Multi-objective optimization control of wastewater treatment process based on multi-strategy adaptive differential evolution algorithm

To address the problems of high energy consumption and substandard effluent quality in the wastewater treatment process, a multi-objective optimization control method for wastewater treatment process based on multi-strategy adaptive differential evolution algorithm is proposed. Firstly, the tracking control of the dissolved oxygen concentration of the 3rd and 4th units is added under the conventional differential tracking control framework, which aims to expand the optimal adjustment range of energy consumption and effluent water quality. Then, a multi-strategy adaptive differential evolution algorithm (MSADE) is proposed, which selects proper mutation strategy and random individuals to guide the population mutation by combining the multi-strategy fusion mutation technique and sorting optimization method. Further, the convergence of proposed algorithm and the diversity of the pareto solution can be greatly improved by updating the crossover rate adaptively according to the evolution process information. Finally, the MSADE algorithm and the PID controller are combined, and a novel multi-objective optimization method is built with a good balance of energy consumption and effluent quality, realizing the dynamic optimization process and the tracking control of setting values of dissolved oxygen and nitrate nitrogen concentration. The simulation results on the international benchmark simulation platform BSM1 show that the proposed method can effectively reduce energy consumption and improve effluent quality in the wastewater treatment process. © 2021, Editorial Board of CIESC Journal. All right reserved.