Reducing the Environmental Impact of Sewer Network Overflows Using Model Predictive Control Strategy
Vasiliev, Iulian (Universitat Autònoma de Barcelona. Departament de Telecomunicació i Enginyeria de Sistemes)
Luca, Laurentiu (Dunarea de Jos University of Galati)
Barbu, Marian (Dunarea de Jos University of Galati)
Vilanova, Ramon (Universitat Autònoma de Barcelona. Departament de Telecomunicació i Enginyeria de Sistemes)
Caraman, Sergiu Viorel (Dunarea de Jos University of Galati)

Date:	2024
Abstract:	This paper proposes a method for reducing the environmental impact of sewer network (SN) overflows. The main objective of the paper is to minimize the wastewater quantity and the pollutant loads that overflow from the SN. The proposed algorithm to achieve this goal is Model Predictive Control using Particle Swarm Optimization as optimization method. It was tested in simulation using a simplified model of the network based on Benchmark Simulation Modelsewer as prediction model, and a forecasted influent. Three cases have been considered: (a) the fitness function is defined as the global yearly overflow volume calculated using equal weights for each tank; (b) the fitness function uses different weights for each tank depending on the medium loads and (c) integrating a penalty term related to the system state at the end of the prediction horizon in the previous fitness function. The simplified model determined a significant reduction of the integration time minimizing the optimization time.
Grants:	Agència de Gestió d'Ajuts Universitaris i de Recerca 2022/SGR-197 Agencia Estatal de Investigación PID2019-105434RB-C33
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Model predictive control ; Particle swarm optimization ; Sewer network environmental impact ; Sewer network optimization
Published in:	Water resources research, Vol. 60, Issue 1 (January 2024) , art. e2023WR035448, ISSN 1944-7973

DOI: 10.1029/2023WR035448

14 p, 667.1 KB

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