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Παρασκευή 20 Απριλίου 2018

The field experiments and model of the natural dust deposition effects on photovoltaic module efficiency

Abstract

The maximisation of the efficiency of the photovoltaic system is crucial in order to increase the competitiveness of this technology. Unfortunately, several environmental factors in addition to many alterable and unalterable factors can significantly influence the performance of the PV system. Some of the environmental factors that depend on the site have to do with dust, soiling and pollutants. In this study conducted in the city centre of Kraków, Poland, characterised by high pollution and low wind speed, the focus is on the evaluation of the degradation of efficiency of polycrystalline photovoltaic modules due to natural dust deposition. The experimental results that were obtained demonstrated that deposited dust-related efficiency loss gradually increased with the mass and that it follows the exponential. The maximum dust deposition density observed for rainless exposure periods of 1 week exceeds 300 mg/m2 and the results in efficiency loss were about 2.1%. It was observed that efficiency loss is not only mass-dependent but that it also depends on the dust properties. The small positive effect of the tiny dust layer which slightly increases in surface roughness on the module performance was also observed. The results that were obtained enable the development of a reliable model for the degradation of the efficiency of the PV module caused by dust deposition. The novelty consists in the model, which is easy to apply and which is dependent on the dust mass, for low and moderate naturally deposited dust concentration (up to 1 and 5 g/m2 and representative for many geographical regions) and which is applicable to the majority of cases met in an urban and non-urban polluted area can be used to evaluate the dust deposition-related derating factor (efficiency loss), which is very much sought after by the system designers, and tools used for computer modelling and system malfunction detection.



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