Control-oriented quality modelling approach of sewer networks

• Published in: Journal of environmental management 2021-09, Vol.294, p.113031-113031, Article 113031
• Main Authors: Sun, Congcong, Romero, Luis, Joseph-Duran, Bernat, Meseguer, Jordi, Palma, Ramon Guasch, Puentes, Montse Martinez, Puig, Vicenç, Cembrano, Gabriela
• Format: Article
• Language: English
• Subjects: Control-oriented quality modelling; MPC optimization; Sewer network; TSS
• ISSN: 0301-4797; 1095-8630
• DOI: 10.1016/j.jenvman.2021.113031

A control-oriented quality modeling approach is proposed for sewer networks, which can represent quality dynamics using simple equations in order to optimize pollution load from combined sewer overflows in large scale sewer network in real time. Total suspended solid has been selected as the quality indicator, regarding it is easy to be estimated through measuring turbidity and correlated with other quality indicators. The model equations are independent for different elements in sewer network, which allows a scalable usage. In order to ensure accuracy of the proposed models, a calibration procedure and a sensitivity analysis have been presented using data generated by virtual reality simulation. Afterwards, a quality-based model predictive control has been developed based on the proposed models. To validate effectiveness and efficiency of the modelling and optimization approaches, a pilot case, based on the Badalona sewer network in Spain is used. Application results under different scenarios show that the control-oriented modelling approach works properly to cope with quality dynamics in sewers. The quality-based optimization approach can provide strategies in reducing pollution loads in real time. •A simplified quality modelling approach for the sewer network is proposed.•Calibration and sensitivity analysis confirm its accuracy and scalability.•Quality-based optimization has been developed using model predictive control.•The simple model ensure pollution optimized in complex sewer network in real time.•The models and optimization approach have been validated in real life pilot.