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In-Situ Solar Tower Power Plant Optimization by Differentiable Raytracing

Pargmann, Max and Ebert, Jan and Maldonado Quinto, Daniel and Pitz-Paal, Robert and Kesselheim, Stefan (2023) In-Situ Solar Tower Power Plant Optimization by Differentiable Raytracing. Nature Communications. Nature Publishing Group. ISSN 2041-1723. (Submitted)

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Solar tower power plants deliver climate-neutral electricity and process heat and can play a key role to facilitate the ongoing energy transition. These plants reflect sunlight with thousands of mirrors (heliostats) to a receiver and can generate temperatures over 1000°C. In practice, a plant must be operated with safety margins as even small surface deformations and heliostat misalignments can locally lead to dangerous temperature peaks. These imperfections are difficult to assess and limit the plant's efficiency, which hinders commercial success in a competitive market. We present a computational technique that predicts the incident power distribution of each heliostat including the inaccuracies based solely on focal spot images that are already acquired in most solar power plants. The method combines differentiable ray tracing with a smooth parametric description of the heliostat and reconstructs flawed mirror surfaces with sub-millimeter precision. Applied at the solar tower plant in Jülich, our approach outperforms all alternatives in accuracy and reliability. The approach can be integrated into the existing infrastructure and plant control at low cost, leading to increased efficiency of existing and decreased expenses for future power plants and supports establishing a new, green energy technology. For other fields, our approach can be a blueprint. We implement a common simulation technique in the Machine Learning framework PyTorch, leveraging automatic differentiation and GPU computation. By combining gradient-based optimization methods and a tunable parametric heliostat model, we overcome the high data requirements of data-centric methods while at the same time maintaining the flexibility required for modeling a complex real-world system.

Item URL in elib:https://elib.dlr.de/197409/
Document Type:Article
Title:In-Situ Solar Tower Power Plant Optimization by Differentiable Raytracing
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Pargmann, MaxUNSPECIFIEDhttps://orcid.org/0000-0002-4705-6285UNSPECIFIED
Ebert, JanJülich Supercomputing CentreUNSPECIFIEDUNSPECIFIED
Maldonado Quinto, DanielUNSPECIFIEDhttps://orcid.org/0000-0003-2929-8667UNSPECIFIED
Pitz-Paal, RobertUNSPECIFIEDhttps://orcid.org/0000-0002-3542-3391UNSPECIFIED
Kesselheim, StefanJülich Supercomputing CentreUNSPECIFIEDUNSPECIFIED
Journal or Publication Title:Nature Communications
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
Publisher:Nature Publishing Group
Keywords:Solar Tower, Heliostat Field, Differentiable Ray Tracing, Surface Diagnosis, NURBS
HGF - Research field:Energy
HGF - Program:Materials and Technologies for the Energy Transition
HGF - Program Themes:High-Temperature Thermal Technologies
DLR - Research area:Energy
DLR - Program:E SW - Solar and Wind Energy
DLR - Research theme (Project):E - Smart Operation
Location: Köln-Porz
Institutes and Institutions:Institute of Solar Research > Solar Power Plant Technology
Deposited By: Pargmann, Max
Deposited On:28 Sep 2023 12:29
Last Modified:28 Sep 2023 12:29

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