Pressure Management of Large-Scale Water Distribution Network Using Optimal Location and Valve Setting

Dini, Mehdi; Asghar, Asadi

doi:10.1007/s11269-019-02381-x

Cited by 20 publications

(9 citation statements)

References 16 publications

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“…Their performances have been demonstrated better than GA. Particle swarm optimization (PSO) [32] and differential evolution (DE) [33] algorithms were also employed to address the optimal valve setting problems, but for small scale WDSs. Although the heuristic solution approaches can solve complex optimization problems, they normally require a huge computation time, especially for large scale WDSs, hence they are appropriate for off-line control.…”

Section: Introductionmentioning

confidence: 99%

Optimal Pressure Management in Water Distribution Systems Using an Accurate Pressure Reducing Valve Model Based Complementarity Constraints

Dai

2021

Water

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Water loss according to water leakages in water distribution systems (WDSs) is a challenging problem worldwide. An inappropriate operation of the WDS leads to unnecessarily high pressure distribution in the WDS and thus a large amount of water leakage exists. For this reason, optimal pressure management in WDSs through regulating operations of pressure reducing valves (PRVs) is priority for water utilities. The pressure management can be accomplished in a hierarchical control scheme with high level and low level controllers. While the high level controller is responsible for calculating pressure set points for critical nodes, the task of a low level controller is to regulate the pressures at the critical nodes to the set points. The optimal pressure management in the high level controller can be casted into a nonlinear programing problem (NLP) where PRV models are crucial and determine proper operation of the WDS and quality of overall pressure control. PRV models having been used until now either describe two operating modes (active and open modes) or three operating modes (active, open and check valve modes) with parameter dependence. Such models make the formulated NLP unsuitable for the case PRVs work in check valve modes or resulted in inaccurate NLP solution with unexpected operation modes of PRVs, respectively. Therefore, this paper proposes an accurate PRV model based on complementarity constraints. The new PRV model is parameter-less dependence and is capable of describing complete operation modes of PRVs in practice. As a result, the formulated NLP is general and provides accurate NLP solution. The efficiency of our new PRV model is demonstrated on numerous case studies for optimal pressure management of WDSs.

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Section: Introductionmentioning

confidence: 99%

Optimal Pressure Management in Water Distribution Systems Using an Accurate Pressure Reducing Valve Model Based Complementarity Constraints

Dai

2021

Water

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“…Recently, Cao et al (2019) proposed an approach based on the k-means++ method to simultaneously place pressure sensors and localizing PRVs for the purpose of control system design for online pressure control. Mehdi and Asghar (2019) introduced a new Valve Selection Index (VSI) and that the links with high values of VSI will be chosen as potential links for placing valves. The Particle Swarm Optimization was then used to determine optimal pressure settings of PRVs by maximum the nodal pressure reliability index in the WDS.…”

Section: Introductionmentioning

confidence: 99%

A new mathematical program with complementarity constraints for optimal localization of pressure reducing valves in water distribution systems

Dai

2021

Appl Water Sci

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Water loss reduction in water distribution systems (WDSs) is a challenging task for water utilities worldwide. One of the most reliable and cost-effective ways to reduce water loss is to properly regulate operational pressure of the system through optimizing pressure reducing valve (PRV) placements. This well-known engineering problem can be casted into a mixed-integer nonlinear program (MINLP) where binary variables are introduced to represent positions of PRVs. Many works in the literature applied heuristic algorithms to address the optimization problem. In this paper, at first, we proposed a new optimization model and reformulated it as the mathematical program with complementarity constraints (MPCCs). It is due to the fact that the stationary point of the MPCCs is likely to be trapped into bad local solutions, a soft heuristic method is then proposed to determine the MINLP local solution in each iteration before a stationary point of the MPCCs is reached. This method not only enhances the quality of MINLP solution, but also decreases computation time for solving the MPCCs. The newly formulated MPCCs is applied to determine optimal localization of PRVs for two WDS benchmarks and a real-world WDS in Vietnam. The results are compared with others in the literature demonstrating that using our new optimization model, better and more reliable MINLP solution can be found for large scale WDSs.

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“…Mehdi and Asghar [6] adjusted the node pressure with the particle swarm optimization algorithm considering both the pressure reducing valves and the reliability of WDNs. Zhang et al [7] optimized the locations of water meters based on natural and administrative borders using the genetic algorithm to improve the hydraulic ability and water quality of WDNs.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Water Distribution Network Design for Resisting Cascading Failures

2020

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Water distribution networks (WDNs) is crucial to ensure social operations and economic activities. However, WDNs are highly sensitive and vulnerable to disasters. The aim of this study is to mitigate the catastrophic consequences of cascading failures in WDNs. A flow-based WDN cascading failure model is built. The extended multi-objective particle swarm optimization model is developed to resist cascading failures and improve resilience. This model takes pipe diameter as the decision variable to minimize cost and maximize pressure deficit. Water balance, pressure, and standard pipe diameter are the constraints. The classical optimal scenario (COS) and the cascading failure scenario (CFS) are simulated. The model is applied to a small and medium-sized benchmarked WDN. Results show that the extended PSO can find the optimal solution on the benchmarked WDN. The Pareto fronts are obtained. Compare to the Pareto fronts between COS and CFS, the pressure deficit under CFS is significantly reduced, and the cost is reduced while the same pressure deficit increased. Different tolerance parameters are tested. The small network is not sensitive to the tolerance parameter, but the medium-sized network is sensitive. The model evaluates a variety of conflicting goals, which help designers and water managers resist cascading failures in WDNs.

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Pressure Management of Large-Scale Water Distribution Network Using Optimal Location and Valve Setting

Cited by 20 publications

References 16 publications

Optimal Pressure Management in Water Distribution Systems Using an Accurate Pressure Reducing Valve Model Based Complementarity Constraints

Optimal Pressure Management in Water Distribution Systems Using an Accurate Pressure Reducing Valve Model Based Complementarity Constraints

A new mathematical program with complementarity constraints for optimal localization of pressure reducing valves in water distribution systems

Optimization of Water Distribution Network Design for Resisting Cascading Failures

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