Advanced Water Management Centre, Building 60, Research Road, The University of Queensland, St. Lucia, Brisbane QLD 4072, Australia; Center for Microbial Ecology and Technology (CMET), Ghent University, Coupure Links 653, 9000 Ghent, Belgium.
Advanced Water Management Centre, Building 60, Research Road, The University of Queensland, St. Lucia, Brisbane QLD 4072, Australia.
Water Res. 2018 May 15;135:302-310. doi: 10.1016/j.watres.2018.02.022. Epub 2018 Feb 13.
Water utilities worldwide spend annually billions of dollars to control sulfide-induced corrosion in sewers. Iron salts chemically oxidize and/or precipitate dissolved sulfide in sewage and are especially used in medium- and large-size sewers. Iron salt dosing rates are defined ad hoc, ignoring variation in sewage flows and sulfide levels. This often results in iron overdosing or poor sulfide control. Online dosing control can adjust the chemical dosing rates to current (and future) state of the sewer system, allowing high-precision, stable and cost-effective sulfide control. In this paper, we report a novel and robust online control strategy for the dosing of ferrous salt in sewers. The control considers the fluctuation of sewage flow, pH, sulfide levels and also the perturbation from rainfall. Sulfide production in the pipe is predicted using auto-regressive models (AR) based on current flow measurements, which in turn can be used to determine the dose of ferrous salt required for cost-effective sulfide control. Following comprehensive model-based assesment, the control was successfully validated and its effectiveness demonstrated in a 3-week field trial. The online control algorithm controlled sulfide below the target level (0.5 mg S/L) while reducing chemical dosing up to 30%.
全世界的水务公司每年花费数十亿美元来控制污水中的硫化物引起的腐蚀。铁盐通过化学氧化和/或沉淀污水中的溶解硫化物，尤其用于中大型污水管道。铁盐投加率是根据特定情况定义的，忽略了污水流量和硫化物水平的变化。这通常导致铁盐投加过量或硫化物控制不佳。在线投加控制可以根据污水系统的当前（和未来）状态来调整化学投加率，从而实现高精度、稳定和具有成本效益的硫化物控制。本文报道了一种新颖且强大的污水管道中添加亚铁盐的在线控制策略。该控制考虑了污水流量、pH 值、硫化物水平的波动，以及降雨的干扰。基于当前流量测量值，使用自回归模型（AR）预测管道中的硫化物生成量，进而可以确定为实现经济有效的硫化物控制所需的亚铁盐投加量。经过全面的基于模型的评估，该控制算法在为期 3 周的现场试验中得到了成功验证和有效性证明。在线控制算法将硫化物控制在目标水平（0.5mgS/L）以下，同时将化学投加量减少了 30%。
