Li Jiuling, Sharma Keshab, Li Wei, Yuan Zhiguo
Australian Centre for Water and Environmental Biotechnology (formerly AWMC), The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia.
School of Information Technologies, The University of Sydney, Sydney, NSW 2006, Australia.
Water Res. 2022 Apr 15;213:118141. doi: 10.1016/j.watres.2022.118141. Epub 2022 Feb 1.
Real-time control (RTC) is an important tool for safe and cost-effective operations of sewer systems by, for example, reducing sewer overflow or enhancing sulfide mitigation. Due to the long transport time of sewage and the inherent dynamics in sewage flow rates, model-predictive control is often needed, which requires the prediction of sewage hydraulic characteristics across the network. The full hydraulic models are often unsuitable for such purposes due to their high computational demands, which are not affordable as the models need to be called for numerous times in each optimisation step. In this study, two swift, data-driven hydraulic models are developed to predict sewage flow rates in gravity sewers receiving feeds from rising main(s) and gravity main(s), respectively. The models are shown to be able to predict both the sewage flow rate and the cross-sectional flow area in high fidelities with solutions of Saint-Venant Equations, but reduce the computational time by up to four orders of magnitude. The swift hydraulic models were then integrated into an RTC strategy for NaOH dosing in a simulated real-life sewer network, and achieved cost-effective control of sulfide. These models could potentially be used for other sewer RTC applications.
实时控制（RTC）是下水道系统安全且经济高效运行的重要工具，例如，可减少下水道溢流或加强硫化物减排。由于污水输送时间长以及污水流量存在固有动态变化，通常需要模型预测控制，这就要求预测整个管网的污水水力特性。完整的水力模型往往因其高计算需求而不适用于此类目的，因为在每个优化步骤中都需要多次调用模型，成本过高。在本研究中，开发了两种快速的数据驱动水力模型，分别用于预测接收来自提升干管和重力干管进水的重力下水道中的污水流量。结果表明，这些模型能够以圣维南方程的解高精度预测污水流量和横截面积，但计算时间最多可减少四个数量级。然后，将快速水力模型集成到模拟实际下水道网络中用于氢氧化钠投加的实时控制策略中，并实现了对硫化物的经济有效控制。这些模型可能会用于其他下水道实时控制应用。
