Optimal setting strategy of electrocoagulation process in heavy metal wastewater treatment plant

With the increasingly stringent environmental protection policies of various countries, the contradiction between the treatment cost and the purification degree of environmental pollutants has become increasingly significant, which has become a major factor restricting the efficient operation of wastewater treatment plants. Hence, keeping the ion concentration at the outlet as low as possible while reducing the cost are the main objectives of treating heavy metal wastewater by electrocoagulation (EC) process. However, due to the complicated mechanism and uncertain production conditions, it is difficult to achieve those goals by manually setting the current through operators' experience. In this paper, we develop a dynamic multi-objective optimization strategy for EC process to balance these two conflicting production targets. First, we define the removal efficiency (RE) to measure the effectiveness of the EC process. Due to the anodic passivation and cathodic polarization in the EC process, the current reversing period (CRP) is proposed and optimized to ensure the stable performance of the electrodes. Then the current setting problem is formulated as a constrained multi-objective optimization problem with competing objectives of RE and cost. An interval-adjustable control parameterization (CP) approach is developed to reduce the complexity of this optimization problem. To compute this optimization problem, a heuristic method named multi-objective state transition algorithm (MOSTA) with evaluation value is investigated. The effectiveness of our model and optimization strategy is demonstrated by a successful implementation in an EC process of a wastewater treatment plant in Chenzhou, China.

Automated summary

This paper develops a dynamic multi-objective optimization strategy to balance the treatment efficiency and cost of heavy metal wastewater treatment process. By defining the removal efficiency and optimizing the current reversing period, the difficulty of manually setting the current is addressed. An interval-adjustable control parameterization approach is proposed to simplify the optimization problem, and a heuristic method named multi-objective state transition algorithm is used for computation. The effectiveness of the model and optimization strategy is demonstrated through a successful implementation in a wastewater treatment plant in Chenzhou, China.