4.3 Article

Resilience of industrial PV module glass coatings to cleaning processes

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AIP Publishing
DOI: 10.1063/5.0024452

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资金

  1. Federal Ministry of Economic Affairs and Energy of Germany (BMWi) in the WIPANO-project ROSE [03TNH022A]
  2. state of SaxonyAnhalt within the project MetroLarge [FuE 065/17]
  3. f | solar GmbH

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Soiling, the accumulation of dust, is a detrimental influencing factor for solar energy generation in desert climates, as it blocks the sun light and therefore reduces the energy yield of photovoltaic (PV) modules. Accordingly, soiling requires mitigation by frequent cleaning. However, regular cleaning of PV modules can damage glass surfaces and commonly used anti-reflective coatings (ARCs), which typically enable 2-3% or even higher increases in the power output. Within this study, the damage potential of dry manual cleaning on uncoated solar glass and two different commercial ARCs is examined. For this, a cleaning test apparatus and methodology applicable to full size PV modules were developed. The changes in the optical behavior of coated and uncoated glass samples were investigated both theoretically and experimentally, including the analysis of spectroscopic reflectance and microstructural damage patterns. It is found that dry brushing on dusty surfaces causes only minor damage to uncoated glass surfaces with no changes in hemispherical reflectance, even at high numbers of brush cycles. In contrast, both the tested coatings indicate significant reductions of the AR performance, already after 100 brush cycles with increasing reflectance up to 2.3% at 600 nm. Furthermore, the coatings indicated different stabilities during extended abrasion testing, but still retained the AR properties after 500 cycles of testing, reflecting harsh and bi-weekly cleaning over 20 years of operation. Localized coating removal and-to a less extent-coating thinning were identified as ARC degradation mechanisms, which were supported by spectroscopy experimental and simulation results for microstructural analysis of the samples.

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