Control Of Water Distribution Networks Research Articles

A method for water supply network DMA partitioning planning based on improved spectral clustering

Abstract Recently, the scale and complexity of water distribution networks (WDNs) have been increasing with the acceleration of urbanization process. It has become a hot research focus to use district metering area (DMA) for more efficient management and control of WDNs. This article proposes a multistage DMA planning method based on improved weighted spectral clustering and genetic algorithm, aiming to address issues such as high investment cost and large differences in the water network demand distribution. First, the actual case pipe network is transformed into an undirected weighted graph based on graph theory, and a similarity matrix is formed by combining the physical properties and hydraulic characteristics of the water network. Then, based on the similarity matrix, the weighted spectral clustering algorithm is used to preliminarily divide the WDN, and the performance of the water supply pipe network formed with different division quantities and different weighting schemes is discussed. Finally, the genetic algorithm is used to optimize the arrangement of valves and flow meters on boundary pipes to generate the final configuration of DMA. The results show that the proposed method has a significant improvement in pipe network topology, hydraulic performance index, and economy compared with the traditional DMA method.

Port-Hamiltonian based control of water distribution networks

We design controllers for a nonlinear model of a water distribution network (WDN). Most existing approaches to the control of WDNs model the pumps as simple pressure gains. We show that a commonly used empirical model of a pump leads to a port-Hamiltonian (pH) and hence stable system. We use standard arguments to show that WDNs are incrementally pH, and show that local PI controllers preserve stability. These controllers are robust in that they do not require specific knowledge of the equilibrium input. We further show that controllers based on physical feedback that WDN operators usually rely on have merit in the pH framework. All of these controllers are shown to be useful in mitigating disturbances and tracking setpoints corresponding to assignable equilibria.

Adaptive Model Predictive Control for Fire Incidents in Water Distribution Networks

The real-time control of water distribution networks for firefighting is an important but little-studied problem. Water utilities in England and Wales reduce hydraulic pressure to a minimum regulatory threshold in order to reduce leakage and avoid financial penalties. However, utilities are not legally bound to guarantee specific flow rates from fire hydrants, which poses a risk for firefighting. This study presents an adaptive nonlinear model predictive control scheme for water distribution networks integrating two modes of control: (1) normal control, when a network operates under normal conditions and the objective is to minimize energy costs and average zonal pressure, and (2) fire control, when fire flows need to be delivered from hydrants without exceeding maximum pressure and customer demand is maintained to the best extent possible. The proposed scheme is applied to an operational network. It demonstrates the combined benefits of reducing costs and leakage with increased fire flows.

IoT-Enabled Water Distribution Systems—A Comparative Technological Review

Water distribution systems are one of the critical infrastructures and major assets of the water utility in a nation. The infrastructure of the distribution systems consists of resources, treatment plants, reservoirs, distribution lines, and consumers. A sustainable water distribution network management has to take care of accessibility, quality, quantity, and reliability of water. As water is becoming a depleting resource for the coming decades, the regulation and accounting of the water in terms of the above four parameters is a critical task. There have been many efforts towards the establishment of a monitoring and controlling framework, capable of automating various stages of the water distribution processes. The current trending technologies such as Information and Communication Technologies (ICT), Internet of Things (IoT), and Artificial Intelligence (AI) have the potential to track this spatially varying network to collect, process, and analyze the water distribution network attributes and events. In this work, we investigate the role and scope of the IoT technologies in different stages of the water distribution systems. Our survey covers the state-of-the-art monitoring and control systems for the water distribution networks, and the status of IoT architectures for water distribution networks. We explore the existing water distribution systems, providing the necessary background information on the current status. This work also presents an IoT Architecture for Intelligent Water Networks - IoTA4IWNet, for real-time monitoring and control of water distribution networks. We believe that to build a robust water distribution network, these components need to be designed and implemented effectively.

Port-Hamiltonian Based Control of Water Distribution Networks

Port-Hamiltonian Based Control of Water Distribution Networks

Receding Horizon Control for Drinking Water Networks: The Case for Geometric Programming

Optimal, network-driven control of water distribution networks (WDNs) is very difficult: valve and pump models form nontrivial, combinatorial logic; hydraulic models are nonconvex; water demand patterns are uncertain; and WDNs are naturally of large scale. Prior research on control of WDN addressed major research challenges, yet either i) adopted simplified hydraulic models, WDN topologies, and rudimentary valve/pump modeling or ii) used mixed-integer, nonconvex optimization to solve WDN control problems. The objective of this article is to develop tractable computational algorithms to manage WDN operation, while considering arbitrary topology, flow direction, an abundance of valve types, control objectives, hydraulic models, and operational constraints-all while only using convex, continuous optimization. Specifically, we propose new geometric programming (GP)-based model predictive control (MPC) algorithms, designed to solve the water flow equations and obtain WDN controls, i.e., pump/valve schedules alongside heads and flows. The proposed approach amounts to solving a series of convex optimization problems that graciously scale to large networks. The proposed approach is tested using a 126-node network with many valves and pumps and is shown to outperform traditional, rule-based control. The developed GP-based MPC algorithms, as well as the numerical test results, are all included on Github.

Economic nonlinear predictive control of water distribution networks based on surrogate modeling and automatic clustering

The operation of large-scale water distribution networks (WDNs) is a complex control task due to the size of the problem, the need to consider key operational, quality and safety-related constraints as well as because of the presence of uncertainties. An efficient operation of WDNs can lead to considerable reduction in the energy used to distribute the required amounts of water, leading to significant economic savings. Many model predictive control (MPC) schemes have been proposed in the literature to tackle this control problem. However, finding a control-oriented model that can be used in an optimization framework, which captures nonlinear behavior of the water network and is of a manageable size is a very important challenge faced in practice. We propose the use of a data-based automatic clustering method that clusters similar nodes of the network to reduce the model size and then learn a deep-learning based model of the clustered network. The learned model is used within an economic nonlinear MPC framework. The proposed method leads to a flexible scheme for economic robust nonlinear MPC of large WDNs that can be solved in real time, leads to significant energy savings and is robust to uncertain water demands. The potential of the proposed approach is illustrated by simulation results of a benchmark WDN model.

Optimal control of water distribution networks without storage

The paper investigates the problem of optimal control of water distribution networks without storage capacity. Using mathematical optimization, we formulate and solve the problem as a non-convex NLP, in order to obtain optimal control curves for both variable speed pumps and pressure reducing valves of the network and thus propose a methodology for the automated control of real operational networks. We consider both single-objective and multi-objective problems with average zonal pressure, pump energy consumption and water treatment cost as objectives. Furthermore, we investigate global optimality bounds for the calculated solutions using global optimization techniques. The proposed approach is shown to outperform state-of-the-art global optimization solvers. The described procedure is demonstrated in a case study using a large size operational network.

A Real-Time Augmented Reality System for Water Distribution System

Control of water distribution network by Real-Time Monitoring System (RTMS) can play an inerrant role in its management. RTMS could be used to monitor and analyse hydraulic and water quality parameters in a Water Distribution Network (WDN). Besides, the RTMS warns operators on actions such as to stop pumping, to conserve water, and minimise risks when needed. RTMS can also provide many operational benefits (improve water quality, decrease operational costs, reduce customer complaints, reduce water losses, and modelling capability, etc.). For Quality & Maintenance of the distribution network, the concept of Augmented Reality (AR) can be used as a tool to support maintenance task as the Data from the distribution network can be gathered and parsed in real-time. The useful information will be transmitted to the AR device (PC tablet, smartphone, glasses, watch…) through wireless connectivity. This paper aims to introduce the concept of RTMS and AR technology. It provides a review of some RTMS application in the drinking water sector and shows the benefit of the implementation of AR in that environment. Furthermore, this paper attempts to propose how the RTMS and AR can be merged as system architecture and be applied to enhance the quality of the water within the network, the distribution system management, and maintenance of the distribution network.

A modeling and distributed MPC approach for water distribution networks

This paper deals with the modeling and control of water distribution networks consisting of multiple pressure zones that are interconnected by fixed-speed pumps. A simplified control-oriented model with linear dynamics and non-convex constraints which considers the pressures and losses in the zones is derived. Based on the model, a periodic distributed model predictive scheme which is tailored to the non-convex constraints and minimizes an economic objective is introduced. The scheme uses event-triggered communication between the subsystems to reduce the communicational load. The proposed model and controller are evaluated using a model of the water distribution network of the city of Kaiserslautern, Germany.

Intelligent system for control of water distribution networks

Abstract The objective of this research study was the development of an intelligent system based on artificial neural networks for water distribution networks that operate with parallel pumps. The purpose of the system is to automate the process and to define the operating state of the electric motors (on, off or with partial rotation speed). The intelligent system developed is generic, which allows the application of its control structure in similar processes, and it was applied in an experimental setup that simulates a real water supply system. The performance of the network was tested experimentally under different operating conditions, including in the presence of disturbances. The settling time was, in all experiments, less than 30 seconds, the tests did not show overshoot and the maximum error was 2.9%. Results showed excellent performance in terms of pressure regulation, and it is hoped that the controller can be successfully implemented in real water distribution systems, in order to reduce water and electricity consumption, decrease maintenance costs and increase the reliability of operating procedures.

Non-linear economic model predictive control of water distribution networks

This paper addresses a non-linear economic model predictive control (EMPC) strategy for water distribution networks (WDNs). A WDN could be considered as a non-linear system described by differential-algebraic equations (DAEs) when flow and hydraulic head equations are considered. As in other process industries, the main operational goal of WDNs is the minimisation of the economic costs associated to pumping and water treatment, while guaranteeing water supply with required flows and pressures at all the control/demand nodes in the network. Other operational goals related to safety and reliability are usually sought. From a control point of view, EMPC is a suitable control strategy for WDNs since the optimal operation of the network cannot be established a priori by fixing reference volumes in the tanks. Alternatively, the EMPC strategy should determine the optimal filling/emptying sequence of the tanks taking into account that electricity price varies between day and night and that the demand also follows a 24-hour repetitive pattern. On the other hand, as a result of the ON/OFF operation of parallel pumps in pumping stations, a two-layer control scheme has been used: a non-linear EMPC strategy with hourly control interval is chosen in the upper layer and a pump scheduling approach with one-minute sampling time in the lower layer. Finally, closed-loop simulation results of applying the proposed control strategy to the D-Town water network are shown.

Control of water distribution networks with dynamic DMA topology using strictly feasible sequential convex programming

AbstractThe operation of water distribution networks (WDN) with a dynamic topology is a recently pioneered approach for the advanced management of District Metered Areas (DMAs) that integrates novel developments in hydraulic modeling, monitoring, optimization, and control. A common practice for leakage management is the sectorization of WDNs into small zones, called DMAs, by permanently closing isolation valves. This facilitates water companies to identify bursts and estimate leakage levels by measuring the inlet flow for each DMA. However, by permanently closing valves, a number of problems have been created including reduced resilience to failure and suboptimal pressure management. By introducing a dynamic topology to these zones, these disadvantages can be eliminated while still retaining the DMA structure for leakage monitoring. In this paper, a novel optimization method based on sequential convex programming (SCP) is outlined for the control of a dynamic topology with the objective of reducing average zone pressure (AZP). A key attribute for control optimization is reliable convergence. To achieve this, the SCP method we propose guarantees that each optimization step is strictly feasible, resulting in improved convergence properties. By using a null space algorithm for hydraulic analyses, the computations required are also significantly reduced. The optimized control is actuated on a real WDN operated with a dynamic topology. This unique experimental program incorporates a number of technologies set up with the objective of investigating pioneering developments in WDN management. Preliminary results indicate AZP reductions for a dynamic topology of up to 6.5% over optimally controlled fixed topology DMAs.

Optimal control of water distribution networks with storage facilities

Optimal operation of water distribution networks (WDNs) is concerned with meeting consumer demands at desired pressures in an efficient and equitable manner while conserving resources. This can be achieved by implementing advanced control schemes such as model predictive control (MPC). If sufficient water is available, the control objective is to meet consumer demands while preventing wastage. On the other hand, if the available water is insufficient or inadequate to meet consumer demands at the required pressures, equitable distribution of the available resource is of primary importance. In this contribution, a nonlinear model predictive controller is proposed for optimal operation of WDNs that can deal with both the above situations. The proposed approach takes into account availability of storage facilities at the source and demand points. In addition, the control algorithm can account for plant-model mismatch. Performance of the proposed model based control strategy is illustrated through numerical simulations of an illustrative WDN operating under various water availability scenarios. In the water sufficient scenario, the proposed MPC strategy is able to meet the consumer requirements while minimizing the excess amount of water supplied. In the water deficient scenario, the MPC algorithm is able to exploit the available storage facilities at consumer end to reduce the daily supply deficit by about 20%. Using a longer prediction horizon in MPC results in a further reduction of about 40% in the daily supply deficit.

Adaptive water distribution networks with dynamically reconfigurable topology

This paper presents a novel concept of adaptive water distribution networks with dynamically reconfigurable topology for optimal pressure control, leakage management and improved system resilience. The implementation of District Meter Areas (DMAs) has greatly assisted water utilities in reducing leakage. DMAs segregate water networks into small areas, the flow in and out of each area is monitored and thresholds are derived from the minimum night flow to trigger the leak localization. A major drawback of the DMA approach is the reduced redundancy in network connectivity which has a severe impact on network resilience, incident management and water quality deterioration. The presented approach for adaptively reconfigurable networks integrates the benefits of DMAs for managing leakage with the advantages of large-scale looped networks for increased redundancy in connectivity, reliability and resilience. Self-powered multi-function network controllers are designed and integrated with novel telemetry tools for high-speed time-synchronized monitoring of the dynamic hydraulic conditions. A computationally efficient and robust optimization method based on sequential convex programming is developed and applied for the dynamic topology reconfiguration and pressure control of water distribution networks. An investigation is carried out using an operational network to evaluate the implementation and benefits of the proposed method.

Essential considerations in the computer control of water distribution systems

Overall, this paper presents a reliability perspective of the required systems and activities for control of water distribution networks. A description is initially given of the ways in which computers are being used for water control purposes. This is followed by an analysis of the important reliability features of the control system, the telemetry system, and the water system. Particular attention is devoted to the numerical reliability of the control modules, the data reliability of the telemetry transfers, and the operational reliability of the individual systems and components. The comments and conclusions are partly based on the design and implementation of an on-line control scheme for a city distribution network in the UK.

Editorial Special issue: French-UK Workshop on the Advances in Operational Control of Water Distribution Networks

"Editorial Special issue: French-UK Workshop on the Advances in Operational Control of Water Distribution Networks." CIVIL ENGINEERING SYSTEMS, 8(4), p. i