Deposition Characteristics of Aerosol Particles on the Surface of PV Modules: Numerical Study. Issue 2 (15th December 2022)

• Record Type: Journal Article
• Authors: Qiu, Yunfeng; Guo, Xiao; Wang, Yahui; Tian, Rui; Wei, Chuan; Liu, Shuang
• Is Part Of: Advanced theory and simulations. Volume 6:Issue 2(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-12-15
• Subjects: aerosol particles -- deposition rate -- numerical simulation -- PV modules -- stepwise linear regression; Science -- Simulation methods -- Periodicals; Science -- Methodology -- Periodicals; Engineering -- Simulation methods -- Periodicals; Engineering -- Methodology -- Periodicals; 507.21
• DOI: 10.1002/adts.202200750
• Languages: English
• ISSNs: 2513-0390

Abstract

Abstract: The deposition of aerosol particles can significantly affect the surface transmittance of photovoltaic (PV) modules and thus reduce photoelectric efficiency. With the aid of the control variable method, orthogonal experimental design, and stepwise linear regression method, a numerical simulation study of the deposition process of aerosol particles on the surface of a PV module is carried out in this paper. The influence laws of inflow wind velocity ( v ), particle diameter ( d ), installation angle ( α ), and particle concentration ( c ) on the deposition process of aerosol particles are analyzed, respectively. The deposition mechanism of aerosol particles on the surface of the PV module is disclosed, and the prediction model of deposition rate ( n ) is proposed. The results show that v, d, and c all positively affect n of the aerosol particles within the value ranges of each investigation variable in this study. α positively affects n of the aerosol particles when v is less than 3.65 m s −1 . α negatively affects the n of the aerosol particles when v is larger than 3.65 m s −1 . The prediction model could accurately predict the n of aerosol particles. This research has a theoretical guiding significance for the formulation process of cleaning strategies for the surface of PV modules. Abstract : The prediction model of n could be obtained with the aid of the control variable method, orthogonal experimental design, and stepwise linear regression method. The prediction model of n and the output data of the meteorological monitoring equipment are written into the control program, which could accurately control the operational process of the photovoltaic (PV) modules' automatic cleaning device.