Spatial Aggregation Effect on Water Demand Peak Factor

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 2019
Author(s):  
Giuseppe Del Giudice ◽  
Cristiana Di Cristo ◽  
Roberta Padulano
Keyword(s):  
Water Demand ◽  
Distribution Systems ◽  
Water Distribution ◽  
Expected Value ◽  
Spatial Aggregation ◽  
Confidence Bands ◽  
Empirical Estimation ◽  
Peak Factor ◽  
Aggregation Effect ◽  
Time Aggregation

A methodological framework for the estimation of the expected value of hourly peak water demand factor and its dependence on the spatial aggregation level is presented. The proposed methodology is based on the analysis of volumetric water meter measurements with a 1-h time aggregation, preferred by water companies for monitoring purposes. Using a peculiar sampling design, both a theoretical and an empirical estimation of the expected value of the peak factor and of the related standard error (confidence bands) are obtained as a function of the number of aggregated households (or equivalently of the number of users). The proposed methodology accounts for the cross-correlation among consumption time series describing local water demand behaviours. The effects of considering a finite population is also discussed. The framework is tested on a pilot District Metering Area with more than 1000 households equipped with a telemetry system with 1-h time aggregation. Results show that the peak factor can be expressed as a power function tending to an asymptotic value greater than one for the increasing number of aggregated households. The obtained peak values, compared with several literature studies, provide useful indications for the design and management of secondary branched pipes of water distribution systems.

scholarly journals Hydraulic Performance Analysis and Modeling of Water Supply Distribution System of Addis Ababa Science and Technology University, Ethiopia

2020 ◽  
Author(s):  
Chalchisa Milkecha ◽  
Habtamu Itefa
Keyword(s):  
Water Supply ◽  
Water Demand ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Addis Ababa ◽  
Science And Technology ◽  
Hydraulic Performance ◽  
Alternative Methods ◽  
The University

This study was conducted generally by aiming assessment of the hydraulic performance of water distribution systems of Addis Ababa Science and Technology University (AASTU). In line with the main objective, this study addressed, (1) pinpointing problems of existing water supply versus demand deficit (2) evaluating the hydraulic performance of water distribution system using water GEMS and (3) recommended alternative methods for improving water demand scenarios. The University’s water supply distribution network layout was a looped system and the flow of water derived by both gravity and pressurized system. The gravity flow served for the academic and administrative staffs whereas the pressurized system of the network fed the students dormitories, cafeteria’s etc. The study revealed the existence of unmet minimum pressure requirement around the student dormitories which accounts 25.64% below the country’s building code standard during the peak hour consumption. The result of the water demand projection showed an increment of 2.5 liter per capita demand (LPCD) in every five years. Hence, first, the university’s water demand was projected and then hydraulic parameters such as; pressure, head loss and velocity were modeled for both the existing and the improved water supply distribution. The finding of the study was recommended to the university’s water supply project and institutional development offices for its future modification and rehabilitation works.

scholarly journals Real-Time Burst Detection in District Metering Areas in Water Distribution System Based on Patterns of Water Demand with Supervised Learning

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1765 ◽  
Author(s):  
Pingjie Huang ◽  
Naifu Zhu ◽  
Dibo Hou ◽  
Jinyu Chen ◽  
Yao Xiao ◽  
...  
Keyword(s):  
Supervised Learning ◽  
Water Demand ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Time Window ◽  
Learning Algorithm ◽  
Burst Detection ◽  
Pipe Burst ◽  
Dynamic Time

This paper proposes a new method to detect bursts in District Metering Areas (DMAs) in water distribution systems. The methodology is divided into three steps. Firstly, Dynamic Time Warping was applied to study the similarity of daily water demand, extract different patterns of water demand, and remove abnormal patterns. In the second stage, according to different water demand patterns, a supervised learning algorithm was adopted for burst detection, which established a leakage identification model for each period of time, respectively, using a sliding time window. Finally, the detection process was performed by calculating the abnormal probability of flow during a certain period by the model and identifying whether a burst occurred according to the set threshold. The method was validated on a case study involving a DMA with engineered pipe-burst events. The results obtained demonstrate that the proposed method can effectively detect bursts, with a low false-alarm rate and high accuracy.

Adaptable urban water demand prediction system

2015 ◽  
Vol 15 (5) ◽  
pp. 958-964 ◽  
Author(s):  
G. Banjac ◽  
M. Vašak ◽  
M. Baotić
Keyword(s):  
Mutual Information ◽  
Water Demand ◽  
Distribution Systems ◽  
Water Distribution ◽  
Meteorological Data ◽  
Model Parameters ◽  
Prediction System ◽  
Prediction Ability ◽  
Demand Prediction ◽  
Water Demand Prediction

In this work, identification of 24-hours-ahead water demand prediction model based on historical water demand data is considered. As part of the identification procedure, the input variable selection algorithm based on partial mutual information is implemented. It is shown that meteorological data on a daily basis are not relevant for the water demand prediction in the sense of partial mutual information for the analysed water distribution systems of the cities of Tavira, Algarve, Portugal and Evanton East, Scotland, UK. Water demand prediction system is modelled using artificial neural networks, which offer a great potential for the identification of complex dynamic systems. The adaptive tuning procedure of model parameters is also developed in order to enable the model to adapt to changes in the system. A significant improvement of the prediction ability of such a model in relation to the model with fixed parameters is shown when a certain trend is present in the water demand profile.

scholarly journals Multivariate statistical analysis for water demand modelling: implementation, performance analysis, and comparison with the PRP model

2015 ◽  
Vol 18 (1) ◽  
pp. 4-22 ◽  
Author(s):  
Chiara M. Fontanazza ◽  
Vincenza Notaro ◽  
Valeria Puleo ◽  
Gabriele Freni
Keyword(s):  
Statistical Analysis ◽  
Return Period ◽  
Water Demand ◽  
Distribution Systems ◽  
Water Distribution ◽  
Distribution Network ◽  
Water Distribution Network ◽  
Water Volume ◽  
Demand Model ◽  
Consumption Data

Water demand is the driving force behind hydraulic dynamics in water distribution systems. Consequently, it is crucial to accurately estimate the actual water use to develop reliable simulation models. In this study, copula-based multivariate analysis was proposed and used for demand prediction for a given return period. The analysis was applied to water consumption data collected in the water distribution network of Palermo (Italy). The approach produced consistent demand patterns and could be a powerful tool when coupled with water distribution network models for design or analysis problems. The results were compared with those obtained using a classical water demand model, the Poisson rectangular pulse (PRP) model. The multivariate consumption data statistical analysis results were always higher than those of the PRP model but the copula-based method maintained the daily water volume of actual consumptions and provided maximum daily consumption that increased with the return period.

Assessment of real losses in potable water distribution systems: some recent developments

2005 ◽  
Vol 5 (1) ◽  
pp. 33-40 ◽  
Author(s):  
R. McKenzie ◽  
C. Seago
Keyword(s):  
Water Demand ◽  
Distribution Systems ◽  
Water Distribution ◽  
Potable Water ◽  
Demand Management ◽  
Water Distribution Systems ◽  
Water Demand Management ◽  
Local Conditions ◽  
The World ◽  
Real Losses

Considerable progress has been made over the past 10 years in the assessment and benchmarking of real losses in potable water distribution systems. Most of the advances have been based on the burst and background estimate (BABE) methodology, which was first developed in the mid-1990s by the UK water industry and has since been widely accepted and used in many parts of the world. Since the original BABE methodology was developed, several other key concepts have been added to the evergrowing list of water demand management tools. In particular, the infrastructure leakage index (ILI) and unavoidable annual real losses (UARL) introduced by A. Lambert, and the fixed area variable area discharge (FAVAD) theory by J. May, are now recognised as key “tools of the trade” in any water demand management assessment. One of the first main developments where the above-mentioned concepts were applied in practice to benchmark leakage was in South Africa, where the local Water Research Commission supported the production of the BENCHLEAK Model. This was basically the first comprehensive model to assess real losses in potable water distribution systems using the UARL and ILI concepts. The model was developed by one of the authors together with A. Lambert, and was soon followed by similar developments in Australia (BENCHLOSS) and New Zealand (BENCHLOSSNZ). Both models incorporated additions and enhancements to the original South African model, and were tailored to suit the local conditions in line with the clients' requirements. Similar developments took place in parallel by various leakage specialists, most notably in Brazil, Malaysia and Cyprus, to mention just a few of the similar initiatives. Each time a new model was developed, certain improvements were made and the “science” of leakage management and benchmarking was enhanced. Through the use of the different models and from discussions with various researchers from around the world, it has become clear that there is a genuine need for such models, and they are being readily accepted by clients in most areas. The discussions have also raised many questions concerning the derivation of the terms used to calculate the UARL and the ILI, and, to address these concerns a specialist group was created through the IWA to investigate the various issues. This paper will highlight the progress that has been made to date with regard to the key issues that have been raised by the task-team members, and recommendations based on the feedback that has been received from around the world. The paper will also present some of the results that have been obtained from different parts of the world to highlight both the progress and the problems associated with the assessment of real losses. The paper will conclude with a short description of several new models that have been developed and are in use, which demonstrate the latest improvements to an ongoing process to assess and benchmark real losses in water distribution systems.

scholarly journals Correlation Analysis of Water Demand and Predictive Variables for Short-Term Forecasting Models

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
B. M. Brentan ◽  
G. Meirelles ◽  
M. Herrera ◽  
E. Luvizotto ◽  
J. Izquierdo
Keyword(s):  
Water Demand ◽  
Distribution Systems ◽  
Water Distribution ◽  
Demand Forecasting ◽  
Principal Component ◽  
Correlation Study ◽  
Self Organizing Maps ◽  
Water Demand Forecasting ◽  
Predictive Variables ◽  
Short Term Forecasting

Operational and economic aspects of water distribution make water demand forecasting paramount for water distribution systems (WDSs) management. However, water demand introduces high levels of uncertainty in WDS hydraulic models. As a result, there is growing interest in developing accurate methodologies for water demand forecasting. Several mathematical models can serve this purpose. One crucial aspect is the use of suitable predictive variables. The most used predictive variables involve weather and social aspects. To improve the interrelation knowledge between water demand and various predictive variables, this study applies three algorithms, namely, classical Principal Component Analysis (PCA) and machine learning powerful algorithms such as Self-Organizing Maps (SOMs) and Random Forest (RF). We show that these last algorithms help corroborate the results found by PCA, while they are able to unveil hidden features for PCA, due to their ability to cope with nonlinearities. This paper presents a correlation study of three district metered areas (DMAs) from Franca, a Brazilian city, exploring weather and social variables to improve the knowledge of residential demand for water. For the three DMAs, temperature, relative humidity, and hour of the day appear to be the most important predictive variables to build an accurate regression model.

scholarly journals Models for forecasting water demand using time series analysis: a case study in Southern Brazil

2021 ◽  
Author(s):  
Danielle C. M. Ristow ◽  
Elisa Henning ◽  
Andreza Kalbusch ◽  
Cesar E. Petersen
Keyword(s):  
Time Series ◽  
Water Consumption ◽  
Water Demand ◽  
Web Application ◽  
Water Resource Management ◽  
Distribution Systems ◽  
Water Distribution ◽  
Demand Forecasting ◽  
Model Quality

Abstract Technology has been increasingly applied in search for excellence in water resource management. Tools such as demand-forecasting models provide information for utility companies to make operational, tactical and strategic decisions. Also, the performance of water distribution systems can be improved by anticipating consumption values. This work aimed to develop models to conduct monthly urban water demand forecasts by analyzing time series, and adjusting and testing forecast models by consumption category, which can be applied to any location. Open language R was used, with automatic procedures for selection, adjustment, model quality assessment and forecasts. The case study was conducted in the city of Joinville, with water consumption forecasts for the first semester of 2018. The results showed that the seasonal ARIMA method proved to be more adequate to predict water consumption in four out of five categories, with mean absolute percentage errors varying from 1.19 to 15.74%. In addition, a web application to conduct water consumption forecasts was developed.

Stochastic simulation model of water demand in residential buildings

2019 ◽  
Vol 41 (5) ◽  
pp. 544-560
Author(s):  
Tiago de VG Ferreira ◽  
Orestes M Goncalves
Keyword(s):  
Flow Rate ◽  
Water Consumption ◽  
Water Demand ◽  
Distribution Systems ◽  
Water Distribution ◽  
Residential Buildings ◽  
Water Distribution Systems ◽  
Simulation Models ◽  
System Components ◽  
Stochastic Simulation Model

Over the years, researchers have been conducting studies to investigate the water consumption profile in buildings; these studies have contributed to the accumulation of knowledge regarding the correct sizing of hydraulic systems in buildings. In the context of the methods for the characterization of system demand or loading values, the procedures commonly employed to obtain the project flow rate were primarily proposed in the mid-20th century. These models require revision and adaptation to the current water consumption values. In recent years, certain researchers have proposed simulation models with an application focus on water distribution systems owing to the random and temporal behavior of water demand in this system type. In this study, a water-demand stochastic simulation model in residential buildings is proposed, which encompasses the behavioral modelling of users and their interaction with the system to improve the design process of water distribution systems. Therefore, geographical and population factors (quantity, distribution, and organization) were considered for the behavioral modelling of users; regarding the system modelling, aspects related to the hydraulic system were considered, such as the relation between system components, the type of sanitary appliance, and the number of available devices. Different simulations—with several different types of showers—were conducted using the proposed model. Comparing the flows obtained from the simulation and from the Brazilian standard, for all system components, the decrease in the project flow rate varied from 4% to 61%. In terms of material consumption regarding the pipe (PVC), the decrease varied from 25% to 63%. Practical application: When assessing potential designs for components in water distribution systems in buildings robust information is required for water demand across different time scales. The use of simulation models represents an important advance for the dimensioning process of these components, since it is possible to know a wider range of information about the system demand possibilities. The use of this type of model, as discussed in this article, will equip the designer with an enhanced decision making capacity.

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