Soiling in Solar Energy Systems: The Role of the Thresholding Method in Image Analysis

Leonardo Micheli*, Greg P. Smestad, Muhammad Zahid Khan, Katja Lange, Huda M.I. Almughary, Mounir Abraim, Yanal Alamat, Cody B. Anderson, Said Bentouba, Benjamin Figgis, Pavan Fuke, Ahmed Amine Hachicha, Mounia Karim, Anil Kottantharayil, Alfredo A. Martinez-Morales, Ahmed Alami Merrouni, Douglas Olivares, Giovanni Picotti, Jorge Rabanal-Arabach, Florian WiesingerKlemens Ilse*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

The use of image analysis has often been suggested as a practical way to monitor the soiling accumulated on the surfaces of solar energy conversion devices. Indeed, the deposited soiling particles can be counted and characterized to calculate the area they cover, and this area can be converted into an energy loss. However, several particle counting methodologies exist and can lead to dissimilar results. This work focuses on the role of thresholding, an essential step where particles are distinguished from a background based on the pixel brightness. Sixteen automatic thresholding methods are assessed using 13 200 micrographs of glass coupons soiled at nine locations globally. In low-to-intermediate soiling conditions, the "Triangle" method is found to return the minimum coefficient of variation and a mean deviation closer to zero. On the other hand, methods assuming a bimodal distribution of pixel brightness underestimate the area coverage. In addition, since soiling can be unevenly distributed over a surface, different loss estimations can be returned when the same image analysis process is used on different spots on a sample's surface. For these reasons, image analysis should be repeated at multiple locations on each investigated surface.Image analysis has often been suggested as a practical way to monitor the soiling accumulated on solar energy conversion devices. However, several methodologies exist and can lead to dissimilar results. This work investigates the role of thresholding by analyzing 13 200 micrographs of soiled glass coupons and discusses some preliminary best practice guidelines for image-based soiling estimation.image (c) 2023 WILEY-VCH GmbH
Original languageEnglish
Article number2300654
Number of pages14
JournalSolar RRL
Volume8
Issue number3
DOIs
Publication statusPublished - Feb 2024

Keywords

  • Concentrating solar thermal
  • Image analysis
  • Photovoltaics
  • Soiling
  • Thresholds

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