Run-time optimisation of sewer remote control systems using genetic algorithms and multi-criteria decision analysis: CSO and energy consumption reduction

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.