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Modelling photovoltaic soiling losses through optical characterization

AbstractThe accumulation of soiling on photovoltaic (PV) modules affects PV systems worldwide. Soiling consists of mineral dust, soot particles, aerosols, pollen, fungi and/or other contaminants that deposit on the surface of PV modules. Soiling absorbs, scatters, and reflects a fraction of the incoming sunlight, reducing the intensity that reaches the active part of the solar cell. Here, we report on the comparison of naturally accumulated soiling on coupons of PV glass soiled at seven locations worldwide. The spectral hemispherical transmittance was measured. It was found that natural soiling disproportionately impacts the blue and ultraviolet (UV) portions of the spectrum compared to the visible and infrared (IR). Also, the general shape of the transmittance spectra was similar at all the studied sites and could adequately be described by a modified form of the Ångström turbidity equation. In addition, the distribution of particles sizes was found to follow the IEST-STD-CC 1246E cleanliness standard. The fractional coverage of the glass surface by particles could be determined directly or indirectly and, as expected, has a linear correlation with the transmittance. It thus becomes feasible to estimate the optical consequences of the soiling of PV modules from the particle size distribution and the cleanliness value.
- Academy of Scientific and Innovative Research India
- National Renewable Energy Laboratory United States
- Physical Measurement Laboratory United States
- Heriot-Watt University United Kingdom
- Heriot-Watt University United Kingdom
Photovoltaic Arrays, Cleanliness, Particle, PV, Oceanography, soiling; experimental; transmittance; spectrum, Turbidity, Size, Materials Science and Engineering, Ångström turbidity equation, Transmittance, Photovoltaic system, Ultraviolet, Microscopy, Soiling, Energy, Ecology, Physics, Q, R, Imaging and sensing, Geology, Particle size, Photovoltaic Efficiency, Chemistry, Physical chemistry, Particle (ecology), Physical Sciences, Sunlight, Medicine, Infrared, 570, Particle-size distribution, PV System, Energy science and technology, Science, Optical spectroscopy, Partial Shading, 530, Modelling, Article, Environmental science, Techniques and instrumentation, Optical physics, Meteorology, Artificial Intelligence, Machine Learning Methods for Solar Radiation Forecasting, Optical techniques, Optoelectronics, Aerosol, Biology, Renewable Energy, Sustainability and the Environment, Electronics, photonics and device physics, Building Integrated Photovoltaics, Optics, Photovoltaic Maximum Power Point Tracking Techniques, FOS: Earth and related environmental sciences, Materials science, 620, Photovoltaics, Optics and photonics, FOS: Biological sciences, Computer Science, Solar Thermal Energy Technologies
Photovoltaic Arrays, Cleanliness, Particle, PV, Oceanography, soiling; experimental; transmittance; spectrum, Turbidity, Size, Materials Science and Engineering, Ångström turbidity equation, Transmittance, Photovoltaic system, Ultraviolet, Microscopy, Soiling, Energy, Ecology, Physics, Q, R, Imaging and sensing, Geology, Particle size, Photovoltaic Efficiency, Chemistry, Physical chemistry, Particle (ecology), Physical Sciences, Sunlight, Medicine, Infrared, 570, Particle-size distribution, PV System, Energy science and technology, Science, Optical spectroscopy, Partial Shading, 530, Modelling, Article, Environmental science, Techniques and instrumentation, Optical physics, Meteorology, Artificial Intelligence, Machine Learning Methods for Solar Radiation Forecasting, Optical techniques, Optoelectronics, Aerosol, Biology, Renewable Energy, Sustainability and the Environment, Electronics, photonics and device physics, Building Integrated Photovoltaics, Optics, Photovoltaic Maximum Power Point Tracking Techniques, FOS: Earth and related environmental sciences, Materials science, 620, Photovoltaics, Optics and photonics, FOS: Biological sciences, Computer Science, Solar Thermal Energy Technologies
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