Sensitivity study for modelling atmospheric attenuation of solar radiation with radiative transfer models and the impact in solar tower plant production

The solar radiation reflected by the heliostats towards the receiver in solar tower plants may be attenuated by scattering and absorption processes along the optical path. This phenomenon has been traditionally computed by the solar tower plant codes using simple models based on polynomial functions of the slant range and taking very extreme conditions for the turbidity based on the standard visual range. Radiative transfer codes (libRadtran) allow modelling the atmospheric attenuation as a function of the slant range considering different aerosol conditions taken from several AERONET stations in regions of interest for CSP. The methodology presented in this work for modelling atmospheric attenuation with libRadtran can be used with any other radiative transfer model. The results showing the sensitivity of the attenuation loss to the aerosol optical depth, assuming homogeneous vertical distribution, have been fit to a simple model that can be used in Solar Advisor Model (SAM). The attenuation loss in the model proposed reaches around 20% at 1 km of slant range for highly aerosol load typical of some desert sites. Sensitivity estimations with SAM have been performed also for two reference solar tower plants (Ivanpah 1 and Gemasolar) to study the impact of atmospheric attenuation in the output power of the plant. The different attenuation loss between low and very high turbidity conditions can result in a reduction of the power output of a large plant like Ivanpah 1 of around 12% of average daily production, 20% in the field optical efficiency and 11% in the power absorbed by the receiver. In smaller plants with large thermal storage system (Gemasolar) the impact of the attenuation loss is significantly smaller (around 4%). Modelling the atmospheric attenuation in the solar tower codes should include aerosol optical depth as input in a daily basis for allowing the inclusion of the expected aerosol variability of desert and arid sites. (c) 2016 Elsevier Ltd. All rights