污水处理过程的多目标优化

Multi-Objective Optimization of Wastewater Treatment Plant

为了在保证污水处理厂出水质量达标、控制日常运营成本的同时尽量减少温室气体(GHG)的排放,将温室气体的排放纳入了污水处理的性能评价范畴,并与出水质量(EQI)、操作成本指数(OCI)等传统性能评价指标构成了污水处理过程的多目标优化问题。为研究此性能指标的多目标优化问题,构建了简化的污水处理仿真平台BSM2-e,此平台包括初沉池、活性污泥反应器、二次澄清池和浓缩单元。针对多目标优化问题的求解,采用多目标进化算法NSGA-II对该算法的精英选择策略做了改进,算法在拥挤距离选择的基础上增加了筛选步骤,以改善算法的分布性,将该算法应用于BSM2-e多目标优化问题,取得了较好的仿真结果。优化结果表明,GHG排放指标与EQI有冲突,提高出水质量可增加温室气体的排放,而GHG排放指标与OCI无冲突,在不增加操作成本的情况下可有效降低温室气体的排放。

In order to reduce the emission of process （WWTP） while guaranteeing the green house gases （GHG） in a wastewater treatment effluent quality index （EQI） and maintaining the operating cost index （OCI）, this study takes GHGs as an evaluation indictor for WWTP. Combined with other two traditional evaluation indexes, OCI and EQI, a multi-objective optimization problem is formulated. To study the three-objective optimization problem, a simplified wastewater treatment simulation platform BSM2-e was built. BSM2-e includes a primary clarifier, five activated sludge reactors, a secondary clarifier and a dewatering unit. To solve the multi-objective optimization problem, an improved non-dominated sorting genetic algorithm was proposed, making the screen of populations based on crowding distance more accurate. The improved algorithm was used to solve the multi-objective optimization problem of WWTP, and satisfied simulation results were obtained. Optimization results showed that GHGs and EQI are conflicting objectives, while GHGs and OCI are not. This means that GHGs cannot be reduced without loss in effluent quality, but it may be reduced without increase in OCI.