scholarly journals Model Predictive Control of a River Reach with Weirs

10.29007/1nnf ◽  
2018 ◽  
Author(s):  
Klaudia Horváth ◽  
Bart van Esch ◽  
Jorn Baayen ◽  
Ivo Pothof ◽  
Jan Talsma ◽  
...  
Keyword(s):  
Decision Support ◽  
Convex Optimization ◽  
Decision Support System ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Support System ◽  
Water System ◽  
Open Water ◽  
Global Optimum ◽  
Water Levels

A decision support system for water management based on convex optimization, RTC-Tools 2, is applied for a water system containing river branches connected by weirs. The advantage of convex optimization is the ability of finding the global optimum, which makes the decision support system robust and deterministic. In this work the convex modeling of open water channels and weirs is presented. The decision support system is implemented for a river made of 12 river reaches divided by movable weirs. It is shown how the discharge wave is dispatched in the river without the water levels exceeding the bounds by controlling the weir heights. After this test the optimization can be applied to a realistic numerical model and model predictive control can be implemented.

scholarly journals Time-instant optimization for hybrid model predictive control of the Rhine–Meuse delta

2013 ◽  
Vol 15 (2) ◽  
pp. 271-292 ◽  
Author(s):  
H. van Ekeren ◽  
R. R. Negenborn ◽  
P. J. van Overloop ◽  
B. De Schutter
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Sea Water ◽  
Water System ◽  
Open Water ◽  
Time Instant ◽  
Water Levels ◽  
Continuous Variables ◽  
Discrete Events ◽  
Control Structures

In order to ensure safety against high sea water levels, in many low-lying countries, water levels are maintained at certain safety levels, and dikes have been built, while large control structures have been installed that can also be adjusted dynamically after they have been constructed. Currently, these control structures are often operated purely locally, without coordination of actions being taken at different locations. Automatically coordinating these actions is difficult, as open water systems are complex, hybrid dynamical systems, in the sense that continuous dynamics (e.g. the evolution of the water levels) appear mixed with discrete events (e.g. the opening or closing of barriers). In low lands, this complexity is increased further due to bi-directional water flows resulting from backwater effects and interconnectivity of flows in different parts of river deltas. In this paper, we propose a model predictive control (MPC) approach that is aimed at automatically coordinating the actions of control structures. The hybrid dynamical nature of the water system is explicitly taken into account. In order to relieve the computational complexity involved in solving the MPC problem, we propose TIO-MPC, where TIO stands for time-instant optimization. Using this approach, the original MPC optimization problem that uses both continuous and integer variables is transformed into a problem involving only continuous variables. Simulation studies of current and future situations are used to illustrate the behavior of the proposed scheme.

Gold coast seaway smartrelease decision support system: optimising recycled water release in a sub tropical estuarine environment

2009 ◽  
Vol 60 (8) ◽  
pp. 2077-2084 ◽  
Author(s):  
G. Stuart ◽  
A. Hollingsworth ◽  
F. Thomsen ◽  
S. Szylkarski ◽  
S. Khan ◽  
...  
Keyword(s):  
Water Quality ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Numerical Models ◽  
Water Levels ◽  
Gold Coast ◽  
Recycled Water ◽  
Water Release ◽  
The Impact

Gold Coast Water is responsible for the management of the water, recycled water and wastewater assets of the City of the Gold Coast on Australia's east coast. Excess treated recycled water is released at the Gold Coast Seaway, a man-made channel connecting the Broadwater Estuary with the Pacific Ocean, on an outgoing tide in order for the recycled water to be dispersed before the tide changes and re-enters the Broadwater estuary. Rapid population growth has placed increasing demands on the city's recycled water release system and an investigation of the capacity of the Broadwater to assimilate a greater volume of recycled water over a longer release period was undertaken in 2007. As an outcome, Gold Coast Water was granted an extension of the existing release licence from 10.5 hours per day to 13.3 hours per day from the Coombabah wastewater treatment plant (WWTP). The Seaway SmartRelease Project has been designed to optimise the release of the recycled water from the Coombabah WWTP in order to minimise the impact to the receiving estuarine water quality and maximise the cost efficiency of pumping. In order achieve this; an optimisation study that involves intensive hydrodynamic and water quality monitoring, numerical modelling and a web-based decision support system is underway. An intensive monitoring campaign provided information on water levels, currents, winds, waves, nutrients and bacterial levels within the Broadwater. This data was then used to calibrate and verify numerical models using the MIKE by DHI suite of software. The Decision Support System will then collect continually measured data such as water levels, interact with the WWTP SCADA system, run the numerical models and provide the optimal time window to release the required amount of recycled water from the WWTP within the licence specifications.

scholarly journals Continuous nonlinear model predictive control of a hybrid water system

2012 ◽  
Vol 15 (2) ◽  
pp. 246-257 ◽  
Author(s):  
Eelco Nederkoorn ◽  
Jan Schuurmans ◽  
Joep Grispen ◽  
Wytze Schuurmans
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Nonlinear Model ◽  
Land Surface ◽  
Real Life ◽  
Water System ◽  
Water Levels ◽  
Nonlinear Model Predictive Control ◽  
Weather Forecasts ◽  
Highly Nonlinear

Incorporating weather forecasts in the control of land surface water levels requires predictions of the net inflow to the water system. This net inflow is the combined flow of an incoming load (rain, evaporation, etc.) and outgoing pump rates. Because the pump costs are considerable, optimal pump schedules have minimal energy consumption. Model predictive control (MPC) is able to compute, revise and apply such optimized schedules by incorporating a model of the water system. The pumps typically cause discontinuities in the model, which leads to mathematical complications. Avoiding advanced solving techniques for these hybrid systems, this paper introduces an alternative that enables pure continuous MPC by smoothing the jumps. Although the resulting underlying model is continuous, it is also highly nonlinear. This requires use of the specialized class of nonlinear model predictive control (NMPC), which is able to cope with the arising nonlinearities. Control inputs computed by these methods can be translated to the original hybrid system by a final post-processing step. This paper presents the outlined scheme, and verifies it by applying an optimized NMPC implementation (the DotX nonlinear predictive controller, DNPC), equipped with the approximated continuous nonlinear model, to a real-life hybrid water system.

scholarly journals Planning and Managing the Integrated Water System: A Spatial Decision Support System to Analyze the Infrastructure Performances

2020 ◽  
Vol 12 (16) ◽  
pp. 6432
Author(s):  
Michele Grimaldi ◽  
Monica Sebillo ◽  
Giuliana Vitiello ◽  
Vincenzo Pellecchia
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Water System ◽  
Decision Makers ◽  
Spatial Decision Support System ◽  
Human Beings ◽  
Spatial Decision Support ◽  
System A ◽  
The Individual

The demand for water is constantly increasing, while there are factors related to climate change and pollution that make it less and less available. Addressing this problem means being able to face it with a global approach, which takes into account that human beings need water to survive, as well as all the systems on which they rely, namely sanitation, health, education, business, and industry. While human behavior is influenced by the growing awareness on this topic promoted by organizations specifically targeting this mission, the need to protect water resources in operational terms has led mainly to the need for smart urban infrastructure planning, consistent with the objective of promoting sustainable development. To this aim, the authorities in charge of monitoring the implementation of the investment plans by operators need to perform accurate evaluations of the technical quality of the services provided. The present paper introduces a framework to design a Multi-criteria Spatial Decision Support System, conceived to help decision-makers define and analyze the investment priorities of the individual service operators. By building a knowledge model of the network under investigation, decision-makers are aware of physical components of the whole system and are provided with an intervention priority index related to the network objects that could be affected by the planning action to be implemented.

scholarly journals Distributed tree-based model predictive control on a drainage water system

2012 ◽  
Vol 15 (2) ◽  
pp. 335-347 ◽  
Author(s):  
J. M. Maestre ◽  
L. Raso ◽  
P. J. van Overloop ◽  
B. De Schutter
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Drainage System ◽  
Water System ◽  
Open Water ◽  
Weather Forecast ◽  
Drainage Water ◽  
Programming Approach ◽  
Continuous Exposure ◽  
Dual Decomposition

Open water systems are one of the most externally influenced systems due to their size and continuous exposure to uncertain meteorological forces. The control of systems under uncertainty is, in general, a challenging problem. In this paper, we use a stochastic programming approach to control a drainage system in which the weather forecast is modeled as a disturbance tree. Each branch of the tree corresponds to a possible disturbance realization and has a certain probability associated to it. A model predictive controller is used to optimize the expected value of the system variables taking into account the disturbance tree. This technique, tree-based model predictive control (TBMPC), is solved in a distributed fashion. In particular, we apply dual decomposition to get an optimization problem that can be solved by different agents in parallel. In addition, different possibilities are considered in order to reduce the communicational burden of the distributed algorithm without reducing the performance of the controller significantly. Finally, the performance of this technique is compared with others such as minmax or multiple MPC.

scholarly journals Basin-scale hydrogeological, geophysical, geochemical and isotopic characterization: an essential tool for building a Decision Support System for the sustainable management of alluvial aquifer systems within the provinces of Milan and Monza-Brianza

2016 ◽  
Author(s):  
Maurizio Gorla ◽  
Roberto Simonetti ◽  
Chiara Righetti
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Water Supply ◽  
Water Resource ◽  
Support System ◽  
Groundwater Resources ◽  
Water System ◽  
Aquifer Systems ◽  
Basin Scale ◽  
Isotopic Characterization

CAP Group is a public company, supplying the municipalities within the provinces of Milan and Monza/Brianza (Northern Italy) with the integrated water service: 197 municipalities and more than 2 million users served, 887 wells, 154 wall-mounted tanks and hubs, a water supply network of over 7500 km, from which approximately 250 million cubic metres of water per year are withdrawn. The drinking water supply comes exclusively from groundwater resources, circulating in several overlapping aquifer systems. Basin-scale water resource management, as required by the European Water Framework Directive (2000/60/EC), is an extremely complex task. In view of this backdrop, CAP is currently developing a project called Infrastructural Aqueduct Plan that relies on a Decision Support System approach. The paper describes the preliminary steps concerning the design of a prototype Decision Support System aiming at the management of groundwater resources on a basin scale (Ticino and Adda rivers area). CAP Group Decision Support System is intended to be a package allowing for water resource assessment, identification of boundary conditions, climatic driving forces and demographic pressures, simulation and investigation of future forecasts and comparison of alternative policy measures. The project has been designed in steps including Geodatabase building, geographic information system (GIS) analysis (including multilayer analysis) and numerical modelling. The data collected in the geodatabase were analyzed to design GIS quantitative and qualitative thematic maps in order to perform the multilayer analysis of current and future state and impacts, for providing the decision maker with a comprehensive picture of the water system. The multilayer analysis relies on specific indicators based on some quantitative and qualitative data: hydrogeological, chemical, isotopic, soil use and hazards, climatic and demographic. Each parameter belonging to these macro areas were classified by 7-criticality classes scale and weights were assigned to each of them. For each macro area a synthetic index was calculated by multiplying class values with weights. These synthetic indexes were managed with a multilayer approach and compared with other models and tools (e.g. geological model, numerical groundwater model, distribution network model) in order to obtain criticality indexes. The assessment of these criticality indexes allow to evaluate alternative and strategic solutions to achieve a more efficient and sustainable water system management using a best choice approach. Currently the project team is working on multilayer analysis. The next task will be the implementation of groundwater numerical model.

scholarly journals Decision support system for metabolism-based transition to urban water systems of tomorrow

2016 ◽  
Vol 16 (3) ◽  
pp. 855-863 ◽  
Author(s):  
Mark Morley ◽  
Kourosh Behzadian ◽  
Zoran Kapelan ◽  
Rita Ugarelli
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Real Life ◽  
Water System ◽  
Intervention Strategies ◽  
Urban Water ◽  
Urban Water System ◽  
Northern European ◽  
And Performance

A decision support system (DSS) tool for the assessment of intervention strategies in an urban water system (UWS) with an integral simulation model called ‘WaterMet2’ is presented. Lists of intervention options and performance indicators are exposed by the DSS for the user to define intervention strategies and metrics for their comparison. The quantitative and risk-based metrics are calculated by WaterMet2 and risk modules, while the qualitative metrics may be quantified by external tools feeding into the DSS. Finally, a multi-criteria decision analysis approach is employed in the DSS to compare the defined intervention strategies and rank them with respect to a pre-specified weighting scheme for different scenarios. This mechanism provides a useful tool for decision makers to compare different strategies for the planning of UWS with respect to multiple scenarios. The suggested DSS is demonstrated through the application to a northern European real-life case study.

scholarly journals Water demand and supply analysis using a spatial decision support system

2013 ◽  
Vol 3 (3) ◽  
pp. 199-209
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Water Demand ◽  
Water Allocation ◽  
Water System ◽  
Spatial Decision Support System ◽  
Spatial Decision Support ◽  
Demand And Supply ◽  
Water Demand And Supply

A prototype Spatial Decision Support System for the evaluation of water demand and supply management schemes is presented. The water basin is topologically mapped to a network of spatial objects representing the physical entities and their connections. Several GIS functions, which include data input/update, network derivation from the basin map and network building/modification are incorporated. The tool integrates suitable models for demand site requirements calculation and water allocation. Alternative scenarios can be constructed, trends and interactions of the complex water system can be analysed, strategies to solve water allocation conflicts can be evaluated and necessary infrastructure interventions can be planned in advance in order to meet water needs. The tool is demonstrated through a case study, involving the current situation and future policies for a typical Greek island.

scholarly journals Decision support system for the long-term city metabolism planning problem

2015 ◽  
Vol 16 (2) ◽  
pp. 542-550 ◽  
Author(s):  
M. S. Morley ◽  
D. Vitorino ◽  
K. Behzadian ◽  
R. Ugarelli ◽  
Z. Kapelan ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
User Interfaces ◽  
Performance Metrics ◽  
Real Life ◽  
Water System ◽  
Planning Horizon ◽  
Planning Problem

A decision support system (DSS) tool for the assessment of intervention strategies (Alternatives) in an urban water system (UWS) with an integral simulation model called ‘WaterMet2’ is presented. The DSS permits the user to identify one or more optimal Alternatives over a fixed long-term planning horizon using performance metrics mapped to the TRUST sustainability criteria. The DSS exposes lists of in-built intervention options and system performance metrics for the user to compose new Alternatives. The quantitative metrics are calculated by the WaterMet2 model, and further qualitative or user-defined metrics may be specified by the user or by external tools feeding into the DSS. A multi-criteria decision analysis approach is employed within the DSS to compare the defined Alternatives and to rank them with respect to a pre-specified weighting scheme for different Scenarios. Two rich, interactive graphical user interfaces, one desktop and one web-based, are employed to assist with guiding the end user through the stages of defining the problem, evaluating and ranking Alternatives. This mechanism provides a useful tool for decision makers to compare different strategies for the planning of UWS with respect to multiple Scenarios. The efficacy of the DSS is demonstrated on a northern European case study inspired by a real-life UWS for a mixture of quantitative and qualitative criteria. The results demonstrate how the DSS, integrated with an UWS modelling approach, can be used to assist planners in meeting their long-term, strategic-level sustainability objectives.

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