[1]刘小梅,曾思育,顾朝光,等.基于多目标优化的厂网河一体化调度方法[J].中国给水排水,2025,41(9):123-129.
　LIUXiao-mei,ZENGSi-yu,GU Chao-guang,et al.Integrated Scheduling Method for Wastewater Treatment Plant, Sewer Network and Receiving River Based on Multi-objective Optimization[J].China Water & Wastewater,2025,41(9):123-129.

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基于多目标优化的厂网河一体化调度方法

中国给水排水[ISSN:1000-4062/CN:12-1073/TU] 卷: 第41卷期数: 2025年第9期页码: 123-129 栏目: 出版日期: 2025-05-01

Title:: Integrated Scheduling Method for Wastewater Treatment Plant, Sewer Network and Receiving River Based on Multi-objective Optimization

作者:: 刘小梅^1,2，曾思育¹，顾朝光²，赵洁²，陈文³; （1.清华大学环境学院，北京 100084；2.北控水务集团，北京 100102；3.丹华水利环境技术<上海>有限公司，上海 200235）

Author(s):: LIU　Xiao-mei^1，2， ZENG　Si-yu¹， GU Chao-guang²， ZHAO　Jie²， CHEN　Wen³; （1. School of Environment， Tsinghua University， Beijing 100084， China； 2. Beijing Enterprises Water Group Limited， Beijing 100102， China； 3. DHI A/S， Shanghai 200235， China）

关键词:: 厂网河一体化; 优化调度; 模拟分析; 多目标优化

Keywords:: wastewater treatment plant-sewer network-river integration; optimized scheduling; simulation analysis; multi-objective optimization

摘要:: 通过排水管网-污水厂-河道一体化调度能有效改善河网水环境质量，提升区域河道断面水质达标率。以杭州市余杭区塘河南片水系为例，分别构建排水管网和河网水动力水质模型，通过数值模拟，量化分析现状智能分流井、闸站调度规则下河道水质达标情况，识别关键调度要素，并通过选择合适的优化调度算法，选取排水管网的总溢流污染负荷、汛期污染强度和补水量作为优化目标，采用粒子群算法（PSO）和非支配排序遗传算法（NSGA-Ⅱ）进行调度方案优化。结果表明，优化后排水管网溢流污染负荷削减80%，红卫港水质达标率从0提升到71%，枫树港COD_Mn平均浓度为11.6 mg/L，降低了37%，显著提高了河网水质达标率，降低了排口溢流污染，从而改善了水环境。

Abstract:: Through the coordinated and integrated management of the drainage network, wastewater treatment plants, and receiving rivers, the water environmental quality of the river network can be significantly enhanced, leading to improved water quality regular rate in regional river sections. Hydrodynamic water quality models for both the drainage network and river network in the southern part of the Tanghe River system in Yuhang District were separately established. Through numerical simulation, the quantitative analysis of river water quality regular rate was conducted under the intelligent scheduling rules of diversion wells and sluice gates. Key scheduling factors were identified, and optimization objectives were established by selecting appropriate algorithms. Specifically, the total overflow pollution load, flood season pollution intensity, and supplementary water volume of the drainage network were chosen as the primary optimization targets. Particle swarm optimization (PSO) and non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ) were employed to optimize the scheduling schemes. After optimization, the overflow pollution load of the drainage network was reduced by 80%, the water quality regular rate at Hongweigang River increased from 0 to 71%, and the average COD_Mnat Fengshugang River decreased by 37% to 11.6 mg/L. These improvements significantly enhanced the overall water quality regular rate of the river network and effectively mitigated outlet overflow pollution, thereby substantially improving the water environment.

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　ZHAOMei-ling,ZHANG Qiao-zhen,ZHU Jun,et al.Design of Optimal Dispatching System of Water Supply Network Based on Online Model[J].China Water & Wastewater,2022,38(9):35.
[2]刘祥祥,朱一松,高越飞,等.改进粒子群算法耦合水力模型的供水优化调度分析[J].中国给水排水,2025,41(9):59.
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更新日期/Last Update: 2025-05-01