Comparison of demand pattern calibration in water distribution networks with geographic and non-geographic parameterization

Demands are one of the most uncertain parameters in water distribution network models. A good calibration of the model demands leads to better results when using the model for any purpose. A demand pattern calibration methodology that uses a priori information has been developed for calibrating the behavior of demand groups. In cities, similar demand behaviors are distributed all over the network, contrary to smaller villages where demands are clearly sectorised in residential neighborhoods, commercial zones and industrial sectors. In this work, demand pattern calibration has a final use for leakage detection and isolation. Detecting a leakage in a pattern that covers nodes spread all over the network makes the isolation unfeasible. Besides, demands in the same zone may be more similar due to the common pressure of the area rather than for the type of contract. A demand pattern calibration methodology is applied to a real network with synthetic non-geographic demands for calibrating geographic demand patterns. The results are compared with a previous work where the calibrated patterns were the original non-geographic onesPeer ReviewedPostprint (published version

Comparison of demand calibration in water distribution networks using pressure and flow sensors

Water distribution network models are used by water companies in a wide range of applications. A good calibration of these models is required in order to improve the confidence of the application results. Pressure and flow measurements are the main source of information when calibrating a hydraulic model. The selection of both the type and location of the sensors is crucial to guarantee a good calibration. This paper describes a sensor placement methodology based on the analysis of pressure and flow sensitivity using the Singular Value Decomposition. A comparison of demand calibration in a real network with synthetic data is presented. Three sets of sensors are considered: pressure sensors, flow sensors, and a combination of both.Peer ReviewedPostprint (author's final draft

Benchmark de control y superivisión de redes de distribución de aguas

La disponibilidad de agua potable es posible gracias a las infraestructuras construidas que conforman las redes de distribución. Las compañías de agua son las encargadas de mantener estas redes en buen estado, así como asegurar unas condiciones de calidad y presion en el consumidor final. Estas condiciones se verifican mediante medidas realizadas en los sensores de la red. Si se dispone del modelo de la red de distribución de agua, estas medidas pueden utilizarse tambien para su calibración, así como en metodologías de detección de fugas [3], control de la calidad del agua [2], etc. Estas metodologías se desarrollan en lenguaje Matlab, combinadas con otros entornos que permiten la simulación de redes hidraulicas, como EPANET [4]. Este trabajo presenta una interfaz gráfica que combina ambas herramientas, permitiendo su interconexión y facilitando la aplicación por parte del usuario de funciones ya existentes, a la vez que permite incorporar nuevos módulos personalizados.Peer ReviewedPostprint (published version

Leak detection and localization through demand components calibration

Success in the application of any model-based methodology (e.g., design, control, supervision) highly depends on the availability of a well-calibrated model. The calibration of water distribution networks needs to be performed online due to the continuous evolution of demands. During the calibration process, background leakages or bursts can be unintentionally incorporated to the demand model and treated as a system evolution (change in demands). This work proposes a leak-detection and localization approach to be coupled with a calibration methodology that identifies geographically distributed parameters. The approach proposed consists in comparing the calibrated parameters with their historical values to assess if changes in these parameters are caused by a system evolution or by the effect of leakage. The geographical distribution allows unexpected behavior of the calibrated parameters (e.g., abrupt changes, trends, etc.) to be associated with a specific zone in the network. The performance of the methodology proposed is tested on a real water distribution network using synthetic data. Tested scenarios include leaks occurring at different locations and ranging from 2.5 to 13% of the total consumption. Leakage is represented as pressure-dependent demand simulated as emitter flows at the network nodes. Results show that even considering a low number of sensors, leaks with an effect on parameters higher than the parameters’ uncertainty can be correctly detected and located within 200 m.Peer ReviewedPostprint (author's final draft

Model calibration and leakage assessment applied to a real Water Distribution Network

The use of water distribution network models depends highly on the confidence that the operators have on them. Models generated automatically from the Geographical Information System using the hydraulic equations integrated in a simulation model [7] are available in most of the water utilities. Once the first simulation results are compared with the available measurements, calibration is required [6]. This paper presents the process of adjusting the original network model of a village called Sant Joan de Vilatorrada network to fit the simulation results with the measurements. The adjustments in the model range from the macroalibration level to the microcalibration level [3]. The macrocalibration process is based on the analysis done by the engineers, and the conclusions are formalised for future use in other networks. Microcalibration is centred in setting the emitter coefficients using Genetic Algorithm optimisation. The results of the work include an adjusted model for decision taking, an assessment of the background leakage and a methodology to be applied in other parts of the network.Peer ReviewedPostprint (published version

Parameter uncertainty modelling in water distribution network models

The use of water distribution network (WDN) models is an extended practice [13]. Confidence on decisions taken upon such models depends highly on their accuracy [11]. The parameters uncertainty has to be defined in order to include it in the model. Some of the parameters in a network (e.g. pipes lengths and diameters) can be easily measured and their uncertainty can be calculated on a statistical basis [4]. Demands cannot be measured directly and they have to be estimated using other measurements [10][8]. The uncertainty in the measurements used for that estimation is propagated to the parameters [1]. Besides, demands have their own stochastic nature that induces uncertainty. This paper describes how the pressure measurements are used to infer the uncertainty model in demands for a real network. The real data are treated in order to avoid the effect of boundary conditions. An uncertainty model for demands is calculated to justify the observed behaviour of the measurements. Montecarlo simulations are used for the validation.Peer ReviewedPostprint (published version

Demand modeling for water networks calibration and leak localization

The success in the application of any model-based methodology (e.g. design, control, supervision) highly depends on the availability of a well calibrated model. There is no best or unique solution for the calibration problem as the methodologies are developed depending on which parameters have to be calibrated and the final use of the model. The main objective in this thesis is to develop an adaptive water distribution network model which both calibrates its demands online and discerns between faults and system evolution. The calibration is focused on demands due to their daily variability and continuous evolution. The singular value decomposition is a powerful tool for solving the optimization problem. Additionally, the deep understanding of this tool allows to redefine the demand model. A novel demand model is proposed, where each individual demand is defined as a combination of demand components. These demand components are calibrated demand multipliers that represent the behavior of nodes in a determined geographical zone. The membership of each nodal demand to every demand component is produced naturally through the analysis of the singular value decomposition of the sensitivity matrix. The same analysis is also used to define the location of sensors for the calibration. The calibration in water distribution networks needs to be performed online due to the continuous evolution of demands. During the calibration process, background leakages or bursts can be unintentionally incorporated to the demand model and treated as a system evolution (change in demands). To solve that, a leak detection and localization approach to be coupled with the calibration methodology that identifies geographically distributed parameters is proposed. The approach consists in comparing the calibrated parameters with their historical values to assess if changes in these parameters are caused by a system evolution or by the effect of leakage. The geographical distribution allows to associate an unexpected behavior of the calibrated parameters (e.g. abrupt changes, trends, etc.) to a specific zone in the network. The set of methods proposed are exemplified through an academic dummy network to help the reader completely understand their fundamentals. Furthermore, three real water distribution networks situated in Barcelona and Castelldefels are used to evaluate the performance of the whole method with real systems and real data. The good results obtained show the potential of the developed method and the viability of the real-time calibration and leak detection and localization processes.L'èxit en l'aplicació de qualsevol metodologia basada en models (p. ex. disseny, control, supervisió) depèn, en gran part, de la disponibilitat d'un model ben calibrat. No hi ha una solució única o global per aquest problema, ja que les metodologies es desenvolupen en funció de l'ús final del model. L'objectiu principal d'aquesta tesi és desenvolupar un model adaptatiu per xarxes de distribució d'aigua que calibri les seves demandes de forma online mentre distingeix entre fallades i evolució del sistema. La calibració es centra en les demandes degut a la seva variabilitat diària i a la seva evolució continua. La descomposició en valors singulars és una eina molt potent per resoldre problemes d'optimització. Addicionalment, la comprensió detallada d'aquesta eina permet redefinir el model de demandes. Es proposa un model de demandes innovador, on cada demanda individual es defineix com una combinació de components de demanda. Aquests components de demanda són multiplicadors de demanda que han estat calibrats, i que representen el comportament dels nodes en una zona geográfica determinada. La pertinença de cada demanda nodal a cadascun dels components de demanda es produeix de forma natural mitjanant l'anàlisi de la descomposició en valors singulars de la matriu de sensibilitat. El mateix anàlisi també s'utilitza per definir la localització dels sensors per la calibració. La calibració en xarxes de distribució d'aigua s'ha de realitzar en línia, ja que les demandes evolucionen contínuament. Durant el procés de calibració, les fuites latents o espontànies poden ser incorporades involuntàriament al model de demanda, i ser tractades com una evolució del sistema (canvi en les demandes). Per solucionar-ho, es proposa un mètode de detecció i localització de fuites que s'acobla a la metodologia de calibració que identifica components de demanda geogràfics. El mètode proposat consisteix en comparar els paràmetres calibrats amb els seus valors històrics per valorar si els canvis en aquests paràmetres es deuen a una evolució del sistema, o a l'efecte de les fuites. La distribució geogràfica permet associar un comportament no esperat dels paràmetres calibrats (p. ex. canvis sobtats, tendències, etc.) a una zona específica de la xarxa. El conjunt de mètodes proposats s'ha exemplificat mitjanant una xarxa acadèmica molt simple per ajudar al lector a entendre completament els seus fonaments. A més a més, s'han utilitzat tres xarxes de distribució d'aigua situades a Barcelona i Castelldefels per avaluar el funcionament del mètode complet amb sistemes i dades reals. Els bons resultats obtinguts mostren el potencial de la metodologia desenvolupada i la viabilitat de la calibració de demandes i detecció i localització de fuites en temps real.Postprint (published version

Demand pattern calibration in water distribution networks

Water distribution network models are widely used by water companies. Consumer demands are one of the main uncertainties in these models, but their calibration is not feasible due to the low number of sensors available in most real networks. However, the behaviour of these individual demands can be also calibrated if some a priori information is available. A methodology for calibrating demand patterns based on singular value decomposition (SVD) is presented. Demand stochastic nature is overcome by using multiple data samples. The methodology is applied to two water distribution systems: an academic network and a real network with synthetic data.Postprint (published version

Teaching automatic control and modelling through a real application: water distribution networks

Vídeo elaboral per a l'International Congress of Education, Innovation and Learning Technologies 201

Modelling and simulation of drinking-water networks

This book presents a set of approaches for the real-time monitoring and control of drinking-water networks based on advanced information and communication technologies. It shows the reader how to achieve significant improvements in efficiency in terms of water use, energy consumption, water loss minimization, and water quality guarantees. The methods and approaches presented are illustrated and have been applied using real-life pilot demonstrations based on the drinking-water network in Barcelona, Spain. The proposed approaches and tools cover: • decision-making support for real-time optimal control of water transport networks, explaining how stochastic model predictive control algorithms that take explicit account of uncertainties associated with energy prices and real demand allow the main flow and pressure actuators—pumping stations and pressure regulation valves—and intermediate storage tanks to be operated to meet demand using the most sustainable types of source and with minimum electricity costs; • decision-making support for monitoring water balance and distribution network quality in real time, implementing fault detection and diagnosis techniques and using information from hundreds of flow, pressure, and water-quality sensors together with hydraulic and quality-parameter-evolution models to detect and locate leaks in the network, possible breaches in water quality, and failures in sensors and/or actuators; • consumer-demand prediction, based on smart metering techniques, producing detailed analyses and forecasts of consumption patterns, providing a customer communications service, and suggesting economic measures intended to promote more efficient use of water at the household level. Researchers and engineers working with drinking-water networks will find this a vital support in overcoming the problems associated with increased population, environmental sensitivities and regulation, aging infrastructures, energy requirements, and limited water sources.Peer ReviewedPostprint (published version