Operation Of Water Distribution Systems Research Articles

Modeling a game to shift peak water demands: WaterTime leaderboard

Residential water demands vary with a diurnal pattern, and peak hour demands lead to inefficiencies in the operation and management of urban water distribution systems. Peak hourly demands generate significant costs due to the energy requirements of producing and pumping large volumes of potable water. High peak demands also require large investments in infrastructure expansion to support urban growth and economic development. This research develops an agent-based model to assess a demand-side management strategy that shifts high hourly demands. This research envisions a gamification system that rewards players through a leaderboard for shifting water end uses for laundry, irrigation, and bathing from on-peak to off-peak periods. Gamification of demand shifting behaviors is enabled through advanced metering infrastructure, which measures hourly or sub-hourly demands at the account level, and can be analyzed to assess water use behaviors. This research develops an Agent-based Modeling approach based on the Opinion Dynamics theory to calculate the changing opinion of household agents toward shifting water demands, based on utility broadcasts, observations of neighbor water use, social media, and participation in a leaderboard. The model is applied for eight months of hourly demand data collected through smart meters at a participating utility. Results show that a high level of participation in the leaderboard increases the adoption rate of customers shifting the time of specific end uses and may account for up to a 37 % reduction of the peak volume. The diurnal curve is flattened as consumers shift water use from on-peak to off-peak hours. The Agent-Based Model - Opinion Dynamics approach can assist water utilities in designing and evaluating gamification approaches that mitigate peak demands to support water infrastructure management.

An Optimal Upgrading Framework for Water Distribution Systems Operation

An Optimal Upgrading Framework for Water Distribution Systems Operation

Employing Tank Constraints to Present Total Cost and Water Age Trade-Offs in Optimal Operation of Water Distribution Systems

Employing Tank Constraints to Present Total Cost and Water Age Trade-Offs in Optimal Operation of Water Distribution Systems

Machine learning for water demand forecasting: Case study in a Brazilian coastal city

ABSTRACT Water resources management is crucial for human well-being and contemporary socio-economic development. However, the increasing use of water has led to various problems that affect its quality and availability. To address these issues, accurate forecasting of water consumption is essential for the optimal operation of water collection, treatment, and distribution systems. This study aims to compare four machine learning methods for predicting daily urban water demand in a Brazilian coastal tourist city (Guaratuba – Paraná). Historical data from the city’s water distribution system, spanning from 2016 to 2019 (1,461 measurements in total), were considered along with meteorological and calendar data to conduct the investigation. Three time series cross-validation approaches were considered for each method, thus totaling 12 evaluation settings. All models were subjected to hyperparameter optimization and evaluated using appropriate performance metrics from the literature. Results demonstrate the importance of using nonlinear models to predict short-term water demand, highlighting the problem’s complexity. From the compared models, multilayer perceptron provided the best results. Finally, regardless of the model, the best results were obtained by applying an expanding window time series cross-validation, indicating that the more historical data available, the better, in this particular case.

Opflow Celebrates 50 Years of Operators Teaching Operators

After 50 years of publication, Opflow continues to share practical advice and wisdom with water treatment and distribution system operators. Operators sharing what they’ve learned is one of the most effective ways to ensure successful continuity in any utility.

Adjustable Robust Optimization for Water Distribution System Operation Under Uncertainty

AbstractThe optimal operation of water distribution systems (WDS) is a paramount objective for water utilities due to the substantial energy consumption associated with pumping. A major challenge in optimizing WDS operation is addressing uncertainties such as those related to consumer demands. Real‐time operation under uncertainty necessitates a dynamic approach that can utilize the newly observed information and adjust the operational policy accordingly. This study presents an adjustable robust optimization (ARO) approach to tackle this challenge. Unlike static optimization methods, ARO generates a decision rule policy that is dynamically adjusted as new data becomes available and the operational horizon evolves, thereby ensuring adaptability to changing conditions. Furthermore, the study includes a quantitative analysis of typical demand uncertainty that supports the formulation of the ARO model. The proposed method is evaluated through two case studies and compared with traditional folding horizon approaches. The results indicate that the ARO method is competitive with traditional methods in terms of objective value and surpasses them in terms of robustness. An additional advantage of the method is its offline operation capability which enables it to produce decision rules independent of real‐time programs. This feature facilitates various practical applications such as what‐if analyses, maintenance work planning, and preparation for other special events.

Dependence of actual filling level of gravity flow water distribution on sediment thickness in benching part of pipes

The regulatory requirements of SP 32.13330.2018 (Sewerage. Pipelines and wastewater treatment plants) set the minimum sewage velocity in water distribution systems, depending on the highest filling level of pipes. It is known that during the operation of gravity flow water distribution systems under certain conditions, a layer of internal sediments might be formed, which increases the filling level of pipes and changes the values of the hydraulic characteristics of the flow. The study suggests the dependence between the values of hydraulic characteristics of the flow and the amount of internal sediments on the surface where the sewage flows. The authors introduced the calculated dependencies for hydraulic calculation of gravity flow water distribution systems with sediments on the surface where the sewage is moving. The study confirmed the dependence of the actual filling level of gravity flow water distribution systems on the amount of sediments on the surface. A specific example confirming the existence of such a dependence was given. The paper presented a graph of dependence between actual filling level and sediment thickness in benching part of pipes. It was shown that during the operation of gravity flow water distribution systems with internal sediments it is necessary to control the value of the actual filling of pipes 𝐻ф 𝑑пр and the amount of sediment in their benching part ℎ, which have a significant impact on the values of the hydraulic characteristics of the sewage flow.

Water distribution system design integrating behind-the-meter solar under long-term uncertainty

Water distribution systems (WDSs) are important urban water infrastructure supporting a wide range of human activities. Due to the significant amount of energy consumed by the WDS throughout its lifespan, the operation of WDSs may have a significant impact on the environment, affecting the sustainable development of cities into the future. Behind-the-metre (BTM) solar photovoltaic (PV) system integration has been considered an effective way to reduce the impact of WDSs on the environment. However, solar PV technology is developing rapidly. Combined with long-term changes in water demand driven by population growth and urbanisation, the design of a WDS considering BTM solar has become a more challenging task. In this study, the co-design of WDS integrating BTM solar PV systems under changing future conditions in terms of water demand and solar PV technology development is investigated. It has been found that the BTM solar PV system and the potential development in solar PV technology effectively improve the robustness of WDS design under uncertain future water demand. The outcomes of this study can be extended to guide infrastructure design to provide sustainable infrastructure for future cities, and therefore cities can continue to support human activities in deeply uncertain future.

Deep fuzzy mapping nonparametric model for real-time demand estimation in water distribution systems: A new perspective.

Hydraulic modeling has been recognized as a valuable tool for improving the design, operation, and management of water distribution systems (WDSs) as it allows engineers to simulate and analyze behaviors of WDSs in real time and help them make scientific decisions. The informatization of urban infrastructure has motivated the real-time fine-grained control of WDSs, making it one of the hotspots in recent years, thereby putting higher requirements on WDS online calibration in terms of efficiency and accuracy, especially when dealing with large-complex WDSs. To achieve this purpose, this paper proposes a novel approach (i.e., deep fuzzy mapping nonparametric model (DFM)) from a new perspective for developing a real-time WDS model. To our knowledge, this is the first work that considers uncertainties in modeling problems using fuzzy membership functions and establishes the precise inverse mapping from pressure/flow sensors to nodal water consumption for a given WDS based on the proposed DFM framework. Unlike most traditional calibration methods that require time to optimize model parameters, the DFM approach has a unique analytical solution derived through rigorous mathematical theory, thus the DFM is computationally fast as a result of sensibly handling the problems whose solutions typically require iterative numerical algorithms and large computational time. The proposed method is applied to two case studies and the results obtained show that it can produce a real-time estimation of nodal water consumption with higher accuracy, computational efficiency, and robustness relative to traditional calibration methods.

Coefficients and curves of hourly and daily variations of water demand for improved operation of potable water distribution systems: a case study of Chihuahua City, Mexico

Abstract Maintaining a constant flow in a potable water distribution hydraulic system is challenging due to fluctuations caused by changes in user demand and seasonal factors. This study aimed to calculate the coefficients and curves of hourly and daily variation of water demand in the water distribution system of Chihuahua. It is crucial to understand the hydraulic system's behavior during peak demands and assess its capacity. The methodology involved calculating coefficients and curves of variation of demand based on flow data measured at the inlet of various hydrometric sectors using flanged electromagnetic flowmeters of various diameters and models. The results showed that the variation curves and coefficients of water demand are valuable tools for modeling, designing, and operating water networks. Incorporating these curves into hydraulic simulations during the planning and design stage can improve the accuracy of these models and better reflect the network's actual behavior. The proposed method is suitable for application in cities with similar demographic and social characteristics. The study concludes that accurate supply area information for hydrometric sectors is essential in constructing the curves and coefficients of demand variation, which can lead to opportunities for improving water service by informing more effective network design and operation.

Robust Optimal Operation of Water Distribution Systems

The operation of water distribution systems (WDS) is an energy-intensive process, which is subject to constraints such as consumer demands, water quality, and pressure domains. As such, tracing an operation policy in which constraints are met while energy costs are minimized, is a foremost objective for water utilities. Given the inherent uncertainties in WDS operation and the importance of supply continuity, it is essential to find an operational strategy that is robust against a wide range of circumstances. One promising approach for optimization under uncertainty is robust optimization (RO), which assures a robust (feasible) solution to realizations of the uncertain parameters, within predefined bounds. This study presents an RO-based method for optimizing pump scheduling under uncertainties of consumer demands and pumping costs. The method can capture various types of correlations between the uncertain parameters, thus better reflecting the uncertain nature of WDS operation. The developed methodology is demonstrated in two case studies with different levels of complexity. The impacts of uncertainty levels and correlation coefficients are analyzed to demonstrate their implications on operation policy. The results show the advantages of using RO with tradeoffs between costs and constraints satisfaction.

Optimization of the operation of water distribution systems with emphasis on the joint optimization of pumps and reservoirs

Abstract The high costs generated by water supply systems’ pumping stations has generated great concerns regarding concessionaire companies in the sector. Improvements to increase these systems’ efficiency and consequently reduce electricity costs have been the objective of several researchers and technicians responsible for the sector. Given the many elements that compose these systems, finding the best operational rules is frequently a complex activity. In this context, the present work includes an optimization model based on genetic algorithms that combine the efficient use of reservoirs with the best operational rule for activating pumping systems. The results indicate that with better use of the water storage infrastructure, it is possible to reduce costs for the electricity of the system as a whole.

Adaptation and Resilience

In times of social and environmental changes, water and wastewater utilities provide the foundations for their communities so they can focus on growing and improving. But to remain (or become) sustainable, utilities must themselves grow and improve, and they can do so generally through two approaches: adaptation and resilience. If the wind blows harder, the reed can either adapt to bend more easily, or it can grow stronger and bury its roots deeper to resist breaking. Water systems are unique in that they can use both approaches at the same time, strengthening certain areas of management and operations, while others evolve in response to new perspectives and technologies. Highlighting areas of sustainable water management, this month's Journal AWWA has articles on resource management, source water protection, and the development of alternative supplies and partnerships. Partnerships and collaboration can further a utility's sustainability goals. Our cover story focuses on one example of this—when Des Moines Water Works faced significant source water quality challenges, its utility staff adapted by collaborating with a range of organizations to better protect its water supplies and ultimately its customers. Another article shows how improving water reliability in Washington's South Puget Sound helped aquatic species and increased community water resilience; the complex financial and permitting issues related to a fish passage facility and an additional water supply project were ultimately overcome by collaborating with like-minded organizations to build widespread support. Focusing more on novel technologies and approaches, another story this month shows how utilities can protect their customers and water distribution system operations by using the US Environmental Protection Agency's EPANET program to model water age. The model results can help utilities adapt how they design, operate, and optimize their distribution systems. The final feature in this month's issue describes how utilities need advanced technologies and new analytical approaches to develop alternative water supplies. As more utilities incorporate reverse osmosis in their treatment processes, advanced membrane forensics can identify the causes of membrane fouling, assess membrane condition, and determine ways to optimize the system to improve resilience and save money. This issue demonstrates how the principles of sustainable water are reflected in practice around the industry. But as all these examples show, water systems have a never-ending responsibility to their communities, and continuity and dedication are necessary to make them sustainable now and in the future. Taking a holistic approach by collaborating across an entire community benefits everyone. Join in the collaboration and share your innovative projects or sustainable approaches. Consider writing an article for Journal AWWA by contacting me at journaleditor@awwa.org.

Computational Tools for Supporting the Operation and Management of Water Distribution Systems towards Digital Transformation

This paper presents a set of computational tools specially developed for supporting the operation and management of water distribution systems towards digital transformation of water services. These tools were developed in the scope of two R&D projects carried out in Portugal, DECIdE and WISDom, during 2018–2022. The DECIdE project focused on the development of tools for importing cadastral and operational data, as well as on the three operational tools for supporting the performance assessment: the first allows the calculation of different key performance indicators, both at a global and sectorial level, which is an annual requirement of the water regulator, and the other two allow the calculation of the water and the energy balances and a set of complementary indices. The WISDom project aimed at the implementation of applications that directly address specific water utility needs, namely, the flow rate data processing, the optimal location of pressure sensors, the identification of critical areas in the distribution network for pipe burst location, and the prioritization of pipes for rehabilitation. Implemented tools are useful to support water utilities in the daily operation and management of their systems, being a step forward towards digital transformation of the water sector.

METHOD FOR CALCULATION OF DISPERSIONS OF DEPENDENT VARIABLES OF A STOCHASTIC MODEL OF QUASI-STATIONARY OPERATING MODES OF THE MAIN WATER PIPELINE

The subject of research in the article is a stochastic model of quasi-stationary modes of operation of water supply and distribution systems, which adequately describes the actual operating modes of the water supply system for a given time interval and can be used as a basic model for setting and solving problems of optimal stochastic control of the development and operation of supply and distribution systems. water. The goal of the work is to develop a method for calculating estimates of the dispersions of dependent variables depending on the given values of mathematical expectations and dispersions of independent variables for a stochastic model of quasi-stationary modes of operation of the main water conduit as a subsystem of the water supply and distribution system. To achieve this goal, it is necessary to solve the following tasks: to build a deterministic equivalent of a stochastic model of quasi-stationary modes of operation of the main water conduit; calculate estimates of mathematical expectations of dependent variables; calculate estimates of variances of dependent variables. To calculate estimates of the variances of dependent variables depending on the variances of independent variables, we will use the method of statistical linearization. To obtain estimates of mathematical expectations of dependent variables, the deterministic equivalent of the stochastic model of quasi-stationary modes of operation of the main water conduit is solved by the modified Newton method. The following results are obtained: a method for calculating estimates of the dispersions of dependent variables for a stochastic model of quasi-stationary modes of operation of the main water conduit. Conclusions: the paper proposes an approximate method for calculating the statistical properties of dependent variables depending on the statistical properties of the parameters and independent variables of the stochastic model of quasi-stationary modes of operation of the main water conduit. The proposed method is based on the construction of a deterministic equivalent of a stochastic model of quasi-stationary modes of operation of the main water conduit and its use for calculating estimates of variances of dependent variables depending on the given values of mathematical expectations and variances of independent variables. Compared with the simulation method, the proposed approximate method does not require significant time and computational resources. The use of the proposed method was demonstrated by an example.

A Review of Sources of Uncertainty in Optimization Objectives of Water Distribution Systems

Many studies have applied optimization to the planning, design, rehabilitation or operation of water distribution systems. Recent reviews of the research literature in this area have identified hundreds of papers that address these topics. The objectives considered include variables measuring direct impact of the system such as cost, energy, greenhouse gas emissions, as well as performance variables such as pressure deficit and system reliability. Very few of these studies have considered the effects of the various sources of uncertainty on the objectives considered. The sources of uncertainty include model related uncertainty such as uncertainty in model structure and parameters (e.g., pipe roughness and chemical reaction rates for water quality studies), data related uncertainty such as uncertainty in water demand due to natural variability in the short-term or population growth and/or climate change in the long-term, and human related uncertainty such as lack of knowledge about the physical network as well as modelling errors. This paper is aimed at reviewing the relative importance of these various sources of uncertainty on the key optimization objectives. It also summarizes the key literature in this area and identifies areas where there have been few publications.

Review of hydraulic modelling approaches for intermittent water supply systems

Abstract Intermittent water supply (IWS) is widely used around the world, and with the increase in population and predicted future water scarcity, IWS applications seem to continue. While most of the existing studies on water supply concentrate on continuous water supply (CWS), the research focused on the IWS is now becoming mainstream. Hydraulic modelling is an effective tool for the process of planning, design, rehabilitation, and operation of water distribution systems. It helps significantly in engineers’ decision-making processes. The necessity of modelling IWS systems arises from the complexity and variety of problems caused by intermittency. This paper offers a review of the state-of-the-art IWS modelling and identifies the key strengths and limitations of the available approaches, and points at potential research directions. Currently, neither computer software nor a practically used approach is available for modelling IWS. For a rigorous simulation of IWS, system characteristics first need to be understood, i.e., the user behaviour under pressure-deficient conditions, water losses, and filling and emptying processes. Each of them requires further attention and improvement. Additionally, the necessity of real data from IWSs is stressed. Accurate modelling will lead to the development of improved measures for the problems caused by intermittency.

Hydraulic and Water Quality Reliability of Water Distribution System under Uncertain Conditions

Reliability assessment plays a significant role in the planning, design, and operation of water distribution systems (WDS). Herein, pressure, flow, chlorine concentration, and water age are simulated by continuity, energy, and transport equations; and hydraulic, water quality, and system reliability assessments are proposed based on a comparison between simulated hydraulic and water quality conditions and the desired service level. Because the independent parameters in hydraulic and water quality simulations cannot be estimated accurately, a hydraulic and water quality reliability assessment based on Monte Carlo simulation was applied to a network under three uncertain levels under steady- and unsteady-states. The effects of uncertain parameters on hydraulic and water quality reliability under steady- and unsteady-states were evaluated and compared to obtain the most significant parameters. The results indicated that the mean hydraulic reliability decreases with an increase in the uncertainty level for various nodes under steady- and unsteady-states, while the regulation is not suitable for water quality reliability. Pipe diameters have the most significant effects on hydraulic reliability under steady-state conditions, and mean hydraulic reliability under unsteady-state conditions. Nodal demand, bulk decay coefficient, and wall decay coefficient have effects on water quality reliability under steady-state conditions, while the roughness coefficient and pipe diameter also have effects on mean water quality reliability under unsteady-state condition. The results obtained can give managers more information about network reliability under uncertain conditions.

Resilience Analytics for Interdependent Power and Water Distribution Systems

The occurrence of large-scale outages in power distribution systems (PDSs) caused, for instance, by extreme weather events has raised concerns on the cascading impact of the power outages on the resilience of other critical infrastructures, including water distribution systems (WDSs), whose healthy operation highly relies on the availability of power from PDSs. This paper proposes an analytics model for quantifying the interdependence between the resilience of power and water distribution systems. The proposed model first performs spatio-temporal outage analysis on the PDS and WDS to determine the PDS power serving capability and the resulting cascading impact on the WDS water serving capability during the occurrence of disruptions. The resilience interdependence is then determined by a proposed set of six metrics calculated using the power and water serving capability profiles, which trace and quantify the cascading impacts of power outages in the operation of WDSs during the degradation and recovery stages. The proposed analytics model is implemented on the IEEE 33-bus power distribution system supplying power for pumping stations of a 15-node test WDS, considering multiple cases of water storage capacity, single and multiple outage scenarios, and availability of distributed generation. The numerical results demonstrate that the proposed metrics track the temporal and spatial interdependence between the resilience of power and water distribution systems, providing a mechanism to identify weak spots, and assess options to enhance the resilience of the critical water infrastructure.

Novel approach for burst detection in water distribution systems based on graph neural networks

Sustainable management of water resources is a key challenge for the well-being and security of current and future society worldwide. In this regard, water utilities have to ensure fresh water for all users in a demand scenario stressed by climate change along with the increase in the size of cities. Dealing with anomalies, such as leakages and pipe bursts, represents one of the major issues for efficient water distribution system (WDS) operation and management. To this end, it is crucial to count on suitable methods and technologies to provide a quick, reliable, and accurate detection of such anomalies and supply disruption events. Therefore, this work proposes a novel WDS management framework based on the development of graph convolutional neural networks (GCN) models for bursts detection in WDSs. These methods rely on a WDS graph representation for a set of pressure and flow rates measures. Such a graph is used to design two GCN-based models to identify bursts. In addition, two conventional multi-layer perceptron models are used as the benchmarks to compare the graph-based methodologies. Finally, the proposed methodology is tested on a water utility network, showing the high potential of graph convolutional networks for anomaly detection on WDSs.