Optimal operation of a potable water distribution network

Biscos, C; Mulholland, M.; Lann, M.V. Le; Brouckaert, C.J.; Bailey, Ryan T.; Roustan, M.

doi:10.2166/wst.2002.0228

Cited by 16 publications

(10 citation statements)

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“…The third optimisation model minimises disinfectant concentration deviations at customer demand nodes from desired values (Goldman et al 2004;Kang and Lansey 2009;Munavalli and Kumar 2003;Propato and Uber 2004a;Propato and Uber 2004b;Sakarya and Mays 1999;Sakarya and Mays 2000;Sakarya and Mays 2003). These models are sometimes combined in various ways (Biscos et al 2003;Biscos et al 2002;Gibbs et al 2010a;Ostfeld and Salomons 2006).…”

Section: Urban Drinking Water Distribution Systemsmentioning

confidence: 99%

Lost in optimisation of water distribution systems? A literature review of system operation

Mala-Jetmarova

Sultanova

Savić

2017

Environmental Modelling & Software

237

114

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Optimisation of the operation of water distribution systems has been an active research field for almost half a century. It has focused mainly on optimal pump operation to minimise pumping costs and optimal water quality management to ensure that standards at customer nodes are met. This paper provides a systematic review by bringing together over two hundred publications from the past three decades, which are relevant to operational optimisation of water distribution systems, particularly optimal pump operation, valve control and system operation for water quality purposes of both urban drinking and regional multiquality water distribution systems. Uniquely, it also contains substantial and thorough information for over one hundred publications in a tabular form, which lists optimisation models inclusive of objectives, constraints, decision variables, solution methodologies used and other details. Research challenges in terms of simulation models, optimisation model formulation, selection of optimisation method and postprocessing needs have also been identified.

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Section: Urban Drinking Water Distribution Systemsmentioning

confidence: 99%

Lost in optimisation of water distribution systems? A literature review of system operation

Mala-Jetmarova

Sultanova

Savić

2017

Environmental Modelling & Software

237

114

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“…Biscos et al [98] used a predictive control framework coupled with mixed integer non-linear programming (MINLP) for minimizing the costs of pump operation. Biscos et al [99] extended [98] to include the minimization of chlorine dosage.…”

Section: Predictive Controlmentioning

confidence: 99%

Water Distribution Networks

Ostfeld

2014

Studies in Computational Intelligence

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A water distribution system is a complex assembly of hydraulic control elements connected together to convey quantities of water from sources to consumers. The typical high number of constraints and decision variables, the nonlinearity, and the non-smoothness of the head-flow-water quality governing equations are inherent to water supply systems planning and management problems. Traditional methods for solving water distribution systems management problems, such as the least cost design and operation problem, utilized linear/ nonlinear optimization schemes which were limited by the system size, the number of constraints, and the number of loading conditions. More recent methodologies employ heuristic optimization techniques, such as genetic algorithms or ant colony optimization as stand alone or hybrid data driven-heuristic schemes. This book chapter reviews some of the more traditional water distribution systems problem algorithms and solution methodologies. It is comprised of sub sections on least cost and multi-objective optimal design of water networks, reliability incorporation in water supply systems design, optimal operation of water networks, water quality analysis inclusion in distribution systems, water networks security related topics, and a look into the future.

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“…This calculated flows strategy, based on friction losses and available heads, gave a detailed pressure-balanced solution which was found to be unnecessary. The details of this approach are published in Biscos et al (2002). By observing typical operating sequences on the system, it was realised that the key issue was the sequencing of pumps located on the network trunk.…”

Section: Standard Element Used In the Minlp Optimisationmentioning

confidence: 99%

“…In general, the major empirical guideline for a good MINLP formulation is to keep the problem as linear as possible. The approach based on pressure balances was strongly non-linear (Biscos et al, 2002), so an obvious advantage was obtained in moving to the available flow model.…”

Section: The Mixed Integer Non-linear Programming Optimisationmentioning

confidence: 99%

Optimal operation of water distribution networks by predictive control using MINLP

Biscos¹,

Mulholland²,

Lann³

et al. 2004

WSA

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This paper presents an approach for the operational optimisation of potable water distribution networks. The maximisation of the use of low-cost power (e.g. overnight pumping) and the maintenance of a target chlorine concentration at final delivery points were defined as important optimisation objectives. The first objective is constrained by the maintenance of minimum emergency volumes in all reservoirs, while the second objective would include the minimisation of chlorine dosage and re-dosage requirements. The combination of dynamic elements (e.g. reservoirs) and discrete elements (pumps, valves, routing) makes this a challenging predictive control and constrained optimisation problem, which is being solved by MINLP (Mixed Integer Non-linear Programming). Initial experimental results show the performance of this algorithm and its ability to control the water distribution process.

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Optimal operation of a potable water distribution network

Cited by 16 publications

References 0 publications

Lost in optimisation of water distribution systems? A literature review of system operation

Lost in optimisation of water distribution systems? A literature review of system operation

Water Distribution Networks

Optimal operation of water distribution networks by predictive control using MINLP

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