A computational fluid dynamics approach to selecting a concentrating solar thermal site location around a ferromanganese Smelter based on heliostat soiling potential

Abstract

There is a need to reduce the share of process heat generated by fossil fuels in energy-intensive industries. One proposed solution in the iron and steel sector is to introduce high temperature solar thermal heat energy into a pre-heating stage of the ferromanganese smelting process. In principle, this is an idea that can work, but there are unknowns related to concentrating solar thermal (CST) solar field performance in the vicinity of an industrial smelting operation. This dissertation adopts a two-part approach to addressing the unknowns related to solar field performance. First, a field experimental campaign is carried out at a ferromanganese smelter in South Africa, where mirror soiling data, dust characterisation data, and on-site meteorological data are collected. A clear change in rainfall was observed during the summer and winter period, with the dry winter period being the period where the most mirror soiling was observed. Results from the 8-month mirror soiling measurement campaign showed that proximity of the mirror sampling set to the smelter dust source is the primary driver of mirror soiling rates, with dust concentrations decreasing further away from the source. The secondary drivers for mirror soiling rates were observed to be wind direction and wind speed, for reflectance sampling locations at roughly equal distances from the smelter dust source. A 13 % relative improvement in mirror reflectance loss rate was observed by simply considering an adjacent mirror sampling location through the dry season. The second part of this dissertation demonstrates the use of a large-scale atmospheric flow computational fluid dynamics (CFD) modelling based approach to selecting an appropriate CST solar field site in the vicinity of an industrial smelter. The k-ϵ turbulence model is adapted to be more suitable to modelling neutral atmospheric boundary layer (ABL) flows, along with other modelling strategies. The tailored modelling approach is validated against wind tunnel and on-site wind mast data. On-site wind mast data is also used to derive priority wind speed and direction simulation cases. The discrete phase method (DPM) is used to simulate dust dispersion and deposition based on the results of the full-scale neutral ABL CFD simulations for priority wind cases. The dust deposition results for individual cases are then combined and weighted using the on-site wind data for a given sampling period, yielding a dust deposition map that shows the deposition hot spots around the smelter for the given period. The weighted dust deposition pattern is validated against experimental mirror soiling data for the same iii period. Some minor discrepancies are observed, but the simulation approach correctly predicted the experimentally observed soiling pattern for the studied period. The CFD-based CST solar field site-selection approach is thus successfully demonstrated and validated as an approach that can be used to identify a candidate solar field site relative an industrial dust source.