A new approach for sewer regulation with remote-control systems in case of intense meteorological events is presented. A run-time multi-objective decision method was developed and applied to a case study with the aim of minimising water overflow and electric energy consumption of the upstream water collection system of a wastewater treatment plant. Strategy optimisation makes use of genetic algorithms and short-time predictions of water flows into the sewer system. The ability to efficiently optimise the system controllable parameters even for lags as short as 30 guarantees flexibility, prompt adaptation to changing conditions and reliability. With respect to a conventional approach, energy savings up to 32% can be reached using the proposed run-time optimisation at the price of increasing the total combined sewer overflow of approx. 10%. With respect to the basic system layout, installing an additional buffer tank for most intense rain events can guarantee a 7% reduction of the water outflow and a 36% reduction of the energy consumption. The sensitivity analysis, performed on different layouts, shows no evidence for preferring time horizons for water discharge predictions longer than 90 min.

提出了一种在发生强烈气象事件时采用远程控制系统进行下水道调节的新方法。开发了一种运行时间多目标决策方法，并将其应用于案例研究，目的是最大程度地减少污水处理厂上游集水系统的水溢流和电能消耗。策略优化利用遗传算法和对下水道系统中水流量的短期预测。有效地优化系统可控制参数的能力，即使对于短至30的滞后，也可以确保灵活性，迅速适应变化的条件和可靠性。相对于传统方法，使用建议的运行时优化可以节省多达32％的能源，但代价是总的下水道总溢流量增加了约50％。10％。在基本系统布局方面，为大多数强降雨事件安装一个额外的缓冲罐可以确保将水流出减少7％，并将能耗减少36％。在不同布局上进行的敏感性分析没有证据表明，对于超过90分钟的排水量预测，更倾向于选择时间范围。