A Study Of ASM-based Integrated Membrane Bioreactor Process Simulation And Multi-objective Optimization

Membrane Bioreactor(MBR)is an efficient wastewater treatment and regeneration technology.The high energy consumption of membrane bioreactors in practical engineering is a key issue affecting its wide application.This paper relies on the decentralized sewage treatment project using MBR technology in the suburbs of a city in northern China to establish a simulation model for the AAO-MBR wastewater treatment process,and derives the function relationship between the decision variables and the main effluent water quality parameters,and establishes the water quality standards and total construction.The multi-objective optimization model with the lowest cost and lowest total operating cost proposes an optimized operation strategy,reduces sludge return flow,adjusts the aeration strategy,and achieves the overall optimization of the decentralized wastewater treatment MBR project.In this study,continuous sampling and monitoring were carried out in the engineering field to obtain the change data of water quality and water quantity in and out of water.By investigating the construction and operation data of the integrated MBR processing equipment,a process simulation model of the bioreactor of the MBR engineering wastewater was established on the Biowin and the sensitivity kinetics parameters and chemometrics that have significant influence on the simulation results were identified using the sensitivity analysis method.Including: the maximum growth rate of common heterotrophic bacteria,aerobic decay rate,anoxic decay rate,the maximum growth rate of ammonia oxidizing bacteria,aerobic decay rate,anoxic decay rate.Using the measured influent data in May as the model input,manually corrected for the reaction kinetics parameters and stoichiometric coefficients of the model by means of dynamic simulation.Through trial calculation,the effluent COD,ammonia nitrogen,TN concentration and TP concentration were in good agreement with the measured values.The average deviations were 4.15 mg/L,0.72 mg/L,4.05 mg/L,and 0.34 mg/L.Using the monthly measured influent data of June as the model input,and the dynamic model was used to evaluate the agreement between the model after calibration and the actual MBR project.The results showed that the model showed a good simulation effect for the removal process of COD,ammonia nitrogen,TN and TP.The average deviations of the simulated and measured values were 3.92 mg/L,0.87 mg/L,1.84 mg/L,and 0.25 mg/L.Based on the actual MBR engineering simulation model in a city in north China,the decision variables that have significant effects on the effluent quality,construction costs,and operating costs of the project were determined.Experiments were conducted using the face center combination design of response surface methodology.The relationship between the decision variables and the effluent water quality parameters COD,ammonia nitrogen,and total phosphorus.The experimental results indicating that the model is extremely significant and the established regression equation fits well.After establishing a functional relationship between decision variables,total operating costs,and total construction costs,the electromagnetic-like mechanism algorithm was used to determine that the wastewater treatment project would have the best overall water quality and the lowest total operating cost when meeting the effluent quality standards.The optimal solution set with the lowest construction cost,for the three optimization objectives of this study,the decision makers can optimize the target while taking into account the impact on other target values,and analyze the trade-off relationship between the various targets,according to the project.The actual conditions and their own preferences to choose the final process parameters.By analyzing the distribution of the decision variables,we know that under the condition of single influent water quality,the optimal design and operating parameters of the project are narrow,and each decision variable can be selected during actual operation.Typical values are used to optimize the project.