Accurate and scalable receiver-level flux prediction: A fully data-driven solution

Solar Energy, vol. 299, pp. 113631

Abstract

Concentrated Solar Technologies (CST) systems, particularly central tower configurations with heliostat fields, play a critical role in the renewable energy landscape. By focusing sunlight from thousands of heliostats onto a central receiver, these systems generate high-temperature heat, which serves as a key resource for dispatchable power generation and industrial processes. Accurate receiver-level flux prediction, which depends on precise heliostat characterization, is essential for optimizing efficiency and operational control. However, existing characterization methods face trade-offs between accuracy and scalability, limiting their practicality for large-scale deployment. To overcome these limitations, this study introduces a fully data-driven framework that unifies heliostat characterization and flux prediction, leveraging operational data from standard calibration procedures. Expanding upon previous work that employed StyleGAN for beam-characterization-based predictions, this approach advances the methodology to achieve accurate receiver-level flux predictions. While the prior method demonstrated a proof of concept for a unified data-driven approach, it remained constrained to flux predictions on the calibration target itself. This study introduces key innovations, including aim point generalization strategies and a novel receiver projection technique, effectively bridging the gap between beam-characterization-based heliostat characterization and accurate receiver-level flux predictions. The proposed Transformer-based architecture achieves receiver-level focal spot prediction errors below 12%, exceeding the accuracy of state-of-the-art deflectometry-enhanced ray tracing. By relying exclusively on standard calibration images, the method remains both cost-efficient and scalable, offering a practical solution for large-scale CST applications.

Authors 4

1. Mathias Kuhl corresponding

   Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)

   Affiliation as printed

   DLR, Institute of Solar Research, Linder Höhe, Köln, 51147, Germany

2. Max Pargmann

   Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)

   Affiliation as printed

   DLR, Institute of Solar Research, Linder Höhe, Köln, 51147, Germany

3. Daniel Maldonado Quinto
4. Robert Pitz‐Paal Aachen Chair of Solar Technology

   Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) · RWTH Aachen University

   Affiliation as printed

   DLR, Institute of Solar Research, Linder Höhe, Köln, 51147, Germany

   RWTH Aachen University, Chair of Solar Technology, Linder Höhe, Köln, 51147, Germany