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污水处理工艺数据分析技术的现状与趋势

高嵩,  邱勇,  孟凡琳,  张夏颖,  盘德立,  王凯军

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文章导航 > 环境工程  > 2022 >  40(6): 194-203
刘文龙, 丁毅, 周睿, 沈恒根. 钢包烟气捕集用吹吸式排风罩结构参数的数值模拟试验分析[J]. 环境工程, 2014, 32(2): 81-86. doi: 10.13205/j.hjgc.201402019
引用本文: 高嵩, 邱勇, 孟凡琳, 张夏颖, 盘德立, 王凯军. 污水处理工艺数据分析技术的现状与趋势[J]. 环境工程, 2022, 40(6): 194-203. doi: 10.13205/j.hjgc.202206025
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GAO Song, QIU Yong, MENG Fanlin, ZHANG Xiaying, PAN Deli, WANG Kaijun. STATE-OF-ART AND TRENDS OF DATA ANALYTICAL TECHNIQUES FOR WASTEWATER TREATMENT PROCESSES[J]. ENVIRONMENTAL ENGINEERING , 2022, 40(6): 194-203. doi: 10.13205/j.hjgc.202206025
Citation: GAO Song, QIU Yong, MENG Fanlin, ZHANG Xiaying, PAN Deli, WANG Kaijun. STATE-OF-ART AND TRENDS OF DATA ANALYTICAL TECHNIQUES FOR WASTEWATER TREATMENT PROCESSES[J]. ENVIRONMENTAL ENGINEERING , 2022, 40(6): 194-203. doi: 10.13205/j.hjgc.202206025
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污水处理工艺数据分析技术的现状与趋势

doi: 10.13205/j.hjgc.202206025

  • 1. 江苏省(宜兴)环保产业技术研究院, 江苏 宜兴 214200;

  • 2. 清华大学 环境学院, 北京 100084

基金项目: 

国家重点研发计划项目"面向未来的创新型水技术研发、示范、转化平台建设及实践研究"(2017YFE0119400)

详细信息
    作者简介:

    高嵩(1980-),男,博士在读。主要研究方向为环保科技创新生态、环保创新创业体系、环保装备标准化体系构建、污水厂低碳智慧运营管理。gaosong@jiei.org.cn

    通讯作者:

    邱勇(1977-),男,博士,副研究员。主要研究方向为水处理工艺模拟、环境微流控、智慧水务。qiuyong@tsinghua.edu.cn

STATE-OF-ART AND TRENDS OF DATA ANALYTICAL TECHNIQUES FOR WASTEWATER TREATMENT PROCESSES

  • 1. Jiangsu (Yixing) Institute of Environmental Industry, Yixing 214200, China;

  • 2. School of Environment, Tsinghua Unversity, Beijing 100084, China

摘要

    摘要
  • 摘要: 数据科学的飞速发展为污水处理厂工艺数据分析提供了有力的技术工具。在污水处理工艺运行中应用数据分析技术,需要克服数据、算法和算力上的困难。介绍了污水处理工艺数据分析技术的发展现状,总结了其在数据质量和数学模型方面的技术难点,分析了污水处理工艺数据分析技术的4种典型应用场景,介绍了12个国内外数据分析集成应用的案例,评估了工艺数据分析技术的成熟度和行业应用的就绪度,讨论了技术的发展趋势。研究结果有助于污水处理系统运管人员掌握工艺数据分析技术进展和运用数据分析技术处理业务的需求。
    Abstract: The rapidly developing technologies in data science have provided powerful tools for the data analytical process in wastewater treatment plants (WWTPs).Successfully applying data analytics in WWTPs needs the systematical approach to overcome the gaps in data,algorithm,and computing power.In this paper,firstly we summarized the advances in data analytics for WWTPs,and discussed the challenges that remained in the data quality control and mathematical models.Secondly,we summarized four typical four scenarios of data analytics in WWTPs and introduced twelve cases of integral application of data analytics in the wastewater treatment systems.Thirdly,the technical maturity of data analytics in WWTPs was estimated using the classic tools of hyper curves and technical readiness levels.Finally,the demands of water sectors on data analytics were analyzed to clarify the trends of the technical evolution of data analytics for WWTPs.This review was expected to help the operators and managers in WWTPs understand the advances in data analytics and utilize the developed tools to solve the process problems.
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    • 参考文献(63)
  • [1] 中国产业信息网. 2019年中国污水处理厂数量、产能及各省污水处理厂发展现状.http://hbshebei.bjx.com.cn/news/522228.html.
    [2] LU J Y, WANG X M, LIU H Q, et al. Optimizing operation of municipal wastewater treatment plants in China:the remaining barriers and future implications[J]. Environment International, 2019, 129:273-278.
    [3] QIU Y, LI J, HUANG X, et al. A feasible data-driven mining system to optimize wastewater treatment process design and operation[J]. Water, 2018, 10(134210):1342.
    [4] COROMINAS L, GARRIDO-BASERBA M, VILLEZ K, et al. Transforming data into knowledge for improved wastewater treatment operation:a critical review of techniques[J]. Environmental Modelling&Software, 2018, 106(SI):89-103.
    [5] 中国城镇供水排水协会.城镇水务行业智慧水务调研分析报告(2020年)[M].北京:中国环境出版集团, 2021.
    [6] 施汉昌,邱勇.污水生物处理的数学模型与应用[M].北京:中国建筑工业出版社, 2014.
    [7] 肖剑波,卢培利,张文阁,等.城市污水处理厂进水规律表征与模型校核[J].环境工程学报,2016, 10(8):4244-4250.
    [8] LI D, YANG H Z, LIANG X F. Prediction analysis of a wastewater treatment system using a Bayesian network[J]. Environmental Modelling&Software, 2013, 40:140-150.
    [9] 静贺,邱勇,沈童刚,等.城市污水处理厂进水动态特性及其影响研究[J].给水排水,2010, 46(8):35-38.
    [10] 董建华,王国胤,姚文.基于PCA的水质数据相似度分析模型[J].环境工程,2016, 34(增刊1):841-844.
    [11] WONGBURI P, PARK J K. Big data analytics from a wastewater treatment plant[J]. Sustainability (Basel, Switzerland), 2021, 13(22):12383.
    [12] ESCALAS-CAÑELLAS A,ÁBREGO-GÓNGORA C J, BARAJAS-LÓPEZ M G, et al. A time series model for influent temperature estimation:application to dynamic temperature modelling of an aerated lagoon[J]. Water Research, 2008, 42(10):2551-2562.
    [13] CAI J M, LIANG P, QIU Y, et al. A mass balance framework to evaluate the new pathways of biological nutrient removal in wastewater treatment[J]. Journal of Water Process Engineering, 2020, 37:101523.
    [14] 沈童刚,邱勇,应启锋,等.污水处理厂模拟软件BioWIN的应用[J].给水排水,2009(增刊1):459-462.
    [15] THERRIEN J, NICOLAÏ N, VANROLLEGHEM P A. A critical review of the data pipeline:how wastewater system operation flows from data to intelligence[J]. Water Science and Technology, 2020, 82(12):2613.
    [16] CASTILLO A, CHEALI P, GÓMEZ V, et al. An integrated knowledge-based and optimization tool for the sustainable selection of wastewater treatment process concepts[J]. Environmental Modelling&Software, 2016, 84:177-192.
    [17] XU R Z, CAO J S, FANG F, et al. Integrated data-driven strategy to optimize the processes configuration for full-scale wastewater treatment plant predesign[J]. Science of the Total Environment, 2021, 785:147356.
    [18] 邱勇,施汉昌,曾思育,等.污水处理厂自动控制系统的全流程策略与方法[J].中国给水排水,2011,27(2):16-19.
    [19] FAHAD A, TARI Z, ALMALAWI A, et al. PPFSCADA:privacy preserving framework for SCADA data publishing[J]. Future Generation Computer Systems, 2014, 37:496-511.
    [20] EERIKÄINEN S, HAIMI H, MIKOLA A, et al. Data analytics in control and operation of municipal wastewater treatment plants:qualitative analysis of needs and barriers[J]. Water Science&Technology, 2020,82(12):2681-2690.
    [21] NEGRI E, FUMAGALLI L, MACCHI M. A review of the roles of digital twin in CPS-based production systems[J]. Procedia manufacturing, 2017, 11:939-948.
    [22] IWA White paper-Ditigal Twins[J/OL].[2021-12-20].https://iwa-network.org/wp-content/uploads/2021/03/Digital-Twins.pdf.
    [23] DDHI Future City Flow[M/OL].[2021-12-20]. https://www.dhigroup.com/operational-services/future-city-flow.
    [24] Haskoning Case[M/OL].[2021-12-20].https://global.royalhaskoningdhv.com/digital/resources/publications/digital-twins-for-wastewater-infrastructure.
    [25] Hubgrade digital solutions[M/OL].[2021-12-20]. https://www.veoliawatertechnologies.com/en/hubgrade-digital-solutions.
    [26] GIBERT K, IZQUIERDO J, SÀNCHEZ-MARRō M, et al. Which method to use?An assessment of data mining methods in Environmental Data Science[J]. Environmental Modelling&Software, 2018, 110:3-27.
    [27] HUANG R X, MA C X, MA J, et al. Machine learning in natural and engineered water systems[J]. Water Research, 2021, 205:117666.
    [28] GIBERT K, RODRÍGUEZ-SILVA G, RODRÍGUEZ-RODA I. Knowledge discovery with clustering based on rules by states:a water treatment application[J]. Environmental Modelling&Software, 2010, 25(6):712-723.
    [29] ZHANG L, SCHOLZ M, MUSTAFA A, et al. Assessment of the nutrient removal performance in integrated constructed wetlands with the self-organizing map[J]. Water Research, 2008, 42(13):3519-3527.
    [30] 李冰,邱勇,田宇心,等.面向污水处理厂提标改造的效能测试与模型模拟实践[J].环境工程,2020, 38(7):93-99.
    [31] 李天宇,吴远远,郝晓地,等.数据清洗对污水处理厂生物建模可靠性影响研究[J].环境科学学报,2020, 40(9):3298-3310.
    [32] BERTHOUEX P M. Constructing control charts for wastewater treatment plant operation[J]. Research Journal of the Water Pollution Control Federation, 1989, 61(9):1534-1551.
    [33] 熊志容.质量控制图在化工厂污水管理中的应用[J].安全、健康和环境,2010, 10(9):20-23.
    [34] 施汉昌,邱勇.污水生物处理的数学模型与应用[M].北京:中国建筑工业出版社, 2014.
    [35] van LOOSDRECHT M C M, LOPEZ-VAZQUEZ C M, MEIJER S C F, et al. Twenty-five years of ASM1:past, present and future of wastewater treatment modelling[J]. Journal of hydroinformatics, 2015, 17(5):697-718.
    [36] 宋英琦,孙培德,王如意.活性污泥系统生物场-水力场-温度场耦合模型(FCASM3-Hydro-Temp)Ⅱ:模型校验[J].环境科学学报,2008,28(12):2442-2448.
    [37] 郝晓地,宋虹苇,胡沅胜,等.采用TUD模型动态模拟倒置A2/O工艺运行工况[J].中国给水排水,2007,23(16):85-89.
    [38] 魏忠庆,上官海东,叶均磊,等.基于GPS-X模拟的污水处理厂提标工艺优化[J].中国给水排水,2018, 34(19):81-84.
    [39] 李冰,邱勇,田宇心,等.面向污水处理厂提标改造的效能测试与模型模拟实践[J].环境工程,2020, 38(7):93-99.
    [40] NEWHART K B, HOLLOWAY R W, HERING A S, et al. Data-driven performance analyses of wastewater treatment plants:a review[J]. Water Research, 2019, 157:498-513.
    [41] VERMA A, WEI X, KUSIAK A. Predicting the total suspended solids in wastewater:a data-mining approach[J]. Engineering Applications of Artificial Intelligence, 2013, 26(4):1366-1372.
    [42] 忻培强.好氧微生物污水处理系统的专家系统建立[J].环境工程,2014, 32(增刊1):364-366.
    [43] VERMA A, WEI X, KUSIAK A. Predicting the total suspended solids in wastewater:a data-mining approach[J]. Engineering Applications of Artificial Intelligence, 2013, 26(4):1366-1372.
    [44] ZHAO Y, GUO L, LIANG J, et al. Seasonal artificial neural network model for water quality prediction via a clustering analysis method in a wastewater treatment plant of China[J]. Desalination and Water Treatment, 2016, 57(8):3452-3465.
    [45] BORZOOEI S, MIRANDA G H B, TEEGAVARAPU R, et al. Assessment of weather-based influent scenarios for a WWTP:application of a pattern recognition technique[J]. Journal of Environmental Management, 2019, 242:450-456.
    [46] GIBERT K, RODRIGUEZ-SILVA G, RODRIGUEZ-RODA Ⅰ. Knowledge discovery with clustering based on rules by states:a water treatment application[J]. Environmental Modelling&Software, 2010, 25(6):712-723.
    [47] MARSILI-LIBELLI S. Control of SBR switching by fuzzy pattern recognition[J]. Water Research, 2006, 40(5):1095-1107.
    [48] CHEN J C, CHANG N B. Mining the fuzzy control rules of aeration in a submerged biofilm wastewater treatment process[J]. Engineering Applications of Artificial Intelligence, 2007, 20(7):959-969.
    [49] ZHANG Z J, ZENG Y H, KUSIAK A. Minimizing pump energy in a wastewater processing plant[J]. Energy, 2012, 47(1):505-514.
    [50] ZHANG Z J, KUSIAK A, ZENG Y H, et al. Modeling and optimization of a wastewater pumping system with data-mining methods[J]. Applied Energy, 2016, 164:303-311.
    [51] ZHANG Z J, HE X F, KUSIAK A. Data-driven minimization of pump operating and maintenance cost[J]. Engineering Applications of Artificial Intelligence, 2015, 40:37-46.
    [52] 王浩正,冯宇,孙文超,等.城市排水系统模型综述[J].中国给水排水,2021, 37(22):1-10.
    [53] 王浩正,邱依婷,韩冠宇,等.基于马斯京根方法的概念模型在排水系统中的应用[J].中国给水排水,2021, 37(13):113-120.
    [54] 王浩正,刘智晓,刘龙志,等.流域治理视角下构建弹性城市排水系统实时控制策略[J].中国给水排水,2020, 36(14):66-75.
    [55] AM-TEAM. The digital twin of the link ping ozonation plant (Sweden)[J/OL]. https://www.am-team.com/en/cases/tekniskaverken-digitaltwin. 2021.
    [56] STENTOFT P A, VEZZARO L, MIKKELSEN P S, et al. Integrated model predictive control of water resource recovery facilities and sewer systems in a smart grid:example of full-scale implementation in Kolding[J]. Water Science and Technology, 2020, 81(8):1766-1777.
    [57] BERNARDELLI A, MARSILI-LIBELLI S, MANZINI A, et al. Real-time model predictive control of a wastewater treatment plant based on machine learning[J]. Water Science&Technology, 2020, 81(11):2391-2400.
    [58] FIWAREWATER. Demo case#3:Intelligent control for wastewater treatment (The Netherlands)[J]. https://www.fiware4water.eu/demo-cases/netherlands-intelligent-control-wastewater-case, 2020.
    [59] Intenational Water Association.When AI Meets Water (人工智能赋能数字水务)[Z/OL]. IWA微信公众号注册后下载. 2021.
    [60] ASSOCIATION I W. Digital Water Operational digital twins in the urban water sector:case studies[J/OL]. https://iwa-network.org/wp-content/uploads/2021/03/Digital-Twins.pdf. 2021.
    [61] 邱勇,毕怀斌,田宇心,等.污水处理厂进水数据特征识别与案例分析[J].环境科学学报,2022,42(4):44-52.
    [62] O'CALLAGHAN P, DAIGGER G, ADAPA L, et al. Development and application of a model to study water technology adoption[J]. Water Environment Research, 2018,90:563-574.
    [63] GIBERT K, HORSBURGH J S, ATHANASIADIS I N, et al. Environmental data science[J]. Environmental Modelling&Software, 2018, 106:4-12.
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