Skip to main content

Advertisement

SpringerLink
Log in

Using particle swarm optimization algorithm to optimally locating and controlling of pressure reducing valves for leakage minimization in water distribution systems

  • Original Article
  • Published:
Sustainable Water Resources Management Aims and scope Submit manuscript

Abstract

The main objective of pressure management in a water distribution system (WDS) is to minimize leakages, bursts and maintain the required pressure at every node. One of the methods for pressure management is using pressure-reducing valves (PRV). This paper outlines an optimization-simulation approach to determine the optimum location and settings of the PRVs to control the pressure and minimize the leakage in WDSs. To solve the problem, the particle swarm optimization (PSO) tool was coupled with EPANET hydraulic simulation software in MATLAB environment. The results revealed that by observing all the regulations of the problem, through utilizing the proposed method for finding optimal location and regulating the PRVs, the network average leakage rate in a 24-h utilization period dropped by 23%. The performance of the PSO-based model in pressure management was compared with models based on three specific types of powerful algorithms including a genetic algorithm (GA) from the evolutionary algorithms (EA), artificial bee colony (ABC) from the swarm intelligence, and cultural algorithm (CA) from human behavior. The PSO-based model with the lowest objective function call compared to the other three algorithms, was able to reduce leakage compared to GA, ABC, and CA by 1.63, 3.45, and 8.53%, respectively. That shows the presented method is successful in regulating the pressure level to minimize network leakage.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Abbreviations

WDS:

Water distribution system

PRV:

Pressure reducing valve

C ij :

Hazen–Williams coefficient of pipe connecting nodes i and j

C L :

Coefficient relating the leakage per unit length of pipe to service pressure

d ij :

Diameter of pipe connecting nodes i and j

f(x):

Vector of objective functions

fi, fi(x):

iTh objective function

H i , k :

Head at node i for load condition k

h ij , k :

Head loss between nodes i and j for load condition k

L ij :

Length of pipe connecting nodes i and j

L S :

Total number of decision variables (string length)

L t , i :

Total length of pipes tributary to node i

l i , k :

Leakage at node i for load condition k

N :

Total number of nodes in the system

N L :

Number of load (demand) conditions

N P :

Number of nodes for which pi,k \(\ge\)preq,i

N S :

Number of nodes with leakage

N V :

Maximum number of valves allowed

n V :

Number of valves

p i , k :

Pressure at node i for load condition k

p req , i :

Required pressure at node i

Q ij , k :

Flow rate along pipe connecting nodes i and j for load condition k

Q req , i :

Average demand at node i

V ij , k :

Setting of valve ij for load condition k

v ij , k :

Diameter multiplier simulating the presence of a valve in link connecting nodes i and j for load condition k

w k :

Weight associated with load condition k

x :

Vector of decision variables

α k :

Demand multiplier for load condition k

γ :

Leakage exponent coefficient

References

  • Abdel Meguid H (2011) Pressure, leakage and energy management in water distribution systems. Ph.D. Thesis, Faculty of Technology, De Montfort University, Leicester, UK

  • Afshar A, Kazemi H, Saadatpour M (2011) Particle swarm optimization for automatic calibration of large-scale water quality model (CE-QUAL-W2): application to Karkheh Reservoir. Iran Water Res Manag 25(10):2613–2632

    Article  Google Scholar 

  • Babić B, Dukić A, Stanić M (2014) Managing water pressure for water savings in developing countries. Water SA 40(2):221–232

    Article  Google Scholar 

  • Brentan BM, Luvizotto E Jr, Montalvo I, Izquierdo J, Pérez-García R (2017) Near real time pump optimization and pressure management. Procedia Eng 186:666–675

    Article  Google Scholar 

  • Creaco E, Pezzinga G (2018) Comparison of algorithms for the optimal location of control valves for leakage reduction in WDNs. Water 10(4):466

    Article  Google Scholar 

  • Dini M, Asadi A (2019) Pressure management of large-scale water distribution network using optimal location and valve setting. Water Resour Manag 33(14):4701–4713

    Article  Google Scholar 

  • Jafari-Asl J (2016) Optimal pressure control for leakage minimization in water distribution systems management using meta heuristic techniques. M.Sc. Thesis, Department of Civil Engineering, Faculty of Engineering, Yasouj University, Yasouj, Iran

  • Jafari-Asl J, Sami Kashkooli B, Bahrami M (2018) Optimal pressure control for leakage minimization in water distribution networks. J Water Sustain Dev 2(4):49–56

    Google Scholar 

  • Jowitt PW, Xu C (1990) Optimal valve control in water distribution networks. J Water Resour Plan Manag 116(4):455–472

    Article  Google Scholar 

  • Kaydani H, Najafzadeh M, Mohebbi A (2014) Wellhead choke performance in oil well pipeline systems based on genetic programming. J Pipeline Syst Eng Pract 5(3):06014001

    Article  Google Scholar 

  • Kenedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of the international conference on neural networks, Perth, Australia, 1995 IEEE, Piscataway, pp 1942–1948

  • Kumar ND, Reddy JM (2007) Multipurpose reservoir operation using particle swarm optimization. J Water Resour Plan Manag 133(3):192–201

    Article  Google Scholar 

  • Latifi M, Naeeni ST, Gheibi MA (2017) Upgrading the reliability of water distribution networks through optimal use of pressure-reducing valves. J Water Resour Plan Manag 144(2):04017086

    Article  Google Scholar 

  • Mahdavi MM (2010) Leakage control in water distribution networks using pressure management. Semnan University, Semnan

    Google Scholar 

  • Montalvo I, Izquierdo J, PerezTung RMM (2008) Particle swarm optimization applied to the design of water supply systems. Comput Math Appl. https://doi.org/10.1016/j.camwa.2008.02.006

    Article  Google Scholar 

  • Montalvo I, Izquierdo J, Pérez-García R, Herrera M (2010) Improved performance of PSO with self-adaptive parameters for computing the optimal design of water supply systems. Eng Appl Artif Intell 23(5):727–735

    Article  Google Scholar 

  • Mutikanga HE (2012) Water loss management: tools and methods for developing countries. Ph.D. thesis, TU Delft, Delft University of Technology

  • Najafzadeh M (2019) Evaluation of conjugate depths of hydraulic jump in circular pipes using evolutionary computing. Soft Comput 23(24):13375–13391

    Article  Google Scholar 

  • Najafzadeh M, Sattar AM (2015) Neuro-fuzzy GMDH approach to predict longitudinal dispersion in water networks. Water Resour Manag 29(7):2205–2219

    Article  Google Scholar 

  • Nicolini M (2011) Optimal pressure management in water networks: increased efficiency and reduced energy costs. In: Defense science research conference and expo (DSR), IEEE, Singapore, pp 1–4

  • Nicolini M, Zovatto L (2009) Optimal location and control of pressure reducing valves in water networks. J Water Resour Plan Manag 135(3):178–187

    Article  Google Scholar 

  • Noory H, Liaghat AM, Parsinejad M, Haddad OB (2012) Optimizing irrigation water allocation and multicrop planning using discrete PSO algorithm. J Irrig Drain Eng 138(5):437–444

    Article  Google Scholar 

  • Reis LFR, Porto RM, Chaudhry FH (1997) Optimal location of control valves in pipe networks by Genetic Algorithm. J Water Resour Plann Manage 123(6):317–326

    Article  Google Scholar 

  • Rossman LA (2000) EPANET 2: user’s manual

  • Saldarriaga J, Salcedo CA (2015) Determination of optimal location and settings of pressure reducing valves in water distribution networks for minimizing water losses. Procedia Eng 119:973–983

    Article  Google Scholar 

  • Shi Y, Eberhart RC (1998) Parameter selection in particle swarm optimization. In: International conference on evolutionary programming. Springer, Berlin, pp 591–600

  • Sterling MJH, Bargiela A (2016) Leakage reduction by optimised control of valves in water networks. Trans Inst Meas Control 6(6):293–298

    Article  Google Scholar 

  • Tabesh M, Homehr S (2006) Leakage management in water networks using regulation optimization of PRV faucets genetic algorithm. In: Water resource management conference of Isfahan Industrial University, Society of Iran Water Resource Science and Engineering

  • Tabesh M, Shirzad A, Arefkhani V, Mani A (2014) A comparative study between the modified and available demand driven based models for head driven analysis of water distribution networks. Urban Water J 11(3):221–230

    Article  Google Scholar 

  • Ulanicki B, AbdelMeguid H, Bounds P, Patel R (2008) Pressure control in district metering areas with boundary and internal pressure reducing valves. In: 10th international water distribution system analysis conference, WDSA2008, The Kruger National Park, South Africa

Download references

Author information

Authors and Affiliations

  1. Department of Civil Engineering, University of Sistan and Baluchetan, Zahedan, Iran

    Jafar Jafari-Asl

  2. Hydraulic Structures Department, Tarbiat Modares University, Tehran, Iran

    Bahram Sami Kashkooli

  3. Department of Water Engineering, Faculty of Agriculture, Fasa University, Fasa, Iran

    Mehdi Bahrami

Authors
  1. Jafar Jafari-Asl
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bahram Sami Kashkooli
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mehdi Bahrami
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mehdi Bahrami.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jafari-Asl, J., Sami Kashkooli, B. & Bahrami, M. Using particle swarm optimization algorithm to optimally locating and controlling of pressure reducing valves for leakage minimization in water distribution systems. Sustain. Water Resour. Manag. 6, 64 (2020). https://doi.org/10.1007/s40899-020-00426-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s40899-020-00426-3

Keywords

Search

Navigation