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Particle swarm optimisation-based model and analysis of photovoltaic module characteristics in snowy conditions

DOI:10.1049/iet-rpg.2018.5840 期刊:IET Renewable Power Generation 出版年份:2019 更新时间:2025-09-11 14:15:04
摘要: In this study, a novel methodology of photovoltaic (PV) modelling is proposed to represent the instantaneous electrical characteristics of PV modules covered with snow. The attenuation of the transmitted solar radiation penetrating a layer of snow is rigorously estimated based on the Giddings and LaChapelle theory. This theory introduced the level of radiation that reaches the surface of the PV module through the snowpack, significantly affected by the snow properties and thickness. The proposed modelling approach is based on the single-diode-five-parameter equivalent circuit model. The parameters of the model are updated through instantaneous measurements of voltage and current that are optimised by the particle swarm optimisation algorithm. The proposed approach for modelling snow-covered PV modules was successfully validated in outdoor tests using three different types of PV module technologies typically used in North America's PV farms under different cold weather conditions. In addition, the validity of the proposed model was investigated using real data obtained from the SCADA system of a 12-MW grid-connected PV farm. The proposed model can help to improve PV performance under snow conditions and can be considered a powerful tool for the design and selection of PV modules subjected to snow accretion.
作者: Mohammad Khenar,Seyedkazem Hosseini,Shamsodin Taheri,Ana-Maria Cretu,Edris Pouresmaeil,Hamed Taheri
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Investigating the effects of snow on photovoltaic (PV) module performance and proposing a novel methodology for PV modelling under snowy conditions.

The proposed PSO-based PV model accurately predicts the behaviour of snow-covered PV modules by coupling the albedo and extinction of solar radiation based on the Giddings and LaChapelle theory. The model was validated experimentally and using real data from a PV farm, showing good agreement with experimental results. It offers a significant advantage in predicting electric characteristics of PV modules under different snow conditions, contributing to improved PV system performance in cold climates.

The study focuses on uniformly snow-covered PV modules and does not address non-uniform snow coverage. The model's accuracy under varying snow conditions and its integration into maximum power point tracking (MPPT) boost converters are areas for future research.

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