Multi-objective Optimization Control of Wastewater Treatment Process Based on Overshoot Suppression Strategy

To solve the problem of exceeding standard concentrations of ammonia nitrogen and total nitrogen in the wastewater treatment process, we propose a multi-objective optimization control method based on an exceeding standard suppression strategy. In the proposed method, we establish a prediction model for effluent ammonia nitrogen and total nitrogen concentrations by utilizing the time-series modeling capability of the long short-term memory network. We optimize the water quality and energy consumption using a dynamic population multi-neighborhood and multi-objective evolutionary algorithm based on decomposition. The optimal set values of nitrate nitrogen and dissolved oxygen concentrations are determined by combining the output of the prediction model, and the set values are tracked and controlled. When the water quality exceeds the standard, we adopt an inhibition strategy to control the external return flow and external carbon sources, adjust the concentration of dissolved oxygen, and optimize the concentration of nitrate nitrogen twice to suppress the peak value. The proposed optimization control method is verified on the Benchmark Simulation Model No.1 platform. The results show that the proposed method can effectively restrain the concentration of ammonia nitrogen and total nitrogen from exceeding the standard and that the exceeding time and energy consumption are significantly lower than the comparison control method.