Model Predictive Control in Urban Systems: Optimal and Stochastic Utilization of the infrastructure of sewer systems

Jan Lorenz Svensen, Hans Henrik Niemann, A.K.V. Falk, Henrik Madsen, Niels Kjølstad Poulsen, Henrik Madsen

Research output: Other contributionNet publication - Internet publicationCommunication

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Abstract

The utility of sewer systems to both transport sewage and rainwater results in issues with capacity limits during larger rain events. When the volume capacity of the sewer is reached, then the water exits the sewers wherever it is possible; streets, parks, harbour basins, or basements. This polluting outflow of sewage water leads to damages of both environmental and proprietary nature, as well as a health hazard for the population. The issue can be prevented/reduced by introducing SuDS structures to direct the rainwater to the natural environment, or by expanding/updating the sewer infrastructure to increase its capacity and/or becoming a separate sewer system. Both of these solutions require time-expensive investments in changing the infrastructure, as well as requiring the availability of the needed space for the new infrastructure. Another approach is to achieve better performance with the existing infrastructure. For this, we must control the flows within the sewers, so an optimal control method is useful. Given the physical limits of sewers, the optimal method: Model Predictive Control (MPC) is useful, as it allows for the inclusion of constraints in its formulation of the optimal control, as well as to account for the future evolution of the system, relying on weather forecasts.
Original languageEnglish
Publication date2021
PublisherTechnical University of Denmark
Number of pages2
Publication statusPublished - 2021

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  • Model Predictive Control in Urban Systems

    Svensen, J. L. (PhD Student), Ocampo-Martinez, C. (Examiner), Mikkelsen, P. S. (Examiner), Madsen, H. (Main Supervisor), Niemann, H. H. (Supervisor), Poulsen, N. K. (Supervisor), Falk, A. K. V. (Supervisor), Madsen, H. (Supervisor) & Kallesøe, C. S. (Examiner)

    Samfinansieret - Andet

    15/09/201714/04/2021

    Project: PhD

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