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This study presents a soiling forecasting (SF) tool developed by the University of Patras in order to predict the deposition of dust on Parabolic Trough Collector (PTC) mirrors. The SF estimation is occurred from the ADTM models. Dust accumulation from sedimentation, Brownian motion and impaction are considered in the estimation of deposition velocity. Moreover, the impact of rainfall is also considered. The computational procedure was divided into the laminar flow regime and the turbulence flow regime in order to estimate the rate at which dust particles can accumulate on the surface of a PTC mirror.The meteorological data used in the model's training were taken from a weather station at the company KEAN Soft Drinks Ltd. in Limassol, Cyprus (PTC location), and the particle concentrations were obtained from CAMS global atmospheric forecasts [1]. Two variants of the model were used. The first model uses PM2.5 and PM10 (kg/m3). The second model uses a wider distribution of aerosols. Specifically, dust aerosol mixing ratio in the bins 0.03-0.55 μm, 0.55-0.9 μm and 0.9-20 μm were used.The reflectivity estimations from both models were compared with the available PTC mirror reflectivity measurements to confirm the effectiveness of the SF tool [2]. The validation measurement campaign was conducted from June 3rd to June 7th, 2019. A major soiling event occurs within the first three days which increases gradually until June 5th and then recedes. For the chosen validation period, both models accurately captured the phasing and magnitude of reflectivity. Figure 1 illustrates the soiling mechanisms for the first model and the Figure 2 for the second model respectively. The wind speed during the 4-day period was below 6.8 m/s (laminar flow threshold). The larger particles included in the second model and the corresponding deposition velocity of the coarse particles resulted at higher values for Sedimentation and Brownian motion while Impaction had the same range between the two models (because the wind is the dominant factor of this mechanism). Therefore, the coarser particles resulted in increased influence of sedimentation over impaction in model 2. In both models, the impact of Brownian deposition was the least among the mechanisms. Moreover, the sedimentation had the highest influence, at most hours, in the modelled deposition velocity with occasional outbursts of impaction. The process of calibrating the models with data covering various atmospheric conditions is ongoing. Fig. 1: Input data, soiling mechanisms and reflectivity for model 1. Fig. 2: Input data, soiling mechanisms and reflectivity for model 2. AcknowledgementsSmart Solar System (S3) project is supported under the umbrella of SOLAR-ERA.NET Cofund by Projektträger Jülich – Forschungszentrum Jülich GmbH – Energie-Technologie-Nachhaltigkeit (ETN 1) and General Secretariat of Research and Innovation (GSRI). SOLAR-ERA.NET is supported by the European Commission within the EU Framework Programme for Research and Innovation HORIZON 2020 (Cofund ERA-NET Action, N° 691664). References[1] CAMS, https://atmosphere.copernicus.eu[2] P. K. Ktistis, R. A. Agathokleous, and S. A. Kalogirou, “Experimental performance of a parabolic trough collector system for an industrial process heat application,” Energy, doi: 10.1016/j.energy.2020.119288. |
