Probabilistic and fuzzy approaches for uncertainty consideration in water distribution networks – a review

Pandey, Prerna; Dongre, Shilpa; Gupta, Rajesh

doi:10.2166/ws.2019.141

Cited by 18 publications

(6 citation statements)

References 37 publications

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“…The proposed methodology reflected the contextual uncertainty in the spatial and temporal distributions of hydraulic variables and of the selected performance metrics, by comparing the results of the most opposite scenarios. The methodology offers richer descriptions of the future with a higher range, as opposed to looking at uncertainty as a probabilistic distribution of a single variable or parameter, where the system's context is not considered [8,9] and the range is smaller.…”

Section: Discussionmentioning

confidence: 99%

“…The same zones are identified in the variation between Scenario 1 and Scenario 2 relative to the reference scenario (Figure 8d). This new approach of incorporating aleatory uncertainty of future events in WDN prognosis analysis provides higher insights into the future system behaviour, by considering the two opposite context scenarios instead of simply looking at uncertainty as a probabilistic distribution [8,9], where the system's context is not considered.…”

Section: Scenario Application To System Performance Assessmentmentioning

confidence: 99%

“…Uncertainty is divided into two categories: epistemic uncertainty, related to the imperfection of our knowledge (i.e., limited and inaccurate data and measurement error) and aleatory or variability, uncertainty, related to the inherent variability in social, economic, and technological developments associated with WDN models by external input data, input functions, and parameters (i.e., spatial and temporal variability in water demand) [6,7]. While for epistemic uncertainty additional research may improve the quality of our knowledge, for aleatory uncertainty, additional research may not be sufficient to improve the output, and other methods are regarded, such as probability distributions [8], fuzzy approaches [9], and scenario techniques [10].…”

Section: Introductionmentioning

confidence: 99%

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Integrating Uncertainty in Performance Assessment of Water Distribution Networks by Scenario Building

Carneiro,

Loureiro,

Cabral

et al. 2024

Water

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This paper presents and demonstrates a novel scenario-building methodology that integrates contextual and future time uncertainty into the performance assessment of water distribution networks (WDNs). A three-step approach is proposed: (i) System context analysis, identifying the main key factors that impact the WDN performance; (ii) Scenario definition, identifying the implicated WDN variables, describing its possible evolution, and conjugating them to further establish the reference scenario and the two most relevant and opposite ones; and (iii) Scenario modelling, simulating the WDN behaviour for those scenarios. The obtained spatial and temporal hydraulic results are further used to calculate performance metrics. The methodology is applied to a real WDN to assess resilience performance considering infrastructure asset robustness (real water loss performance indicator), service reliability (minimum pressure index), and service flexibility (network resilience index). A new formulation to assess the metric evolution over time is proposed, deducting the further-away performance results by using an uncertainty weight. The results demonstrate that the increase in metric amplitude for the opposite scenarios over time highlights future uncertainty, reflecting context uncertainty, and the comparison of metric spatial distribution (i.e., at the pipe/node levels) highlights critical areas with higher associated uncertainty.

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Section: Discussionmentioning

confidence: 99%

Section: Scenario Application To System Performance Assessmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Integrating Uncertainty in Performance Assessment of Water Distribution Networks by Scenario Building

Carneiro,

Loureiro,

Cabral

et al. 2024

Water

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“…The intricate nature of WDS is characterized by an underlying uncertainty which also poses a substantial obstacle to conventional deterministic optimization approaches used for both the design and operation of these systems (Boindala et al, 2023a;Dandy et al, 2022). This uncertainty stems from a multitude of factors, encompassing various dimensions, such as fluctuations in demand patterns, supply dynamics, and the inherent variability of parameters within water quality models (Pandey et al, 2020). Demand variability stands as one of the primary sources of uncertainty within WDS (Pandey et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Booster Disinfection Scheduling under Uncertainty in Water Distribution Systems: Approximate Robust Reformulation Approach

Boindala,

Jaykrishnan,

Ostfeld

2023

Preprint

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One key aspect of ensuring water safety in water distribution systems (WDS) is the controlled use of disinfectants like chlorine within these systems. The amount of disinfectant levels in WDS directly impacts the quality and safety of the water supplied to consumers thus chlorine/disinfectant regulation in WDS is paramount. An upper residual Chlorine limit controls the formation of disinfection by-products, while a lower residual Chlorine limit guarantees that the water remains free of organic contaminants. However, accurately modelling the Chlorine reaction in WDS is a complex task due to various influencing factors, including pipe material, pipe age, water pH, temperature, and more. The variability in the Chlorine reaction rate in WDS poses a significant challenge in accurately predicting water quality provided to the consumers and also affects the optimal scheduling of Chlorine booster injections. To ensure the water quality remains within the acceptable range, we consider the chlorine reaction rate as an uncertain parameter and propose an approximate robust reformulation approach for the booster chlorination scheduling problem. We utilize two benchmark WDS systems to perform rigorous testing and analysis of our methodology. The proposed approach provides a systematic and robust method to obtain chlorine injection scheduling that adheres to predefined aims to maintain safe water quality levels while considering the uncertain reaction rate coefficients to be within ellipsoidal uncertainty sets.

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“…They discussed the merits and demerits of fuzzy logic, appreciated its role in data-scarce modeling situations and predictive capability. Pandey et al (2020) reviewed fuzzy and probabilistic approaches in WDN extensively.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy optimization-based Water Distribution Network design using Self-Adaptive Cuckoo Search Algorithm

2021

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Water Distribution Network(s) (WDN) design is gaining prominence in the urban planning context. Several factors that play a significant role in design are uncertainty in data, non-linear relation of head loss & discharge, combinatorial nature of the problem, and high computational requirements. In addition, many conflicting objectives are possible and required for effective WDN design, such as cost, resilience, and leakage. Most of the research work published has used multiobjective evolutionary optimization in solving such complex WDN. However, the challenge of such population based evolutionary approaches is that they provide multiple trade-off Pareto optimal solutions to the decision-maker who will have to choose another set of techniques to arrive at a single optimal solution. The present study employs a fuzzy optimization approach that would provide a single optimal WDN design for Hanoi and Pamapur, India. Maximization of network resilience (NR) and minimization of network cost (NC) are employed in a multiobjective context. Later, minimization of network leakages (NL) is also incorporated, leading to three objective problems. Hyperbolic Membership Function (HMF), Exponential Membership Function (EMF), and Non-linear Membership Function (NMF) are employed in Self-Adaptive Cuckoo Search Algorithm based fuzzy optimization. HMF is found suitable to determine the best possible WDN design for chosen case studies based on the highest degree of satisfaction. HIGHLIGHT Most of the research conducted till now have used evolutionary multiobjective optimization in solving WDNs. But, the challenge of such evolutionary approaches is that they provide multiple trade-off pareto optimal solutions to the decision maker who will have to further choose another methodology to converge to a single optimal solution. The proposed methodology would simplify the decision-making process for an engineer.

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Probabilistic and fuzzy approaches for uncertainty consideration in water distribution networks – a review

Cited by 18 publications

References 37 publications

Integrating Uncertainty in Performance Assessment of Water Distribution Networks by Scenario Building

Integrating Uncertainty in Performance Assessment of Water Distribution Networks by Scenario Building

Booster Disinfection Scheduling under Uncertainty in Water Distribution Systems: Approximate Robust Reformulation Approach

Fuzzy optimization-based Water Distribution Network design using Self-Adaptive Cuckoo Search Algorithm

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