Optimization of Water Distribution Systems Using Online Retrained Metamodels

Bi, Weiwei; Dandy, Graeme C.

doi:10.1061/(asce)wr.1943-5452.0000419

Cited by 35 publications

(26 citation statements)

References 20 publications

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“…Basic water quality parameters that are used in optimisation models of drinking WDSs are chlorine [27,87,120,143] and chloramine [120], modelled as non-conservative applying first order decay kinetics, adjusted by a higher decay rate in parts of the system when needed [120]. In contrast, conservative water quality parameters are typically important for regional multiquality WDSs.…”

Section: Design For Water Qualitymentioning

confidence: 99%

“…In terms of optimisation models, single-objective as well as multi-objective exist which include water quality considerations. In the former, water quality related expenditures, such as the cost of disinfection [27,120], cost of water treatment [53] or cost of losses incurred by insufficient quality [129], are combined with the system design/capital (and operation) costs into one objective. Alternatively, water quality is included as a constraint to a single-objective model in a form of minimum (and maximum) disinfectant concentrations at the network nodes [87,143].…”

Section: Design For Water Qualitymentioning

confidence: 99%

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Lost in Optimisation of Water Distribution Systems? A Literature Review of System Design

Mala-Jetmarova

Sultanova

Savić

2018

Water

130

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Optimisation of water distribution system design is a well-established research field, which has been extremely productive since the end of the 1980s. Its primary focus is to minimise the cost of a proposed pipe network infrastructure. This paper reviews in a systematic manner articles published over the past three decades, which are relevant to the design of new water distribution systems, and the strengthening, expansion and rehabilitation of existing water distribution systems, inclusive of design timing, parameter uncertainty, water quality, and operational considerations. It identifies trends and limits in the field, and provides future research directions. Exclusively, this review paper also contains comprehensive information from over one hundred and twenty publications in a tabular form, including optimisation model formulations, solution methodologies used, and other important details.

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Section: Design For Water Qualitymentioning

confidence: 99%

Section: Design For Water Qualitymentioning

confidence: 99%

Lost in Optimisation of Water Distribution Systems? A Literature Review of System Design

Mala-Jetmarova

Sultanova

Savić

2018

Water

130

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“…In the last two decades, many researchers have shifted the focus of WDS optimization from traditional and deterministic techniques, based on linear and nonlinear programming, to the implementation of methods that were generally based on heuristics derived from nature [18,23]. In recent years, Evolutionary Computation has proven to be a powerful tool to solve optimal pump-scheduling problems [11].…”

Section: Literature Reviewmentioning

confidence: 99%

“…For instance, Perez-Sanchez and his colleagues, by using EPANET model of an irrigation system, showed that theoretically 188. 23 MWh/year energy-equivalent to 137.4 ton CO 2 /year-can be recovered from the Water 2017, 9, 640 2 of 18 system [6,7]. León-Celi, C et al also used EPANET toolkit and two optimization algorithms to find the optimum flowrate distribution in water systems with multiple pump stations and minimize energy usage and potential leakage [8].…”

Section: Introductionmentioning

confidence: 99%

PEPSO: Reducing Electricity Usage and Associated Pollution Emissions of Water Pumps

Miller

2017

Water

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Using metaheuristic optimization methods has enabled researchers to reduce the electricity consumption cost of small water distribution systems (WDSs). However, dealing with complicated WDSs and reducing their environmental footprint remains a challenge. In this study a multi-objective version of Pollution Emission Pump Station Optimization tool (PEPSO) is introduced that can reduce the electricity cost and pollution emissions (associated with the energy consumption) of pumps of WDSs. PEPSO includes a user-friendly graphical interface and a customized version of the non-dominated sorting genetic algorithm. A measure that is called "Undesirability Index" (UI) is defined to assist the search for a promising optimization path. The UI also ensures that the final results are desirable and practical. The various features of PEPSO are tested under six scenarios for optimizing the WDS of Monroe City, MI, and Richmond, UK. The test results indicate that in a reasonable amount of time, PEPSO can optimize and provide practical results for both WDSs.

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“…This approach was possibly outlined first by Nain and Deb (2005). A variety of enhancements to this general approach have been proposed, including different sampling strategies (Knowles, 2006), dynamic algorithm control (Gaspar- Cunha and Vieira, 2005), and online retraining (Bi and Dandy, 2013;Xu et al, 2014;Minsker, 2006, 2011).…”

Section: Current Statusmentioning

confidence: 99%

Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions

Maier

Kapelan

Kasprzyk

et al. 2014

Environmental Modelling & Software

521

317

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In all cases accepted manuscripts should:  link to the formal publication via its DOI  bear a CC-BY-NC-ND license -this is easy to do, click here to find out how  if aggregated with other manuscripts, for example in a repository or other site, be shared in alignment with our hosting policy  not be added to or enhanced in any way to appear more like, or to substitute for, the published journal article AbstractThe development and application of evolutionary algorithms (EAs) and other metaheuristics for the optimisation of water resources systems has been an active research field for over two decades. Research to date has emphasized algorithmic improvements and individual applications in specific areas (e.g., model calibration, water distribution systems, groundwater management, river-basin planning and management, etc.). However, there has been limited synthesis between shared problem traits, common EA challenges, and needed advances across major applications. This paper clarifies the current status and future research directions for better solving key water resources problems using EAs. Advances in understanding fitness landscape properties and their effects on algorithm performance are critical. Future EA-based applications to real-world problems require a fundamental shift of focus towards improving problem formulations, understanding general theoretic frameworks for problem decompositions, major advances in EA computational efficiency, and most importantly aiding real decision-making in complex, uncertain application contexts.

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Optimization of Water Distribution Systems Using Online Retrained Metamodels

Cited by 35 publications

References 20 publications

Lost in Optimisation of Water Distribution Systems? A Literature Review of System Design

Lost in Optimisation of Water Distribution Systems? A Literature Review of System Design

PEPSO: Reducing Electricity Usage and Associated Pollution Emissions of Water Pumps

Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions

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