Aproximación estocástica al análisis de observabilidad en redes de abastecimiento de agua

Díaz, Sarai; Mı́nguez, Roberto; González, Javier

doi:10.4995/ia.2016.4625

Cited by 11 publications

(4 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Available data in water distribution systems typically include water demand pseudomeasurements (i.e. estimations from historical data) but also readings from metering devices (Díaz et al 2016b), which can in turn be associated with volumetric measurements every hour (e.g. volumetric smart meters at house connections) or high-frequency flow measurements (e.g.…”

Section: Introductionmentioning

confidence: 99%

Temporal Scale Effect Analysis for Water Supply Systems Monitoring Based on a Microcomponent Stochastic Demand Model

Díaz

González

2021

J. Water Resour. Plann. Manage.

Self Cite

View full text Add to dashboard Cite

Water demands are the main random factor that conditions flow variability within drinking water supply systems. The importance of using high-resolution demands in distribution mains is already well-known, but there is little knowledge of how the temporal scale (i.e. sampling frequency) affects the ability of a metering or monitoring system to explain network performance. The aim of this paper is to analyse the variability (i.e. information) that is lost because of not using a more frequent sampling rate to characterize water demands. For such purpose, a novel analytical approach based on a conceptualization of the microcomponent-based SIMDEUM model (SIMulation of water Demand, an End-Use Model) is presented. This methodology provides the statistical properties of water demands over different sampling frequencies. It is here applied to Benthuizen case study to 1 Díaz et al., December 15, 2021 further explore the effect of temporal and spatial scaling laws under realistic conditions. Results are of major importance for monitoring design, as they highlight the need for properly combining measurements with different levels of resolution. Moreover, they enable to assess the impact of the sampling selection on the potential characterization level of monitored demands within urban water modelling applications.

show abstract

Section: Introductionmentioning

confidence: 99%

Temporal Scale Effect Analysis for Water Supply Systems Monitoring Based on a Microcomponent Stochastic Demand Model

Díaz

González

2021

J. Water Resour. Plann. Manage.

Self Cite

View full text Add to dashboard Cite

show abstract

“…La explicación se centrará fundamentalmente en los valores medios, aunque la varianza de los histogramas también puede ser útil para caracterizar la incertidumbre de los micro-consumos. Esto puede resultar interesante en aplicaciones orientadas a identificar el estado hidráulico más probable en la red (Díaz et al, 2016), aunque este tema queda fuera del ámbito del presente trabajo.…”

Section: Resultsunclassified

Caracterización de micro-consumos domésticos de agua potable de acuerdo con la percepción de los participantes en una iniciativa de ciencia ciudadana: la experiencia del #50lWaterChallenge

2021

Self Cite

View full text Add to dashboard Cite

<p>Una buena caracterización de las demandas es esencial para modelizar correctamente el flujo y la calidad del agua en sistemas de abastecimiento, especialmente en las zonas terminales de la red. En la actualidad existen dos tipos de modelos estocásticos de demanda, que requieren una adecuada monitorización de viviendas o la realización de encuestas técnicas especializadas. El objetivo de este trabajo es recopilar información orientativa para la puesta en marcha de modelos basados en usos finales mediante la percepción de consumo de los participantes en una experiencia de ciencia ciudadana. Se trata de una sencilla encuesta on-line con motivo del reto #50lWaterChallenge en redes sociales, que recoge información sobre los micro-consumos de agua en las viviendas de forma individual. Los datos recabados son filtrados en dos etapas y los resultados obtenidos se ajustan en general bien a las referencias existentes en la literatura científica. Además, parecen captar las particularidades asociadas a la situación de confinamiento debida a la coyuntura por COVID-19 en España, probando que este tipo de iniciativas pueden ser herramientas ágiles y útiles para caracterizar (o al menos aproximar) el consumo de agua urbana.</p>

show abstract

“…The authors presented a new methodology for sensor placement and uncertainty evaluation of various hydraulic variables. Combining the methods from Díaz et al [10] and the algebraic analysis for clustering presented by [13], a set of research has been presented for improving various needs of SE, such as sensitivity analysis [14], calibration of a WDS [15], SE in changing WDS topologies [16,17], and leak detection using SE [18].…”

Section: Introductionmentioning

confidence: 99%

A Digital Twin of a Water Distribution System by Using Graph Convolutional Networks for Pump Speed-Based State Estimation

Granados

Zanfei

Brentan

et al. 2022

Water

View full text Add to dashboard Cite

Water distribution system monitoring is currently carried out using advanced real-time control technologies to achieve a higher operational efficiency. Data analysis techniques can be implemented for condition estimation, which are crucial tools for managing, developing, and operating water networks using the monitored flow rate and pressure data at some network pipes and nodes. This work proposes a state estimation methodology that enables one to infer the hydraulic state of the operating speed of pumping systems from these pressure and flow measurements. The presented approach suggests using graph convolutional neural network theory linked to hydraulic models for generating a digital twin of the water system. It is validated on two benchmark hydraulic networks: the Patios-Villa del Rosario, Colombia, and the C-Town networks. The results show that the proposed model effectively predicts the state estimation in the two hydraulic networks used. The results of the evaluation metrics indicate low values of mean squared error and mean absolute error and high values of the coefficient of determination, reflecting high predictive ability and that the prediction results adequately represent the real data.

show abstract

Aproximación estocástica al análisis de observabilidad en redes de abastecimiento de agua

Cited by 11 publications

References 20 publications

Temporal Scale Effect Analysis for Water Supply Systems Monitoring Based on a Microcomponent Stochastic Demand Model

Temporal Scale Effect Analysis for Water Supply Systems Monitoring Based on a Microcomponent Stochastic Demand Model

Caracterización de micro-consumos domésticos de agua potable de acuerdo con la percepción de los participantes en una iniciativa de ciencia ciudadana: la experiencia del #50lWaterChallenge

A Digital Twin of a Water Distribution System by Using Graph Convolutional Networks for Pump Speed-Based State Estimation

Contact Info

Product

Resources

About