REVIEW STUDY ON THE TECHNIQUES APPLIED IN THE MODELING OF SOILING ON PHOTOVOLTAIC MODULES
DOI:
https://doi.org/10.59627/cbens.2022.1096Keywords:
Solar Energy, Photovoltaic Module, SoilingAbstract
Soiling on photovoltaic modules is a relevant cause for losses in energy generation, in Belo Horizonte/MG it is estimated a reduction of around 11% in six months of measurement. This article presents a review of the models used in the literature to estimate the losses caused by dirt deposited on the surface of the modules. The research protocol defined the keywords to search for articles published from 2011 onwards in six databases, whose results went through three stages of selection: exclusion of articles with titles not relevant to the research, exclusion of abstract articles not relevant to the research, full reading of the articles and selection of the most relevant to the research. The studies developed were grouped according to the type of model. Statistical models use linear regression and similar methods, are practical and simple. Models based on neural networks can return very accurate results (above 90%), but they are complex and need a lot of data to train them. There are also models based on linear, exponential, derating factor, numerical simulation, optical and ratio-dependent equations, which were less explored by the articles. In general, the models use empirical data to obtain the results, which restricts them to the researched location and prevents their generalization to other regions. Sensitivity analyses indicate that physical characteristics of the dirt (composition, size and others) might be more relevant than the environmental parameters, while among these variables precipitation and wind are the most significant parameters. This shows how challenging it is to develop a mathematical model that includes all impact variables. There is a wide variety of studies and approaches, while comparing them without a standardized methodology for the analyses.
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