污水处理过程的多目标优化

罗健旭; 彭培培; 徐颖; 余昭旭

doi:10.7652/xjtuxb201703022

您当前的位置：

首页 >

文章列表页 >

污水处理过程的多目标优化

更新时间：2025-07-09

- 污水处理过程的多目标优化
- Multi-Objective Optimization of Wastewater Treatment Plant
- 西安交通大学学报 2017年51卷第3期页码：129-135
- 作者机构：
  
  华东理工大学化工过程先进控制和优化技术教育部重点实验室,上海,200237
- 作者简介：
- 基金信息：
  
  : 2016-08-29。作者简介: 罗健旭(1972—),女,副教授,硕士生导师。基金项目: 国家自然科学基金资助项目(61304071)
- DOI：10.7652/xjtuxb201703022
  中图分类号： X703;TP273
- 网络首发：2017-03-10，
  
  纸质出版：2017
- 稿件说明：
移动端阅览
罗健旭, 彭培培, 徐颖, 等. 污水处理过程的多目标优化[J]. 西安交通大学学报, 2017,51(3):129-135.

Multi-Objective Optimization of Wastewater Treatment Plant[J]. 2017, 51(3): 129-135.
罗健旭, 彭培培, 徐颖, 等. 污水处理过程的多目标优化[J]. 西安交通大学学报, 2017,51(3):129-135. DOI： 10.7652/xjtuxb201703022.

Multi-Objective Optimization of Wastewater Treatment Plant[J]. 2017, 51(3): 129-135. DOI： 10.7652/xjtuxb201703022.

摘要

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。

Abstract

In order to reduce the emission of green house gases(GHG)in a wastewater treatment process(WWTP)while guaranteeing the 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.

关键词

Keywords

references

Intergovernmental Panel on Climate Change. 2006 IPCC guidelines for national greenhouse gas inventories [EB/OL]. [2016-08-10]. http: ∥www. ipccnggip. iges.or.jp./public/2006gl/index.html.

徐恭贤, 韩雪. 非线性污水处理过程的多目标优化 [J]. 化工学报, 2013, 64(10): 3665-3672.

XU Gongxian, HAN Xue. Multi-objective optimization of nonlinear wastewater treatment process [J]. CIESC Journal, 2013, 64(10): 3665-3672.

于腾, 曹萃文, 顾幸生, 等. 基于多目标文化差分进化算法的污水处理厂活性污泥单元多目标操作优化 [J]. 计算机与应用化学, 2016, 33(1): 1-9.

YU Teng, CAO Cuiwen, GU Xingsheng, et al. Multi-objective optimizing operational parameters for an activated sludge unit of a wastewater treatment plant using multi-objective cultural differential evolution algorithm [J]. Computers and Applied Chemistry, 2016, 33(1): 1-9.

SCHAFFER J D. Multiple objective optimization with vector evaluated genetic algorithms [C]∥Proceedings of the 1st International Conference on Genetic Algorithms and Their Applications. New York, USA: ACM, 1985: 93-100.

ZITZLER E, THIELE L. Multi-objective evolutionary algorithms: a comparative case study and the strength Pareto approach [J]. IEEE Transactions on Evolutionary Computation, 1999, 3(4): 257-271.

DEB K, PRATAP A, AGARWAL S, et al. A fast and elitist multi objective genetic algorithm: NSGA-II [J]. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182-197.

LUO B, ZHENG J H, XIE J L, et al. Dynamic crowding distance? a new diversity maintenance strategy for MOEAs [C]∥Proceedings of the International Conference on Natural Computation. Piscataway, NJ, USA: IEEE, 2008: 580-585.

FU Y P, HUANG M, WANG H F, et al. An improved NSGA-II to solve multi-objective optimization problem [C]∥The 26th Chinese Control and Decision Conference. Piscataway, NJ, USA: IEEE, 2014: 1037-1040.

JEPPSSON U, ROSÉN C, ALEX J, et al. Towards a benchmark simulation model for plant-wide control strategy performance evaluation of WWTPs [J]. Water Science and Technology, 2006, 53(1): 287-295.

SWEETAPPLE C, FU G, BUTLER D. Identifying sensitive sources and key control handles for the reduction of greenhouse gas emissions from wastewater treatment [J]. Water Research, 2014, 62(10): 249-259.

OTTERPOHL R, FREUND M. Dynamic models for clarifiers of activated sludge plants with dry and wet weather flows [J]. Water Science and Technology, 1992, 26(5/6): 1391-1400.

HENZE M, GRADY JR C P L, GUJER W, et al. Activated sludge model: IAWPRC scientific and technical report No.1 [R]. London, UK: IAWPRC, 1987.

TAKÁCS I, PATRY G, NOLASCO D. A dynamic model of the clarification thickening process [J]. Water Research, 1991, 25(10): 1263-1271.

SWEETAPPLE C, FU G, BUTLER D. Identifying key sources of uncertainty in the modeling of greenhouse gas emissions from wastewater treatment [J]. Water Research, 2013, 47(13): 4652-4665.

BRIDLE T, SHAW A, COOPER S, et al. Estimation of greenhouse gas emissions from wastewater treatment plants [C]∥Proceedings IWA World Water Congress. London, UK: IWA Publishing, 2008: 7-12.

ZITZLER E, DEB K, THIELE L. Comparison of multi-objective evolutionary algorithms: empirical results [J]. Evolutionary Computation, 2000, 8(2): 173-195.

VELDHUIZEN D A V. Multiobjective evolutionary algorithms: classifications, analyses, and new innovations [J]. Evolutionary Computation, 1999, 8(2): 125 -147.

SCHOTT J R. Fault tolerant design using single and multicriteria genetic algorithm optimization [J]. Cellular Immunology, 1995, 37(1): 1-13.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

采用改进多目标粒子群算法的海岛综合能源系统优化调度

面向边缘端工业微服务部署的多目标白鲨优化算法

带锥形孔的矩阵冷却通道流动换热多目标优化

大型可展开网状天线展开过程仿真建模与竖向索预拉力优化调控

采用改进多目标粒子群算法的海岛综合能源系统优化调度