Real-time control; Sewage systems; Water quality; Multidisciplinary
Abstract :
[en] Conventional solutions for wastewater collection focus on reducing overflow events in the sewage network, which can be achieved by adapting sewer infrastructure or, a more cost-effective alternative, by implementing a non-engineering management solution. The state-of-the-art solution is centered on Real-Time Control (RTC), which is already resulting in a positive impact on the environment by decreasing the volume of wastewater being discharged into receiving waters. Researchers have been continuing efforts towards upgrading RTC solutions for sewage systems and a new approach, although rudimentary, was introduced in 1997, known as Pollution-based RTC (P-RTC), which added water quality (concentration or load) information explicitly within the RTC algorithm. Formally, P-RTC is encompassed of several control methodologies using a measurement or estimation of the concentration (i.e. COD or ammonia) of the sewage throughout the network. The use of P-RTC can result in a better control performance with a reduction in concentration of overflowing wastewater observed associated with an increase of concentration of sewage arriving at the Wastewater Treatment Plant (WWTP). The literature revealed that P-RTC can be differentiated by: (1) implementation method; (2) how water quality is incorporated, and (3) overall control objectives. Additionally, this paper evaluates the hydrological models used for P-RTC. The objective of this paper is to compile relevant research in pollution-based modelling and real-time control of sewage systems, explaining the general concepts within each P-RTC category and their differences.
Disciplines :
Electrical & electronics engineering
Author, co-author :
DA SILVA GESSER, Rodrigo ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Automation
VOOS, Holger ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Automation
Multi-Layer Model Predictive Control for Urban Water Management
Funders :
FNR - Fonds National de la Recherche
Funding number :
17139914
Funding text :
The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Rodrigo da Silva Gesser reports financial support was provided by Fonds National de la Recherche - FNR, grant reference 17139914. Rodrigo da Silva Gesser reports financial support and writing assistance were provided by University of Luxembourg, grant reference 17139914. Georges Schutz reports a relationship with RTC4Water that includes: funding grants and non-financial support.This research was funded in whole, or in part, by the Luxembourg National Research Fund (FNR), grant reference 17139914. For the purpose of open access, and in fulfilment of the obligations arising from the grant agreement, the author has applied a Creative Commons Attribution 4.0 International (CC BY 4.0) license to any Author Accepted Manuscript version arising from this submission. The authors would like to thank RTC4Water, the Interdisciplinary Centre for Security, Reliability and Trust (SnT) and the Faculty of Science, Technology and Medicine (FSTM) and Dept. of Engineering from University of Luxembourg for supporting and funding the research.This research was funded in whole, or in part, by the Luxembourg National Research Fund (FNR), grant reference 17139914. For the purpose of open access, and in fulfilment of the obligations arising from the grant agreement, the author has applied a Creative Commons Attribution 4.0 International (CC BY 4.0) license to any Author Accepted Manuscript version arising from this submission. The authors would like to thank RTC4Water, the Interdisciplinary Centre for Security, Reliability and Trust (SnT) and the Faculty of Science, Technology and Medicine (FSTM) and Dept. of Engineering from University of Luxembourg for supporting and funding the research.
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