Modelling approaches for predictive control of large-scale sewage systems

In this report, model predictive control (MPC) of large-scale sewage systems is addressed considering different modelling approaches that include several inherent continuous/discrete phenomena (overflows in sewers and tanks) and elements (weirs) in the system that result in distinct behaviour depending on the dynamic state ( flow/volume) of the network. These behaviours can not be neglected nor can be modelled by a pure linear representation. In order the MPC controller takes into account these phenomena and elements, a modelling approach based on piece-wise linear functions is proposed and compared against a hybrid modelling approach previously reported by the authors. Control performance results and associated computation times of the closed-loop scheme considering both modelling approaches are compared by using a real case study based on the Barcelona sewer network.Preprin

A Mean Field Game Approach to Urban Drainage Systems Control: A Barcelona Case Study

Urban drainage systems (UDSs) are complex large-scale systems that carry stormwater and wastewater throughout urban areas. During heavy rain scenarios, UDSs are not able to handle the amount of extra water that enters the network and flooding occurs. Usually, this might happen because the network is not being used efficiently, i.e., some structures remain underused while many others are overused. This thesis proposes a control methology based on mean field game theory and model predictive control that aims to efficiently use the existing network elements in order to minimize overflows and properly manage the water resource. The proposed controller is tested on a UDS located in the city of Barcelona, Spain, and is compared with a centralized MPC achieving similar results in terms of flooding minimization and wastewater treatement plant usage, but only using local information on non-centralized controllers and using less computation times

On the modeling and real-time control of urban drainage systems: A survey

Trabajo presentado a la 11th International Conference on Hydroinformatics celebrada en New York (US) del 17 al 21 de agosto de 2014.Drainage networks are complex systems composed by several processes including recollection, transport, storing, treatment, and releasing the water to a receiving environment. The way Urban Drainage Systems (UDS) manage wastewater is through the convenient handling of active elements such as gates (redirection and/or retention), storing tanks, and pumping stations, when needed. Therefore, modeling and control of UDS basically consists in knowing and representing the (dynamical) behavior of these elements and managing them properly in order to achieve a given set of control objectives, such as minimization of flooding in streets or maximization of treated wastewater in the system. Given the large number of elements composing an UDS and the interaction between them, management and control strategies may depend on highly complex system models, which implies the explicit difficulty for designing real-time control (RTC) strategies. This paper makes a review of the models used to describe, simulate, and control UDS, proposes a revision of the techniques and strategies commonly used for the control UDS, and finally compares several control strategies based on a case study.This work has been partially supported by project N°548-2012 “Drenaje Urbano y Cambio Climático: Hacia los Sistemas de Alcantarillado del Futuro.”, Mexichem Colombia S.A, the scholarships of Colciencias N°567-2012 and 647-2013, and the EU Project EFFINET (FP7-ICT-2011-8-31855) and the DGR of Generalitat de Catalunya (SAC group Ref. 2009/SGR/1491).Peer Reviewe

On The Modeling And Real-Time Control Of Urban Drainage Systems: A Survey

Drainage network are complex systems composed by several processes including recollection, transport, storing, wastewater and/or rain treatment, and return of the water to a receiving environment. Urban drainage systems (UDS) involve most of these processes inside cities and can be either separate or combined systems, depending on how wastewater and rainwater are managed. The way UDS manage the wastewater is through the convenient handling of active elements such as gates (redirection and/or retention), storing tanks and pumping stations, when needed. Therefore, the modeling and control of UDS basically consists in knowing and representing the (dynamical) behavior of those elements and manage them properly in order to achieve a given set of control objectives, such as minimization of flooding in streets or maximization of treated wastewater in the system. Given the large number of elements composing a UDS and the interaction between them, management and control strategies may depend on highly complex system models, what implies the explicit difficulty for designing real-time control strategies. This paper makes a review on the huge world of models used to describe, simulate, and control UDS. Moreover, a revision of the techniques and strategies commonly used for the control of these systems is also presented and discussed. Mechanisms that ensure the correct operation of the UDS under presence of failures or communication flaws in the system are considered as well

On the modeling and real-time control of urban drainage systems: A survey

Drainage networks are complex systems composed by several processes including recollection, transport, storing, treatment, and releasing the water to a receiving environment. The way Urban Drainage Systems (UDS) manage wastewater is through the convenient handling of active elements such as gates (redirection and/or retention), storing tanks, and pumping stations, when needed. Therefore, modeling and control of UDS basically consists in knowing and representing the (dynamical) behavior of these elements and managing them properly in order to achieve a given set of control objectives, such as minimization of flooding in streets or maximization of treated wastewater in the system. Given the large number of elements composing an UDS and the interaction between them, management and control strategies may depend on highly complex system models, which implies the explicit difficulty for designing real-time control (RTC) strategies. This paper makes a review of the models used to describe, simulate, and control UDS, proposes a revision of the techniques and strategies commonly used for the control UDS, and finally compares several control strategies based on a case study.Peer ReviewedPostprint (author’s final draft

Flooding management using hybrid model predictive control at the Ebro river in Spain

Flooding prevention and control in rivers is a important topic in the river management. This is also the case in the basin of the river Ebro in Spain. In the past, the Ebro basin experienced several floods. In order to reduce the flood hazard in a given area, the local water administration usually sets up several flood-controlled areas for being able to store the excessive water volume during periods of extreme rainfall. In order to control the flows to and from the flooding zones, hydraulic control structures have been put in place. Through these actions, it is planned to have a significant reduction of the flood risk in the basin. Recent simulations of these past events in a hydrodynamic river model showed that flooding could have been significantly reduced and even avoided if the hydraulic structures would have been controlled in a different way. Therefore, the main interest of this paper is to test a different control strategy than the one currently adopted. Due to the specific nature of the flooding problem, a model predictive control (MPC) strategy (Maciejowski, 2001) seems to be the most suitable option. In this paper, the problem of flooding control at the Ebro River in Spain is addressed using MPC. Finally, several scenarios are used to validate the performance of the proposed approach. In Section 2, the problem addressed in this paper is described. In Section 3, a control oriented model is proposed. In Section 4, the control approach based on an MPC is described. Results of the application of the proposed control approach using a Virtual reality simulator are presented in Section 5. Finally, in Section 6, the main conclusions are presented.Peer ReviewedPostprint (author’s final draft