Calibration of Design Models for Leakage Management of Water Distribution Networks

Water Resources Management - Water losses in urban water distribution networks (WDN) accelerate the deterioration of such infrastructures. The enhanced hydraulic modelling provides a...     

Calibration Model for Water Distribution Network Using Pressures Estimated by Artificial Neural Networks

The success of hydraulic simulation models of water distribution networks is associated with the ability of these models to represent real systems accurately. To achieve this, the calibration phase is essential. Current calibration methods are based on minimizing the error between measured and simulated values of pressure and flow. This minimization is based on a search of parameter values to be calibrated, including pipe roughness, nodal demand, and leakage flow. The resulting hydraulic problem contains several variables. In addition, a limited set of known monitored pressure and flow values creates an indeterminate problem with more variables than equations. Seeking to address the lack of monitored data for the calibration of Water Distribution Networks (WDNs), this paper uses a meta-model based on an Artificial Neural Network (ANN) to estimate pressure on all nodes of a network. The calibration of pipe roughness applies a metaheuristic search method called Particle Swarm Optimization (PSO) to minimize the objective function represented by the difference between simulated and forecasted pressure values. The proposed method is evaluated at steady state and over an extended period for a real District Metering Area (DMA), named Campos do Conde II, and the hypothetical network named C-town, which is used as a benchmark for calibration studies.     

Location and Calibration of Valves in Water Distribution Networks Using a Scatter-Search Meta-heuristic Approach

Recently, there has been an increase in the use of meta-heuristic techniques addressing water distribution network design and management optimization problems. The meta-heuristic approach applied to water distribution systems has provided interesting results both for optimum pipe diameter sizing and for the location and management of network pressure control devices (i.e., pumps and valves). Regarding the insertion and calibration of pressure regulation valves, the use of meta-heuristic techniques is relatively recent. We search to strategically placing the valves in order to achieve pressure control in the network and, therefore, the valves must be calibrated in relation to water demand trends over time. In the Pressure Reference Method (PRM) described in this paper, the search for valve location is restricted to pipe-branch sets defined on the basis of hydraulic analysis and considering the range between minimum and maximum acceptable pressures in the network. In the PRM approach, the Scatter-Search (Glover and Laguna, 1997) meta-heuristic procedures are applied to obtain the optimal location and calibration of valves in the water distribution network.     

Leakage Identification in Water Distribution Networks with Error Tolerance Capability

Leakages in water distribution networks have caused considerable waste of water resources. Thus, this study proposes a novel method for hydraulically monitoring and identifying regions where leakages occur in near-real time. A large network is first divided into several identification regions. To exploit a strong constructive and discriminative power, sparse coding is used, thereby adaptively coding the information embedded in observed pressures efficiently and succinctly. And a linear classifier is trained to determine the most likely leakage regions. A benchmark case is presented in this study to demonstrate the effectiveness of the proposed method. Results indicate that the proposed method can identify leakage events with enhanced tolerance capability for measurement errors. The method is also partially effective for identifying two simultaneous leakages. Certain practical advice in balancing the number of sensors and regions is also discussed to enhance the application potential of this method.

     

Detection of Leakage Freshwater and Friction Factor Calibration in Drinking Networks Using Central Force Optimization

Inverse Transient Analysis (ITA) is a powerful approach for leak detection and calibration of friction factors in pressurized pipes. Through this method, a transient flow is initiated and pressures are measured somewhere in the system. Then, a nonlinear programming (NLP) problem with a least-squares criterion objective function is developed to minimize discrepancies between the measured and calculated pressures at measurement sites. Solving the raised NLP results in the problem’s unknowns being leakage specifications and pipe friction factors. For this purpose, various optimization techniques may be utilized. This issue is a major challenge for ITA-based methods. The present work aims at applying the new method of Central Force Optimization (CFO) to the problem of ITA. CFO is a deterministic metaheuristic inspired by gravitational kinematics in which small objects in space are dragged by bigger ones. Herein, the concept and main structure of CFO are represented as well as of CFO. A reference pipe-network is considered to be solved using the ITA equipped with CFO. The results are then discussed compared to the previous works. It is concluded that CFO is easy to implement, computationally efficient and has a remarkable performance in solving leak detection problem.     

GA-ILP Method for Optimization of Water Distribution Networks

Optimization of water distribution networks has been of central importance for recent decades. Genetic Algorithms (GA) are the most famous metaheuristics widely used for this purpose with great success. However, the fact that GA basically requires a large number of computations, has led to investigate for faster solvers. In this research, a new approach is proposed in which a simple GA is linked with the Integer-Linear Programming (ILP) method resulting in a hybrid optimization scheme. Using the mathematical method of ILP, the search space is significantly reduced thereby a limited number of evaluations are required to achieve a good solution. The approach is applied to two benchmark pipe-networks in order to show its ability in terms of accuracy and speed. The results are then compared with the previous works. The obtained results indicate that the proposed model is computationally efficient, like classic methods, while is still very promising in finding the global optimum like the nature-inspired metaheuristics.     

Dealing with Zero Flows in the Simulation of Water Distribution Networks with Low-Resistance Pipes Using the Global Gradient Algorithm

Water Resources Management - This paper shows that the zero flow treatment algorithm and the convergence criteria of EPANET 2.2, the latest version of the EPANET 2 open-source software package, may...     

Modeling of Drinking Water Distribution Networks Using Stochastic Demand

Residential water demand is one of the most difficult parameters to determine when modeling drinking water distribution networks. It has been proven to be a stochastic process that can be characterized as a series of rectangular pulses with a set intensity, duration and frequency. These parameters can be determined using stochastic models such as the Neyman-Scott Rectangular Pulse (NSRP) model. The NSRP model is based on the solution of a non-linear optimization problem. This solution involves theoretical moments that represent the synthetic demand series (equiprobable) and the observed moments (field measurements) that statistically establish the measured demand series. The NSRP model has been applied for residential demand, and the results have been published. However, this model has not been validated for a real distribution network or compared with traditional methods. The present study compared the results of synthetic stochastic demand series, which were calculated using the NSRP model, applied to the determination of pressures, flow rates and leaks; to the results obtained using traditional simulation methods, which use the curve of hourly variation in demand, and to actual pressure and flow rate measurements. The Humaya sector of Culiacan, Sinaloa, Mexico, was used as the study area.     

A Branch-and-Bound Algorithm for Optimal Pump Scheduling in Water Distribution Networks

Nowadays water distribution operation systems are accomplished with the aid of qualified professionals who use their experience in order to achieve a satisfactory performance of the several hydromechanical devices, which are part of the system, such as boosters and valves. In general, these operational rules are empirical and the main goal is to assure the availability of water for the population, with no special concerns about saving energy used in pumping systems. Besides, these empirical rules often disregard hours of lower energy rates. There are several research works concerning the developments of operational rules optimization applied to specific water distribution systems. However, in this work, a general optimization routine integrated with EPANET is presented, which allows the determination of strategic optimal rules of operation for any type of water distribution system. Moreover, a Branch-and-Bound algorithm is also used, where finding the global optimal solution is guaranteed, in admissible computational times. The water distribution system used in this work corresponds to a hypothetical network proposed in the specialized literature.     

Design of Water Distribution Networks using a Pseudo-Genetic Algorithm and Sensitivity of Genetic Operators

Genetic algorithms (GA) are optimization techniques that are widely used in the design of water distribution networks. One of the main disadvantages of GA is positional bias, which degrades the quality of the solution. In this study, a modified pseudo-genetic algorithm (PGA) is presented. In a PGA, the coding of chromosomes is performed using integer coding; in a traditional GA, binary coding is utilized. Each decision variable is represented by only one gene. This variation entails a series of special characteristics in the definition of mutation and crossover operations. Some benchmark networks have been used to test the suitability of a PGA for designing water distribution networks. More than 50,000 simulations were conducted with different sets of parameters. A statistical analysis of the obtained solutions was also performed. Through this analysis, more suitable values of mutation and crossover probabilities were discovered for each case. The results demonstrate the validity of the method. Optimum solutions are not guaranteed in any heuristic method. Hence, the concept of a “good solution” is introduced. A good solution is a design solution that does not substantially exceed the optimal solution that is obtained from the simulations. This concept may be useful when the computational cost is critical. The main conclusion derived from this study is that a proper combination of population and crossover and mutation probabilities leads to a high probability that good solutions will be obtained.     

A Prioritization Model for Rehabilitation of Water Distribution Networks Using GIS

Decision-making for the rehabilitation of water distribution networks in the traditional procedure is based on some simple indices such as the number of incidents while several mechanical, hydraulic and qualitative factors are involved in this process. Evidently, making decision on the rehabilitation of water networks seems to be very difficult as the number of factors increases and they interact with each other. The main objective of this research is to prepare, implement and evaluate a conceptual model to prioritize the rehabilitation of pipes based on different scenarios with respect to the combination effects of basic factors in physical, hydraulic and experimental categories. In order to organize the wide range of data to be used in decision-making models, including the plans aimed for pipe replacement, it is necessary to use geographical information systems (GIS). By determining and introducing the factors involved in the rehabilitation of water networks, this research aims to provide an integrated model consisting of conceptual, GIS, hydraulic analysis and the breakage models to prioritize the rehabilitation schemes. By using the data provided from a real network, the advantages of the proposed methodology are evaluated. Based on the obtained results, age factor, among all the other physical parameters, and pressure, among the hydraulic factors, have the greatest influence in outlining the final rehabilitation scenario. The importance of the pipe length has decreased considerably as well. Furthermore, it can be concluded that rehabilitation management of pipe networks can be optimized by using this methodology.     

Leak Prediction Model for Water Distribution Networks Created Using a Bayesian Network Learning Approach

Water leakage in water distribution systems (WDSs) can bring various negative economic, environmental, and safety effects. Therefore, predicting water leakage is one of the most crucial tasks in water resource management; however, it is also one of the most challenging ones. Previous leakage-related studies have only focused on detecting existing leaks. This paper presents a novel model using expert structural expectation–maximisation, for predicting water leakage in WDSs. The model can take into account the uncertainty of leakage-related factors and balance the contribution of monitoring data and prior information in a Bayesian learning process to maximise leakage prediction accuracy. Moreover, the proposed method can indicate the most crucial factors affecting water leakage. The results of this study could benefit water utilities by aiding them in establishing an effective leakage control plan to minimise the risk of water leakage. A case study is presented to demonstrate the robustness and effectiveness of the proposed method.     

Application of Parameter-Less Rao Algorithm in Optimization of Water Distribution Networks Through Pressure-Driven Analysis

Water Resources Management - Water distribution networks (WDNs) connect consumers to the source of water. The primary goal of optimizing WDNs is to minimize the network costs as WDNs entail high...     

Pressure Management Through Optimal Location and Setting of Valves in Water Distribution Networks Using a Music-Inspired Approach

Pressure management through Pressure Reducing Valves (PRVs) is probably the most used approach related to the leakage management in Water Distribution Networks (WDNs). Its effectiveness in reducing the amount of water losses in existing networks has been highlighted in many papers. In this study, the topic is addressed with particular reference to meta-heuristic optimization techniques, that have proved to be very effective in producing good results with reduced use of computational resources. In particular, the application of the Harmony-Search (HS) method to the location and setting of a pre-fixed number of PRVs is proposed and discussed. A single objective optimization problem is defined which aims at the leakage reduction through the minimization of the water pressures. A double harmonic component is adopted for taking into account both the location and the setting of each PRV. The hydraulic constraints handled by a simulation software are considered as well. The approach is applied to a couple of WDNs: one is the Jowitt and Xu well-known literature test case and the other is a real WDN in Naples, called Napoli Est. The methodology has showed very good results compared to those obtained by using classical Genetic Algorithm techniques both in terms of leakage reduction and computation time.     

Spatial Analysis and Failure Management in Water Distribution Networks Using Fuzzy Inference System

Water Resources Management - Periodic surface inspections of Water Distribution Networks (WDNs) buried in the soil aren’t possible. Failures, leakage or malfunctioning to these networks...     

Self-Adaptive Solution-Space Reduction Algorithm for Multi-Objective Evolutionary Design Optimization of Water Distribution Networks

An effective way to improve the computational efficiency of evolutionary algorithms is to make the solution space of the optimization problem under consideration smaller. A new reliability-based algorithm that does this was developed for water distribution networks. The objectives considered in the formulation of the optimization problem were minimization of the initial construction cost and maximization of the flow entropy as a resilience surrogate. After achieving feasible solutions, the active solution space of the optimization problem was re-set for each pipe in each generation until the end of the optimization. The algorithm re-sets the active solution space by reducing the number of pipe diameter options for each pipe, based on the most likely flow distribution. The main components of the methodology include an optimizer, a hydraulic simulator and an algorithm that calculates the flow entropy for any given network configuration. The methodology developed is generic and self-adaptive, and prior setting of the reduced solution space is not required. A benchmark network in the literature was investigated, and the results showed that the algorithm improved the computational efficiency and quality of the solutions achieved by a considerable margin.     

Optimal Location of Pump as Turbines (PATs) in Water Distribution Networks to Recover Energy and Reduce Leakage

Water distribution networks are high energy and low efficiency systems, where water pressure is frequently reduced by dissipation valves to limit leakage. The dissipation produced by the valves can be converted to energy production to increase the efficiency and reduce the energy impact of networks. If valves are replaced by turbines or pumps as turbines (PATs), they can both reduce pressure and produce energy. This study focuses on the optimal location of PATs within a water distribution network in order to both produce energy and reduce leakage. A new optimization model is developed consisting of several linear and non-linear constraints and a newly proposed objective function, where the turbine installation costs as well as the energy production and the economic saving due to the reduction of leakage can be accounted all together. The case study shows that the application of the mathematical model to a synthetic network ensures better results, in terms of both energy production and water saving, in comparison to other procedures.     

建立给水管网微观动态水力模型标准方法研究

阐述了水司建立给水管网微观动态水力模型的必要性 ,提出了一套适合我国国情的给水管网建模标准方法。这一方法将有助于我国给水管网建模工作走上正规化和科学化的道路。该方法已经成功地应用于上海市。     

Method for Extended Period Simulation of Water Distribution Networks with Pressure Driven Demands

This paper proposes a non-iterative method to perform the simulation of water distribution systems with pressure driven demands using EPANET2 without the need to use its programmer’s toolkit. The method works for single period simulation (snapshot) and for extended period simulation (EPS) as well. It is based on the addition of a flow control valve (FCV), a throttle control valve (TCV), a check valve (CV) and a reservoir to each demand node in the network, in addition to a list of simple controls to modify the setting of the FCV and TCV in each time step. The main advantages of this approach are: 1. the source code of EPANET2 is not modified, 2. the toolkit functions are not needed for the simulation and they remain available for further uses, 3. the extended period simulation (EPS) is performed by EPANET2 and it carries tank levels, demand variation and other time-changing variables internally. The performance of the method is tested in two benchmark networks and a real size network with pumps, tanks and a 24 h demand pattern. The results show that the method computed the pressures and outflows accurately and that the computational time required is not significantly higher than a demand driven execution in most cases.