Control-oriented quality modelling approach of sewer networks
Cita com:
hdl:2117/361710
Document typeArticle
Defense date2021-09-15
Rights accessOpen Access
Except where otherwise noted, content on this work
is licensed under a Creative Commons license
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Attribution-NonCommercial-NoDerivs 3.0 Spain
Abstract
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.
CitationXing, C. [et al.]. Control-oriented quality modelling approach of sewer networks. "Journal of environmental management", 15 Setembre 2021, vol. 294, p. 113031.
ISSN0301-4797
Collections
- Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial - Articles de revista [1.432]
- Doctorat en Enginyeria de Processos Químics - Articles de revista [129]
- SAC - Sistemes Avançats de Control - Articles de revista [521]
- IRI - Institut de Robòtica i Informàtica Industrial, CSIC-UPC - Articles de revista [383]
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