旱区光伏组件疏水性表面自清洁研究与参数优选
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甘肃省教育厅青年博士基金项目(2021QB-046);甘肃省教育厅产业支撑计划项目(2021CYZC-27);兰州理工大学红柳优秀青年教师支持计划(201809)


Hydrophobic surface self-cleaning investigation and parameter selection of PV modules in arid areas
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    摘要:

    表面积尘会严重影响光伏组件的发电效率,可涂覆疏水性涂层提高其自清洁能力来降低积尘量。该研究将灰尘颗粒视为规则球体,基于颗粒接触力学理论,建立光伏组件表面与灰尘颗粒的黏附力学模型,简化光伏组件自清洁时灰尘的受力模型。采用不同疏水性涂层来改变光伏组件表面参数,计算得到光伏组件的自清洁性能与灰尘粒径、表面性能间的关系。研究结果表明:1)光伏组件表面自清洁性能与表面材料弹性模量和摩擦系数相关。2)清洁200 μm粒径以下的灰尘,光伏组件的表面弹性模量对自清洁性能起主要作用;清洁200 μm粒径以上的灰尘,表面摩擦系数起主要作用。3)涂覆不同的疏水性涂层,光伏组件可自清洁不同粒径范围的灰尘。4)以中国西北地区为例,灰尘粒径分布为250~500 μm,可选择涂覆弹性模量在0~2 700 MPa内,摩擦系数为0.1的疏水性涂层以提高光伏组件的自清洁能力。研究结果可为旱区光伏电站制备及涂覆疏水性涂层除尘提供理论依据。

    Abstract:

    Photovoltaic (PV) power generation can convert sunlight into electrical energy. There is an ever developing rapidly industry under the background of carbon peak and carbon neutrality. However, dust accumulation on the surface of PV modules can pose a serious threat to the efficiency of power generation. A hydrophobic coating with low surface energy can be expected to form on the surface, in order to reduce the dust accumulation for better self-cleaning of the PV module. In this study, a mechanical model of the adhesion between the surface of PV modules and dust particles was established to clarify the effect of hydrophobic coating surface properties on the self-cleaning ability of PV modules. The particle contact mechanics was selected to determine the adhesion force of dust particles, particularly with the elastic modulus, Poisson's ratio, and friction coefficient of surface materials. The simulation showed that the surface self-cleaning performance of PV modules was closely related to the elastic modulus and friction coefficient of surface materials, as well as the particle size of dust particles. There was also a strong relationship among the self-cleaning performance of PV modules, dust particle size, and surface performance. The surface elastic modulus played a major role in the self-cleaning performance of PV modules in the range of small particle size dust below 200 μm. With a larger particle size than 200 μm, the friction coefficient was dominated in the self-cleaning performance of PV modules. The self-cleaning of the PV modules varied in the different hydrophobic coatings, and the performance parameters of the PV module surface. The self-cleaning dust particles above 100 μm performed the best using the hydrophobic coating with the friction coefficient of 0.1-0.15 and elastic modulus of 0-100 MPa, whereas the self-cleaning dust particles above 500 μm were required for the hydrophobic coating with the friction coefficient of 0.1-0.15 and elastic modulus of 100-73 000 MPa. The hydrophobic coating with a friction coefficient of 0.1-0.45 and elastic modulus of 100-73 000 MPa was suitable for the PV modules to self-clean dust particles above 1 000 μm. The general soil particle size was divided into fine (100-250 μm), medium (250-500 μm), coarse (500-1 000 μm), very coarse sand (1 000-2 000 μm), and gravel (>2 000 μm). The optimal surface properties of hydrophobic coatings were obtained for the self-cleaning in the different dust particle sizes range. Specifically, the larger the particle size of dust was, the wider the range of elastic modulus and friction coefficient of the hydrophobic coating were. Consequently, the better surface properties of hydrophobic coatings were achieved in the elastic modulus of 0-100 MPa and the friction coefficient of 0.1-0.15, in order to clean the fine sand. The elastic modulus of 100-73 000 MPa and the friction coefficient of 0.1-0.6 were to clean the gravel. The PV power stations can be expected to select the hydrophobic coating for the self-cleaning requirements. The local dust particles can be optimized to reduce the loss of power generation efficiency for the cost saving of PV power stations. For example, once the dust of PV power plants was mainly medium sand (250-500 μm) in Northwest China, the surface properties of hydrophobic coatings can be the elastic modulus of 0-2 700 MPa and the friction coefficient of 0.1.

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张东,俞凯,闫承涛,刘畅,申永前,安周建.旱区光伏组件疏水性表面自清洁研究与参数优选[J].农业工程学报,2022,38(17):232-239. DOI:10.11975/j. issn.1002-6819.2022.17.025

Zhang Dong, Yu Kai, Yan Chengtao, Liu Chang, Shen Yongqian, An Zhoujian. Hydrophobic surface self-cleaning investigation and parameter selection of PV modules in arid areas[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE),2022,38(17):232-239. DOI:10.11975/j. issn.1002-6819.2022.17.025

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  • 收稿日期:2022-07-01
  • 最后修改日期:2022-08-21
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  • 在线发布日期: 2022-10-26
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