Model reduction in model predictive control of combined water quantity and quality in open channels

Xu, Mingfei; Overloop, P. J. van; Giesen, Nick van de

doi:10.1016/j.envsoft.2012.12.008

Cited by 35 publications

(33 citation statements)

References 39 publications

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“…On the other hand, model accuracy is another consideration. Xu [8] applied a model reduction method on the full hydraulic model in MPC that balanced model accuracy and computation time. Current development of MPC in operational water management is to speed up the optimization by providing analytic gradients of the objective function using adjoin methods [9].…”

Section: Scientific Fieldmentioning

confidence: 99%

Forecasting and Predictive Control of the Dutch Canal Network

Loenen

2015

Operations Research/Computer Science Interfaces Series

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Everywhere in the world where canal systems have been constructed, often the main purpose was transportation. But for most canal systems it was inevitable that they also started to play a role in the hydrology of the regions the canals crossed. In normal situations the canals have a drainage function, but in dry periods the systems can provide fresh water. An important goal for the operators is to maintain water levels on setpoint for navigation purposes. Their target is to minimize operating costs, while giving operation for navigation the highest priority. Thereby they have to take into account that the control structures have a limited operating range. A short-term optimization approach for the operational management of the canal system can increase efficiency of the water management, thereby decreasing operation costs. For the Twente Canal system, located in the eastern part of The Netherlands, such an short-term optimization approach was implemented in the operational system. This advisory module calculates the optimal operation of the available structures, given expected fluxes and system boundaries. The approach is based on Model Predictive Control and integrates observations from a gauge network and forecasted fluxes to calculate the best use of pumps and gates. The approach anticipates future lateral inflow and lock operation. The future lateral inflow in the canal sections is calculated by a rainfall-runoff model, which uses observed and forecast precipitation and evaporation. Future lock operation is estimated based on the expertise of the operators. Both have a large impact on the water balance and contain related uncertainties. The short-term optimization is implemented in the Operational Monitoring System for regulated water systems under authority of the National Water Authority (Rijkswaterstaat). This monitoring system advises operating staff on the operation of the related hydraulic structures.A. van Loenen ( ) • M. Xu Deltares,

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Section: Scientific Fieldmentioning

confidence: 99%

Forecasting and Predictive Control of the Dutch Canal Network

Loenen

2015

Operations Research/Computer Science Interfaces Series

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“…Considering these characteristic of CUDN control, MPC has been accepted to have advanced advantages in controlling urban drainage water systems as in Cembrano et al (2004); Xu et al (2013). MPC can generate optimal control actions by optimizing the objective function at every control step.…”

Section: Real-time Control Of Cudnmentioning

confidence: 99%

“…Besides that, MPC can predict the future behavior of the system through using an internal model over a finite prediction horizon. In CUDN, state of space of MPC can be presented as in Xu et al (2013):…”

Section: Real-time Control Of Cudnmentioning

confidence: 99%

“…References have proved that RTC is a reliable and cost-effective solution of CUDNs, which can improve the performance of CUDNs minimizing flooding and CSO volumes, thus protecting the environment as presented in Fu et al (2010); Bulter et al (2010); Butler et al (2005) ; Cembrano This research is funded by EU funding for the project LIFE EFFIDRAIN LIFE14 ENV/ES/00080 et al (2004); Xu et al (2013); Beeneken et al (2013); García et al (2015). Among real-time control methods, model predictive control (MPC), which can compute optimal control actions taking into account not only the current measurements but also predictive behaviors in a certain horizon, has been successfully tested in water supply and also in the context of advanced urban drainage networks by Cembrano et al (2004);Puig et al (2009);Butler et al (2005); Pleau et al (2005).…”

Section: Introductionmentioning

confidence: 99%

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Real-Time Control-Oriented Quality Modelling in Combined Urban Drainage Networks

et al. 2017

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Urban drainage networks (UDN) carry urban wastewater to wastewater treatment plants (WWTP) in order to regenerate it before releasing it to the environment. Combined UDN (CUDN) carry both rain and wastewater together, which can overload the UDN and produce combined sewer overflows (CSO) that pollute the environment. Management of CUDN is receiving increasing attention from both researchers and water managers, in order to meet the high quality standards required for water and environment according to EU Water Framework Directive. Due to the complex dynamics of water quality, integrated control of CUDN and WWTP considering both flows and quality of the conveyed wastewater is a difficult problem. In order to design a real-time control (RTC) taking into account hydraulic and quality variables, the use of conceptual quality models is considered as a suitable option. This paper mainly presents a simplified conceptual quality modelling approach to represent the dynamics of suspended solid in sewers of CUDN oriented to real-time control. A sewer simulator implemented in SWMM (Storm Water Management Model) integrated with a lumped conceptual model for total suspended solid (TSS) is used for calibration and validation. A real example of Perinot sewer network is used as a case study. Discussions about RTC implementation in CUDN are also provided in this paper, where Model Predictive Control (MPC) is proposed as the suitable method to control the integrated water and quality models in CUDN as future motivation.

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“…(Plank et al, 2006). Over the last decade, MPC has been attracting increasing attention in the field of operational water management, with applications focussing on efficient delivery of water in irrigation systems (Van Overloop, 2006;Malaterre and Baume, 1998;Wahlin, 2004;Negenborn et al, 2009), drainage and flood prevention (Blanco et al, 2010;Van Overloop, 2006;Van Overloop et al, 2010b), reservoir network management for multiple operational objectives (Goedbloed et al, 2011;Anand et al, 2013), hydroelectricity generation (Glanzmann et al, 2005;Şahin and Morari, 2010) and on the combined control of water quantity and quality in open channels (Xu, 2013;Xu et al, 2010). …”

Section: Model Predictive Control (Mpc)mentioning

confidence: 99%

Gradient-based hybrid model predictive control using Time Instant Optimization for Dutch regional water systems

Dekens¹

2014

2014 European Control Conference (ECC)

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Many areas in the Netherlands can be characterized as low-lying polder systems. In order to keep our feet dry, a lot of effort is put into ensuring the safety of the physical structures that protect us from flooding, such as dams and dikes. To control the water quantity and quality within the polders, hydraulic structures such as pumps and gates are in place. These can be operated to meet different requirements. Some of these structures are operated manually, but often the control has been automated. The operation of such structures is in many cases done by rule-based (if-then) operators, which base their control actions on a comparison of the current state (e.g. water levels) with the desired state. The field of operational water management aims at optimizing the control of these automated structures.Model Predictive Control (MPC) is an anticipatory control technique that originated in the process industries, and found its way into water management over the last one or two decades. This methodology uses a mathematical model of the controlled process and forecasts of future process states and external disturbances to determine the optimal sequence of control actions over a finite prediction horizon. The trade-off between different, often conflicting objectives of a controller is described mathematically in an objective function. At every time step, an optimization problem has to be solved by minimizing the objective function subject to constraints. Only the first control step is implemented, and the optimization starts again with updated measurements and predictions at the new time step.This thesis focusses on Dutch regional water systems. These systems are often low-lying polder-belt canal systems, where many pumps are needed to meet different requirements regarding water quantity and quality. The control of a complex water system, consisting of continuous dynamics (evolution of water flow and levels) and discrete elements (e.g. barriers and pumps that are operated on or off) can be optimized using a so-called hybrid Model Predictive Controller. However, particularly the optimization of the combination of discrete and continuous elements requires extensive computational effort. Even with the ongoing increase in computational power, computational time remains an issue for the optimization of large hybrid systems in real-time control applications.Time Instant Optimization MPC has been proposed in literature as an alternative to the computationally more demanding Mixed Logical Dynamical models. TIO-MPC involves the Master of Science ThesisBart Dekens ii optimization of a (a priori determined) number of time instants, which are the moments that a discrete variable changes its state. The rationale behind this approach is that in many cases, it is undesirable to have too many switching of controllers. This significantly reduces the amount of optimization variables, as the controller does not have to decide at every time step whether or not to switch the state of discrete variables. The latter would normally l...

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Model reduction in model predictive control of combined water quantity and quality in open channels

Cited by 35 publications

References 39 publications

Forecasting and Predictive Control of the Dutch Canal Network

Forecasting and Predictive Control of the Dutch Canal Network

Real-Time Control-Oriented Quality Modelling in Combined Urban Drainage Networks

Gradient-based hybrid model predictive control using Time Instant Optimization for Dutch regional water systems

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