Digital Twins for Wastewater Treatment: A Technical Review
Ai-Jie Wang,
Hewen Li,
Zhejun He,
Yu Tao,
Hongcheng Wang,
Min Yang,
Dragan Savic,
Glen T. Daigger,
Nanqi Ren
Affiliations
Ai-Jie Wang
School of Civil and Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China; State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China; Corresponding authors.
Hewen Li
School of Civil and Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China
Zhejun He
Department of Civil and Environmental Engineering, Cornell University, Ithaca, NY 14850, USA
Yu Tao
School of Civil and Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China; Corresponding authors.
Hongcheng Wang
School of Civil and Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China; State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China
Min Yang
School of Civil and Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China; BIOMATH, Department of Data Analysis and Mathematical Modelling, Ghent University, Ghent 9000, Belgium
Dragan Savic
KWR Water Research Institute, Nieuwegein 3430 BB, Netherlands; Centre for Water Systems, University of Exeter, Exeter EX4 4QF, UK
Glen T. Daigger
Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI 48109, USA
Nanqi Ren
School of Civil and Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China; State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China
The digital twins concept enhances modeling and simulation through the integration of real-time data and feedback. This review elucidates the foundational elements of digital twins, covering their concept, entities, domains, and key technologies. More specifically, we investigate the transformative potential of digital twins for the wastewater treatment engineering sector. Our discussion highlights the application of digital twins to wastewater treatment plants (WWTPs) and sewage networks, hardware (i.e., facilities and pipes, sensors for water quality and activated sludge, hydrodynamics, and power consumption), and software (i.e., knowledge-based and data-driven models, mechanistic models, hybrid twins, control methods, and the Internet of Things). Furthermore, two cases are provided, followed by an assessment of current challenges in and perspectives on the application of digital twins in WWTPs. This review serves as an essential primer for wastewater engineers navigating the digital paradigm shift.
