In-situ UNet-based heliostat beam characterization method for precise flux calculation using the camera-target method

Concentrated Solar Power (CSP) utilizing solar tower power plants exhibits significant potential for dispatchable sustainable power generation and fuel production, by concentrating up to hundred thousand focal spots of individual mirrors onto one surface. The irradiance on the receiver is a critical parameter for power plant operators, not only to prevent component-damaging temperature peaks and gradients but also to optimize the distribution of heliostat’s focal spots. Therefore, recent approaches aim to exploit images of isolated focal spots on a Lambertian target, taken on a day-to-day basis in most commercial power plants, to achieve more accurate flux predictions. State-of-the-art methods for flux measurements require additional equipment and are mostly time-intensive. This study introduces a novel methodology to derive single heliostat irradiance profiles using simple digital camera images, employing an image-to-image neural network. The model we propose is capable of generating accurate, high-resolution flux distributions from single images. It uniquely accounts for the target surface’s irregularities and reflectivity as well as background irradiation, factors critical for precise measurements of individual focal spots. By incorporating these factors, our methodology offers a new scaling approach for the measured flux density based on a calculated total flux, obviating the need for additional equipment such as flux gauges or moving bars. This enables effortless integration into the daily calibration routine in-situ using the camera-target method. This seamless integration not only supports existing flux prediction methodologies but also paves the way for future enhancements by potentially improving the accuracy of overall flux prediction. • Introduces a UNet-based approach for enhanced flux calculation in camera-target method in CSP plants using digital camera images. • Addresses traditional camera-target method limitations by accounting for background irradiation and surface irregularities. • Seamlessly integrates UNet architecture into existing heliostat calibration workflows in CSP plants. • Method enables calculation of absolute flux values without the need of flux gauges.

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Publication Details

Journal
Solar Energy
Published
2024-08-09
DOI
https://doi.org/10.1016/j.solener.2024.112811
Citations
5
Primary Topic
Spacecraft and Cryogenic Technologies
Type
article
Field-Weighted Citation Impact
6.49

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article

In-situ UNet-based heliostat beam characterization method for precise flux calculation using the camera-target method

Mathias Kuhl, Mehdi Cherti, Robert Pitz‐Paal, Daniel Maldonado Quinto et al.
5 citations
Solar Energy
Spacecraft and Cryogenic Technologies
6.49
article

In-situ UNet-based heliostat beam characterization method for precise flux calculation using the camera-target method

Mathias Kuhl, Mehdi Cherti, Robert Pitz‐Paal, Daniel Maldonado Quinto, Max Pargmann, Jenia Jitsev
article en
5 citations

Abstract

Concentrated Solar Power (CSP) utilizing solar tower power plants exhibits significant potential for dispatchable sustainable power generation and fuel production, by concentrating up to hundred thousand focal spots of individual mirrors onto one surface. The irradiance on the receiver is a critical parameter for power plant operators, not only to prevent component-damaging temperature peaks and gradients but also to optimize the distribution of heliostat’s focal spots. Therefore, recent approaches aim to exploit images of isolated focal spots on a Lambertian target, taken on a day-to-day basis in most commercial power plants, to achieve more accurate flux predictions. State-of-the-art methods for flux measurements require additional equipment and are mostly time-intensive. This study introduces a novel methodology to derive single heliostat irradiance profiles using simple digital camera images, employing an image-to-image neural network. The model we propose is capable of generating accurate, high-resolution flux distributions from single images. It uniquely accounts for the target surface’s irregularities and reflectivity as well as background irradiation, factors critical for precise measurements of individual focal spots. By incorporating these factors, our methodology offers a new scaling approach for the measured flux density based on a calculated total flux, obviating the need for additional equipment such as flux gauges or moving bars. This enables effortless integration into the daily calibration routine in-situ using the camera-target method. This seamless integration not only supports existing flux prediction methodologies but also paves the way for future enhancements by potentially improving the accuracy of overall flux prediction. • Introduces a UNet-based approach for enhanced flux calculation in camera-target method in CSP plants using digital camera images. • Addresses traditional camera-target method limitations by accounting for background irradiation and surface irregularities. • Seamlessly integrates UNet architecture into existing heliostat calibration workflows in CSP plants. • Method enables calculation of absolute flux values without the need of flux gauges.

Solar EnergyVol. 279
Forschungszentrum Jülich (DE), LVR-Klinik Köln (DE), RWTH Aachen University (DE)
Helmholtz-Gemeinschaft, Helmholtz Association
Affordable and clean energy
Openalex Percentile: Top 4%
Spacecraft and Cryogenic Technologies
6.49
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