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Synergistic optimization analysis of dust cleaning efficiency and power generation enhancement on super-hydrophobic photovoltaic panel for droplets with different Weber numbers

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  • Han, Zunshi
  • Lu, Hao
  • Zhao, Wenjun
  • Zheng, Chuanxiao

Abstract

Dust deposition on photovoltaic panels severely degrades power output. The combination of droplets and hydrophobic surfaces can effectively solve this problem. However, the underlying physics of droplet-based cleaning and its quantitative impact on generation remain poorly understood. This study employs an innovative multiphysics framework, integrating computational fluid dynamics with the discrete element method, coupled with a photovoltaic power prediction model that links dust deposition directly to photo-generation physics, to simulate droplet-mediated dust cleaning and its impact on power output. The droplet dynamics are analyzed using a multiphase volume of fluid model, and the dust particle behavior are revealed by Edinburgh elastic-plastic adhesion model. Smaller particles (dp ≤ 100 μm) are readily removed, achieving a dust removal rate of 22.7 % at dp = 50 μm. However, particles that agglomerate due to cohesive forces after droplet cleaning become difficult to remove. Droplet cleaning efficiency correlates with the Weber number. At Weber number = 1.91, both coverage radius and contact frequency reach optimal values, yielding a peak dust removal rate of 14.1 %. Coupling dust deposition density with cleaning efficiency results and inputting them into a photovoltaic power generation model indicates that each 1 g/m2 increase in deposition density causes a maximum power degradation of 2.26 %. Under droplet cleaning conditions with Weber number = 1.91, photovoltaic power significantly increases by 2.9 % under small particle conditions. This study provides theoretical basis and parameter optimization paradigms for self-cleaning design of super-hydrophobic photovoltaic.

Suggested Citation

  • Han, Zunshi & Lu, Hao & Zhao, Wenjun & Zheng, Chuanxiao, 2026. "Synergistic optimization analysis of dust cleaning efficiency and power generation enhancement on super-hydrophobic photovoltaic panel for droplets with different Weber numbers," Renewable Energy, Elsevier, vol. 262(C).
    • Handle: RePEc:eee:renene:v:262:y:2026:i:c:s0960148126001692
    DOI: 10.1016/j.renene.2026.125344
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    References listed on IDEAS

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    1. Hu, Shan & Liu, Yan & Liu, Weidong & Wen, Hailang & Lan, Junjie, 2025. "Assessment methodology for photovoltaic power generation based on multiple random factors of dust deposition," Renewable Energy, Elsevier, vol. 250(C).
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