Abstract
Integrated modelling of the urban wastewater system has received increasing attention in recent years and it has been clearly demonstrated, at least at a theoretical level, that system performance can be enhanced through optimized, integrated control. However, most research to date has focused on simple, single objective control. This paper proposes consideration of multiple objectives to more readily tackle complex real world situations. The water quality indicators of the receiving water are considered as control objectives directly, rather than by reference to surrogate criteria in the sewer system or treatment plant. A powerful multi-objective optimization genetic algorithm, NSGA II, is used to derive the Pareto optimal solutions, which can illustrate the whole trade-off relationships between objectives. A case study is used to demonstrate the benefits of multiple objective control and a significant improvement in each of the objectives can be observed in comparison with a conventional base case scenario. The simulation results also show the effectiveness of NSGA II for the integrated urban wastewater system despite its complexity.
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