Assessment methodology for photovoltaic power generation based on multiple random factors of dust deposition

Shan Hu, Yan Liu, Weidong Liu, Hailang Wen and Junjie Lan

Renewable Energy, 2025, vol. 250, issue C

Abstract: Photovoltaic (PV) modules have dust deposition due to the service in outdoor environment. To assess PV power generation, the prediction results of dust deposition shall be taken as the basis. However, the dust deposition process is a dynamic process with randomness due to the influence of many uncertainties. The existing research is based on the dust deposition prediction of deterministic influence factors, thereby making the PV power generation assessment research based on the dust deposition prediction results lack a solid foundation. In order to assess PV power generation more accurately, this study first describes the randomness of influencing factors. Secondly, a method of randomly selecting deposition criterion based on influence factors is proposed. Thirdly, considering the dynamic updating mechanism of dust collision probability of natural rainfall cleaning effect, the PV power generation assessment model based on the stochastic process of dust deposition is established. Finally, the influence of randomness factors on dust deposition is numerically simulated. The standard deviation of the relative error in power generation was reduced by 50 % compared to other methods, which verifies the correctness and validity of the proposed method. The relevant research results promote the sustainable development of PV energy.

Keywords: Photovoltaic module; Dust deposition; Influencing factors; Stochastic process; Photovoltaic power generation; Assessment methodology (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:250:y:2025:i:c:s0960148125010298

DOI: 10.1016/j.renene.2025.123367

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