Research On An Optimal Control System Of AAO Process For Energy Conservation And Consumption Reduction

Anaerobic-Anoxic-Oxic (AAO) process is one of the most popular municipalwastewater treatment processes in China. For the conservation of water resource andprotection of water environment, it is very important to guarantee the effluent to meetthe standards and decrease the operation cost. According to the analysis on the variationof influent flowrate and nutrient concentrations, as well as the influence of rainfalls oninfluent loads, an autoregressive linear model was established to predict the influentloads in different time scales.The mechanisms of existing mechanistic models are not complete.Overparametrization and complex structure make the models very difficult to bedirectly used for wastewater treatment process control. By supplementing processmechanisms, screening the key mechanisms, as well as simplifying the model equations,this study established a structural-identifiable simplified model. The model kept the keyprocesses such as nitrification, denitrification, biological phosphorus removal andchemical phosphorus removal, but simplified the reaction equations to make theparamteters be identified. Based on mechanistic experiments the simplified model takethe inhibitation on nitrification process of chemical dosage into consideration. So thesimulation of the simplified model on wastewater treatment processes was morecomprehensive.Based on the existing energy and material consumption function of AAO process,combined with the punishment regulation for over-standard effluent discharge of China,this study built a native system for control strategy evaluation by adjusting theequivalent coefficients of effluent quality and adding cost coefficients of chemicaldosage. The system further defined the process control objective function of the AAOprocess. Based on the process simulation and prediction using influent prediction modeland simplified mechanistic model, as well as the off-line and on-line (Extend KalmanFilter) parameter estimation, this study constructed an optimization control system ofAAO process using genetic algorithm for control variable optimization. Under thecotrol of this optimization system, the effluent concentrations can keep stable and meetthe effluent standard, meanwhile the energy was saved and the consumption wasreduced. To verify the control effect and reliability of the sytem，the optimization controlsystem was tested both on the modified BSM platform (modified according to themechanism experiments) and an AAO pilot-scale platform. Compared to the traditionalfeedback control system, the optimization system can achieve energy conservation andmaterial reduciton under the premise of making the effluent stable and meeting thedischarge standard.