predictive maintenance and improved solar flux prediction. We also introduce standardized benchmarks to promote reproducibility and fair comparisons. Providing access to high-quality data, PAINT enables broader participation in solar research, accelerates innovation and facilitates data-driven solutions in solar tower power plant research.</p>

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The PAINT database for operational concentrating solar power plant data following FAIR data principles

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月16日

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  • 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

摘要

Integrating renewable energy is critical for maintaining grid stability while striving towards global climate goals. Concentrating solar power tower plants offer a promising solution but their competitiveness is currently hindered by high operational costs, limited data availability and slow adoption of emerging technologies. To address these barriers, here we introduce PAINT, a FAIR (findable, accessible, interoperable and reusable) open-access database for operational solar tower plant data. PAINT provides 849 GB of high-resolution data collected over multiple years from the Jülich solar tower plant, including heliostat properties, calibration and deflectometry measurements and fine-grained weather data. The database is organized using the SpatioTemporal Asset Catalog metadata specification and supports the development of digital twins, artificial intelligence-based calibration methods, predictive maintenance and improved solar flux prediction. We also introduce standardized benchmarks to promote reproducibility and fair comparisons. Providing access to high-quality data, PAINT enables broader participation in solar research, accelerates innovation and facilitates data-driven solutions in solar tower power plant research.