Optimizing water quality in urban distribution networks: Leveraging digital twin technology for real-time demand management

被引:0
|
作者
Mobadersani, Mohammad [1 ]
Tokdemir, Onur Behzat [1 ]
Candas, Ali Bedii [2 ]
机构
[1] Istanbul Tech Univ, Fac Civil Engn, Dept Civil Engn, Istanbul, Turkiye
[2] Middle East Tech Univ, Fac Engn, Dept Civil Engn, Ankara, Turkiye
关键词
Digital Twin; Water quality; Water distribution networks; Water age; CONSUMPTION;
D O I
10.31462/jcemi.2024.02144156
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Potable water quality is crucial for society's well-being. Advanced devices and systems and a more specialized examination of quality parameters have improved the water quality in treatment plants. However, the property of the water may change for many reasons, such as pollution injection, water age, and system facility condition, and it may not have the same quality as the water released from the treatment plant. Due to the widespread nature of distribution networks, any contamination in water can quickly be distributed among consumers and cause irreparable damage. As a result, it is essential to preserve water quality until it reaches the final user. Leveraging new technologies and digitalization is the only solution to control and manage these massive and complex infrastructures. Digital twin (DT) is a trend word nowadays that is gaining more popularity. Digital Twin connects the physical infrastructure with the hydraulic model through two-way communication using numerous sensors installed inside the distribution network. Although previous studies have focused on the applicability of digital twin technology on water distribution network, they have failed to consider the potential impact of leveraging digital twin capabilities on water quality management. This article reveals the significance of integrating real-time demand data in hydraulic model to prevent water aging in the system by optimizing water level in tanks and pumps working hours based on network real demand and the role of digital twin for this approach.
引用
收藏
页码:144 / 156
页数:13
相关论文
共 50 条
  • [21] Intelligent Decision Support System for Real-Time Water Demand Management
    Borja Ponte
    David de la Fuente
    José Parreño
    Raúl Pino
    International Journal of Computational Intelligence Systems, 2016, 9 : 168 - 183
  • [22] Intelligent Decision Support System for Real-Time Water Demand Management
    Ponte, Borja
    de la Fuente, David
    Parreno, Jose
    Pino, Raul
    INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, 2016, 9 (01) : 168 - 183
  • [23] Research on a Real-Time Control System for Discrete Factories Based on Digital Twin Technology
    Jin, Shousong
    Yu, Fengyi
    Wang, Boyu
    Zhang, Min
    Wang, Yaliang
    APPLIED SCIENCES-BASEL, 2024, 14 (10):
  • [24] Two-tier demand response with flexible demand swap and transactive control for real-time congestion management in distribution networks
    Shen, Feifan
    Wu, Qiuwei
    Huang, Shaojun
    Chen, Xinyu
    Liu, Hui
    Xu, Yan
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2020, 114
  • [25] Smart City Digital Twin-Enabled Energy Management: Toward Real-Time Urban Building Energy Benchmarking
    Francisco, Abigail
    Mohammadi, Neda
    Taylor, John E.
    JOURNAL OF MANAGEMENT IN ENGINEERING, 2020, 36 (02)
  • [26] Hybrid regression model for near real-time urban water demand forecasting
    Brentan, Bruno M.
    Luvizotto, Edevar, Jr.
    Herrera, Manuel
    Izquierdo, Joaquin
    Perez-Garcia, Rafael
    JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2017, 309 : 532 - 541
  • [27] Real-Time Water Quality Modeling with Ensemble Kalman Filter for State and Parameter Estimation in Water Distribution Networks
    Rajakumar, Anjana G.
    Kumar, M. S. Mohan
    Amrutur, Bharadwaj
    Kapelan, Zoran
    JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT, 2019, 145 (11)
  • [28] Storm water management in an urban catchment: effects of source control and real-time management of sewer systems on receiving water quality
    Frehmann, T
    Nafo, I
    Niemann, A
    Geiger, WF
    WATER SCIENCE AND TECHNOLOGY, 2002, 46 (6-7) : 19 - 26
  • [29] Real-Time Demand Estimation and Confidence Limit Analysis for Water Distribution Systems
    Kang, Doosun
    Lansey, Kevin
    JOURNAL OF HYDRAULIC ENGINEERING, 2009, 135 (10) : 825 - 837
  • [30] A digital twin framework for real-time healthcare monitoring: leveraging AI and secure systems for enhanced patient outcomes
    Ahmed K. Jameil
    Hamed Al-Raweshidy
    Discover Internet of Things, 5 (1):