Simultaneous Sensor Placement and Pressure Reducing Valve Localization for Pressure Control of Water Distribution Systems

Cao, Hao; Hopfgarten, Siegbert; Ostfeld, Avi; Salomons, Elad; Li, Pu

doi:10.3390/w11071352

Cited by 14 publications

(10 citation statements)

References 41 publications

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“…The proposed methodology in this paper will be applied to the WDN studied by Jowitt and Xu [50], which is reproduced in Figure 2. This network is a benchmark Water Distribution System, which is very often used to verify optimization methods in water supply networks such as optimal valve location in [51][52][53] and PAT localization problems in [54]. The network consists of 37 links, 22 nodes, and 3 reservoirs.…”

Section: Benchmark Water Distribution Networkmentioning

confidence: 99%

Smart Hydropower Water Distribution Networks, Use of Artificial Intelligence Methods and Metaheuristic Algorithms to Generate Energy from Existing Water Supply Networks

Karakatsanis

Theodossiou

2022

Energies

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In this paper, the possibility of installing small hydraulic turbines in existing water-supply networks, which exploit the daily pressure fluctuations in order to produce energy, is examined. For this purpose, a network of five pressure sensors is developed, which is connected to an artificial intelligence system in order to predict the daily pressure values of all nodes of the network. The sensors are placed at the critical nodes of the network. The locations of the critical nodes are implemented by applying graph theory algorithms to the water distribution network. EPANET software is used to generate the artificial intelligence training data with an appropriate external call from a Python script. Then, an improvement model is implemented using the Harmony Search Algorithm in order to calculate the daily pressure program, which can be allocated to the turbines and, consequently, the maximum energy production. The proposed methodology is applied to a benchmark water supply network and the results are presented.

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Section: Benchmark Water Distribution Networkmentioning

confidence: 99%

Smart Hydropower Water Distribution Networks, Use of Artificial Intelligence Methods and Metaheuristic Algorithms to Generate Energy from Existing Water Supply Networks

Karakatsanis

Theodossiou

2022

Energies

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“…In practice, a PRV has three operating modes, which are active (i.e., the PRV maintains the downstream pressure at the preset value), open (i.e., when the downstream pressure is lower than the pressure setting) and check valve modes (i.e., when upstream pressure is lower than the downstream pressure) [1,10,33]. Consider a PRV placed on link ij, we denote H i,k as the nodal upstream head and H j,k as the nodal downstream head.…”

Section: Existing Mathematical Model Of Prv and The Newly Proposed Prv Model 21 Existing Model Of Pressure Reducing Valvesmentioning

confidence: 99%

“…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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“…NSGA-II was used to choose the best combinations of PRVs among the link candidates as well as pressure setting of PRVs. 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.…”

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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Simultaneous Sensor Placement and Pressure Reducing Valve Localization for Pressure Control of Water Distribution Systems

Cited by 14 publications

References 41 publications

Smart Hydropower Water Distribution Networks, Use of Artificial Intelligence Methods and Metaheuristic Algorithms to Generate Energy from Existing Water Supply Networks

Smart Hydropower Water Distribution Networks, Use of Artificial Intelligence Methods and Metaheuristic Algorithms to Generate Energy from Existing Water Supply Networks

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

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