Abstract:

As the biochemical process of wastewater is usually a dynamic process due to large perturbations in the influent flow rate and the pollutant load,it is difficult to determine the dynamic optimal set values of the control variables in the biochemical process of wastewater.In this paper,by combining the shuffled frog leaping algorithm (SFLA) of global optimization and the particle swarm optimization (PSO) algorithm of fast convergence,a hybrid optimal algorithm,namely,SFLA- PSO,is proposed.Then,the efficiency and accuracy of the proposed algorithm are verified by means of the simulation experiments of four typical functions.Finally,the SFLA- PSO algorithm is applied to the biochemical process of wastewater with pre- denitrification.Simulation results under the conditions of dry,rainy and stormy weathers demonstrate that the proposed algorithm can ensure the effective pollutant removal of the biochemical process of wastewater with pre- denitrification,and that it reduces the operation cost.

Key words: wastewater treatment, shuffled frog leaping algorithm, particle swarm optimization algorithm, bench-mark simulation model