Genetic algorithms in real time control applied to minimize transient pollution from urban wastewater systems

Real time control aims at optimization of the urban wastewater system performance under dynamic loading from rain. This paper presents a novel approach to control the whole system: sewer system, treatment plant and receiving water with the aim to achieve minimum effects of pollution. The application of nonlinear model predictive control by means of a genetic algorithm reveals excellent results with hypothetical problem sets. The methodology makes it possible to optimize the system performance directly with respect to water quality parameters and to avoid the traditional indirect and artificial performance criteria, such as permissible annual overflow volume. The relevance of this novel approach is illustrated by the fact that no stringent correlation has been found in the investigation between the reduction of overflow volume and the increase of oxygen concentration in the receiving water.