Design and Implementation of a Soiling Forecasting Tool for Parabolic Through Collector Mirrors

Abstract

This study presents a new soiling forecasting algorithm that was designed to predict the deposition of dust on mirror of Parabolic Through Collector (PTC) plants. The PTC soiling model developed in this work is based on existing models for the dust dry deposition over geographic regions. The soiling forecast algorithm is characterized by specific mechanisms. The sedimentation mechanism, also known as “gravitational settling”, is proportional to the sun’s position. Brownian motion is defined as a diffusion process and depends on the air’s wind speed and temperature. Impaction mechanism depends on the wind speed and wind direction and occurs when particles do not follow the curved streamlines of their flow due to the inertia. All three mechanisms depend also on aerosol’s size. Two mechanisms contribute to the mirror’s cleaning, namely rebound and washout. Soiling rate (SR) is the daily rate of dust accumulation on the mirror’s surface and depends on deposition velocity, rebound, the number of particles and their size. The modelled reflectivity is a function of SR and the reflectivity of a cleaned mirror. The model was calibrated using reflectivity measurements which were acquired during a previous project campaign in the period July 2018 – May 2019. The validation of the model for June 2019 showed that it accurately captured the phasing and the magnitude of reflectivity. The results of this study can help the PTC’s operator to choose the optimal cleaning strategy to minimize the energy loss and to reduce O&M cost.

Keywords

• Soiling Forecast
• Soiling Effect
• Modelling
• Particulate Matter
• Parabolic Through Collector (PTC) Plants