Study On Nitrogen Removal Activated Sludge Process Modeling And Control Strategy Simulation

Activated sludge method is an effective method for the wastewater treatment and has been widely applied and studied. With the legislation on the strict wastewater discharge norm,it is necessary to adopt advanced modeling and control technology for the wastewater treatment Process (WWTP) to improve water quality and reduce operating cost. Because of the complex mechanism and time-variant character of the whole process,coupling between variables,the dynamic behavior and characteristics should be regarded. For the sake of improving our country's wastewater process automation control level,it is very useful to do research on its model simulation and control strategies.Based on Benchmark, this study build activated sludge process simulation platform, then evaluate the performance of control strategies by simulation results, and optimize the control system.At first,the Benchmark of IWAQ is introduced,which includes activated sludge model No.1(ASM1) and secondary settlement tank model,then the regulations of control Performance,effluent quality indexes and controller operational range are analyzed in detail. After then the Benchmark simulation platform is introduced and built using MATLAB/Simulink,the simulation model reliability is tested,Secondly,activated sludge model NO.1 as base, singular perturbation and sensitivity analysis were proposed to reduce the system dimension. The number of component, reaction process and parameter of the reduced model are less than original ASM1. To determine which control strategy delivers better performance with respect to plant operating costs, constant manipulated variables and various PI and feed-forward control strategies are tested and predictive control are evaluated in benchmark simulation platform.The latter part outlines the hierarchical control scheme aiming at plant-wide optimization based on the economic performance index considering both the effluent quality and the operation cost. A QPSO algorithm is proposed to look for the optimal value, and it raises the solution efficiency significantly. Simulation experiments validate the effectiveness of the proposed control scheme and method.