Tilt and light-scattering dependent physics-based model for the temporal evolution of soiling loss of solar panels
M. Ryyan Khan,
Mohammad Didarul Islam and
Redwan N. Sajjad
Renewable Energy, 2025, vol. 246, issue C
Abstract:
Numerical models for solar farms are used to model various loss mechanisms and find designs that are techno-economically viable. Soiling is a prominent concern among these losses. The current soiling models utilize daily soiling loss rates, neglecting factors such as panel tilt and solar angle of incidence (AOI). This results in inaccurate temporal performance prediction. In this paper, we present a time-series model for dust accumulation and the corresponding scattering of sunlight and soiling loss. The effects of ambient dust, dust-surface interaction, and panel tilt are phenomenologically modeled. We then present a physics-based model that incorporates the scattering of direct, diffuse, and albedo lights from the accumulated dust. The model also demonstrates the change of soiling loss on the degree of cloudiness. On cloudy days, for example, the AOI dependency is less prominent as the sunlight is less directional, and the soiling loss is higher. The temporal predictive model has been validated using experimental data collected for various panel tilts and seasons. The modeled daily soiling ratio matches well with the data, achieving RMSE<1.35% and r2>0.965. Such a model with diurnal predictions is important for accurate solar-farm modeling and decoupling degradation analysis from soiling losses.
Keywords: Solar farm; Soiling; Soiling ratio; Soiling physics (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148125004720
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:246:y:2025:i:c:s0960148125004720
DOI: 10.1016/j.renene.2025.122810
Access Statistics for this article
Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides
More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().