Optimizing DMAs' formation in a water pipe network: the water aging and the operating pressure factors

Chondronasios, Apostolos; Gonelas, Konstantinos; Kanakoudis, Vasilis; Patelis, Menelaos; Korkana, Panagiota

doi:10.2166/hydro.2017.156

Cited by 26 publications

(21 citation statements)

References 9 publications

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“…GAs are widely used for the optimization of water-related problems [28,[31][32][33]. This optimization technique searches for a solution with minimum costs given as the objective goal of the target problem [33]. Prasad et al (2003) presented a GA with multivariable functions for an optimal design of WDNs using a Pareto-optimal approach [34].…”

Section: Genetic Algorithmsmentioning

confidence: 99%

Energy Cost Optimization for Water Distribution Networks Using Demand Pattern and Storage Facilities

Chang¹,

Choi

Kim³

et al. 2018

Sustainability

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Energy consumption in water supply systems is closely connected with the demand for water, since energy is mostly consumed in the process of water transport and distribution, in addition to the energy that might be needed to pump the water from its sources. Existing studies have been carried out on optimizing the pump operations to attain appropriate pressure and on controlling the water level of storage facilities to transfer the required demand and to reduce the energy cost. The idea is to reduce the amount of the water being supplied when the unit price of energy is high and to increase the supply when the unit price is low. To realize this scheme, the energy consumption of water supply systems, the amount of water transfer, the organization of energy cost structure, the utilization of water tanks, and so forth are investigated and analyzed to establish a model of optimized water demand management based on the application of water tanks in supplied areas. In this study, with the assumption that energy cost can be reduced by the redistribution of a demand pattern, a numerical analysis is conducted on transferring water demand at storage facilities from the peak energy cost hours to the lower energy cost hours. This study was applied at the Bupyeong 2 reservoir catchment, Incheon, Korea.

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Section: Genetic Algorithmsmentioning

confidence: 99%

Energy Cost Optimization for Water Distribution Networks Using Demand Pattern and Storage Facilities

Chang¹,

Choi

Kim³

et al. 2018

Sustainability

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“…Water age differs between networks. A survey of more than 800 distribution networks in the USA showed an average water age of around 1.3 days and a maximum of three days (Shamsaei et al 2013;Chondronasios et al 2017). Kabir et al (2015a) defined and ranked water age ranges to evaluate its effect in a risk assessment model.…”

Section: Water Agementioning

confidence: 99%

A review of water quality factors in water main failure prediction models

Monfared

Nojumi

Bayat

2021

Water Practice and Technology

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Water main failure can result from structural failure of the pipes, changes in water quality, or a combination. This paper is a review of articles evaluating water quality factors and subfactors in the development of water main failure prediction models since 2000. A systematic process was implemented to capture the most relevant current published papers. Of 4598 published papers, 304 were screened for water main failure prediction models. The resulting set was further screened for water quality factors and subfactors (e.g., pH, temperature, etc.). This led to the identification of 18 relevant research papers, and each of these was reviewed comprehensively. The water quality-related findings, as well as combinations with other information – such as type of prediction model and type of prediction – are summarized and discussed.

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“…The investments after the year of 2015 have a significant role in these reductions. Dividing a WDS into district metered areas (DMAs) is important step and task that usually troubles water utility managers towards pressure management for reducing leakages (Chondronasios et al 2017;Creaco and Haidar 2019). Certain DMAs and pressure metered areas (PMAs) were installed in WDSs by taking hydraulic model results as a reference, especially starting from the districts with high water supply and water losses, in order to reduce water losses within the framework of the investments in question.…”

Section: Study Area and Data Descriptionmentioning

confidence: 99%

Non-revenue water ratio prediction with serial triple diagram model

Kizilöz

Şişman

2021

Water Supply

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Water administrations attempt to control the Non-Revenue Water Ratio (NRWR) values in sustainable and well-performing water distribution infrastructures. In this respect, the NRWR value prediction through appropriate models over a small number of controllable variables is significant. The collection, monitoring, and predictions of data on variables that are used in the NRWR calculations are not practical and required significant time besides financial resources. In this study, the NRWR predictions have been made through the suggested method over three parameters. The model prediction accuracies, in the literature obtained by using the Triple Diagram Model (TDM) over two parameters, have been increased through the Serial Triple Diagram Model (STDM) suggested in this study. This method shows that better predictions are possible in the NRWR modeling. Thanks to the model applications developed in this study, water administrations can make predictions with the least error (less than 10% relative error) and certain variables, according to the characteristics of each water distribution network.

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Optimizing DMAs' formation in a water pipe network: the water aging and the operating pressure factors

Cited by 26 publications

References 9 publications

Energy Cost Optimization for Water Distribution Networks Using Demand Pattern and Storage Facilities

Energy Cost Optimization for Water Distribution Networks Using Demand Pattern and Storage Facilities

A review of water quality factors in water main failure prediction models

Non-revenue water ratio prediction with serial triple diagram model

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