IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i7p1582-d1106627.html
   My bibliography  Save this article

Infeasibility Maps: Application to the Optimization of the Design of Pumping Stations in Water Distribution Networks

Author

Listed:
  • Jimmy H. Gutiérrez-Bahamondes

    (PhD in Engineering Systems, Faculty of Engineering, Universidad de Talca, Camino Los Niches Km 1, Curicó 3340000, Chile)

  • Daniel Mora-Melia

    (Department of Engineering and Construction Management, Faculty of Engineering, Universidad de Talca, Camino Los Niches Km 1, Curicó 3340000, Chile
    Department of Hydraulic Engineering and Environment, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain)

  • Bastián Valdivia-Muñoz

    (PhD in Engineering Systems, Faculty of Engineering, Universidad de Talca, Camino Los Niches Km 1, Curicó 3340000, Chile)

  • Fabián Silva-Aravena

    (Faculty of Social and Economic Sciences, Universidad Católica del Maule, Avenida San Miguel 3605, Talca 3480094, Chile)

  • Pedro L. Iglesias-Rey

    (Department of Hydraulic Engineering and Environment, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain)

Abstract

The design of pumping stations in a water distribution network determines the investment costs and affects a large part of the operating costs of the network. In recent years, it was shown that it is possible to use flow distribution to optimize both costs concurrently; however, the methodologies proposed in the literature are not applicable to real-sized networks. In these cases, the space of solutions is huge, a small number of feasible solutions exists, and each evaluation of the objective function implies significant computational effort. To avoid this gap, a new method was proposed to reduce the search space in the problem of pumping station design. This method was based on network preprocessing to determine in advance the maximum and minimum flow that each pump station could provide. According to this purpose, the area of infeasibility is limited by ranges of the decision variable where it is impossible to meet the hydraulic constraints of the model. This area of infeasibility is removed from the search space with which the algorithm works. To demonstrate the benefits of using the new technique, a new real-sized case study was presented, and a pseudo-genetic algorithm (PGA) was implemented to resolve the optimization model. Finally, the results show great improvement in PGA performance, both in terms of the speed of convergence and quality of the solution.

Suggested Citation

  • Jimmy H. Gutiérrez-Bahamondes & Daniel Mora-Melia & Bastián Valdivia-Muñoz & Fabián Silva-Aravena & Pedro L. Iglesias-Rey, 2023. "Infeasibility Maps: Application to the Optimization of the Design of Pumping Stations in Water Distribution Networks," Mathematics, MDPI, vol. 11(7), pages 1-16, March.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:7:p:1582-:d:1106627
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/7/1582/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/7/1582/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aditya Gupta & K. D. Kulat, 2018. "A Selective Literature Review on Leak Management Techniques for Water Distribution System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(10), pages 3247-3269, August.
    2. Alexandru Predescu & Ciprian-Octavian Truică & Elena-Simona Apostol & Mariana Mocanu & Ciprian Lupu, 2020. "An Advanced Learning-Based Multiple Model Control Supervisor for Pumping Stations in a Smart Water Distribution System," Mathematics, MDPI, vol. 8(6), pages 1-29, June.
    3. Oreste Fecarotta & Aonghus McNabola, 2017. "Optimal Location of Pump as Turbines (PATs) in Water Distribution Networks to Recover Energy and Reduce Leakage," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(15), pages 5043-5059, December.
    4. Yasaman Makaremi & Ali Haghighi & Hamid Reza Ghafouri, 2017. "Optimization of Pump Scheduling Program in Water Supply Systems Using a Self-Adaptive NSGA-II; a Review of Theory to Real Application," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(4), pages 1283-1304, March.
    5. Ivana Lučin & Bože Lučin & Zoran Čarija & Ante Sikirica, 2021. "Data-Driven Leak Localization in Urban Water Distribution Networks Using Big Data for Random Forest Classifier," Mathematics, MDPI, vol. 9(6), pages 1-14, March.
    6. N. Nagkoulis & K.L. Katsifarakis, 2020. "Minimization of Total Pumping Cost from an Aquifer to a Water Tank, Via a Pipe Network," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(13), pages 4147-4162, October.
    7. D. Mora-Melia & P. Iglesias-Rey & F. Martinez-Solano & V. Fuertes-Miquel, 2013. "Design of Water Distribution Networks using a Pseudo-Genetic Algorithm and Sensitivity of Genetic Operators," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(12), pages 4149-4162, September.
    8. Safarbek Oshurbekov & Vadim Kazakbaev & Vladimir Prakht & Vladimir Dmitrievskii, 2021. "Improving Reliability and Energy Efficiency of Three Parallel Pumps by Selecting Trade-Off Operating Points," Mathematics, MDPI, vol. 9(11), pages 1-19, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Antonin Ponsich & Bruno Domenech & Mariona Vilà, 2023. "Preface to the Special Issue “Mathematical Optimization and Evolutionary Algorithms with Applications”," Mathematics, MDPI, vol. 11(10), pages 1-6, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Thomas Pirard & Vasileios Kitsikoudis & Sebastien Erpicum & Michel Pirotton & Pierre Archambeau & Benjamin Dewals, 2022. "Discharge Redistribution as a Key Process for Heuristic Optimization of Energy Production with Pumps as Turbines in a Water Distribution Network," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1237-1250, March.
    2. Bohong Wang & Yongtu Liang & Wei Zhao & Yun Shen & Meng Yuan & Zhimin Li & Jian Guo, 2021. "A Continuous Pump Location Optimization Method for Water Pipe Network Design," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(2), pages 447-464, January.
    3. D. Mora-Melia & P. Iglesias-Rey & F. Martinez-Solano & P. Ballesteros-Pérez, 2015. "Efficiency of Evolutionary Algorithms in Water Network Pipe Sizing," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(13), pages 4817-4831, October.
    4. Alejandro Tapia Córdoba & Daniel Gutiérrez Reina & Pablo Millán Gata, 2019. "An Evolutionary Computational Approach for Designing Micro Hydro Power Plants," Energies, MDPI, vol. 12(5), pages 1-25, March.
    5. Hamlehdar, Maryam & Yousefi, Hossein & Noorollahi, Younes & Mohammadi, Mohammad, 2022. "Energy recovery from water distribution networks using micro hydropower: A case study in Iran," Energy, Elsevier, vol. 252(C).
    6. Manoujan, Amin Zarei & Riasi, Alireza, 2024. "Optimal selection of parallel pumps running as turbines for energy harvesting in water transmission lines considering economic parameters," Applied Energy, Elsevier, vol. 359(C).
    7. Kemi Adeyeye & John Gallagher & Helena M. Ramos & Aonghus McNabola, 2022. "The Social Return Potential of Micro Hydropower in Water Networks Based on Demonstrator Examples," Energies, MDPI, vol. 15(18), pages 1-21, September.
    8. Zukang Hu & Wenlong Chen & Beqing Chen & Debao Tan & Yu Zhang & Dingtao Shen, 2021. "Robust Hierarchical Sensor Optimization Placement Method for Leak Detection in Water Distribution System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(12), pages 3995-4008, September.
    9. Moazeni, Faegheh & Khazaei, Javad, 2021. "Optimal energy management of water-energy networks via optimal placement of pumps-as-turbines and demand response through water storage tanks," Applied Energy, Elsevier, vol. 283(C).
    10. Moghaddam, Ali & Kutschelis, Boris & Holz, Frank & Skoda, Romuald, 2024. "Experiments and three-dimensional flow simulations on twin-screw pumps operated as control valves for energy recovery," Energy, Elsevier, vol. 306(C).
    11. Mehdi Dini & Mozhdeh Hemmati & Saeed Hashemi, 2022. "Optimal Operational Scheduling of Pumps to Improve the Performance of Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(1), pages 417-432, January.
    12. Davi Edson Sales Souza & André Luiz Amarante Mesquita & Claudio José Cavalcante Blanco, 2023. "Pressure Regulation in a Water Distribution Network Using Pumps as Turbines at Variable Speed for Energy Recovery," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(3), pages 1183-1206, February.
    13. Yu Shao & Yanxi Yu & Tingchao Yu & Shipeng Chu & Xiaowei Liu, 2019. "Leakage Control and Energy Consumption Optimization in the Water Distribution Network Based on Joint Scheduling of Pumps and Valves," Energies, MDPI, vol. 12(15), pages 1-18, August.
    14. Moslehi, Iman & Jalili Ghazizadeh, Mohammadreza & Yousefi-Khoshqalb, Ehsan, 2020. "An economic valuation model for alternative pressure management schemes in water distribution networks," Utilities Policy, Elsevier, vol. 67(C).
    15. Chi Zhang & Martin F. Lambert & Jinzhe Gong & Aaron C. Zecchin & Angus R. Simpson & Mark L. Stephens, 2020. "Bayesian Inverse Transient Analysis for Pipeline Condition Assessment: Parameter Estimation and Uncertainty Quantification," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 2807-2820, July.
    16. Nikolaos Nagkoulis & Konstantinos L. Katsifarakis, 2022. "Using Game Theory to Assign Groundwater Pumping Schedules," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(5), pages 1571-1586, March.
    17. Ana Paula Pereira Silveira & Herlander Mata-Lima, 2021. "Assessing Energy Efficiency in Water Utilities Using Long-term Data Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(9), pages 2763-2779, July.
    18. Kostner, Michael K. & Zanfei, Ariele & Alberizzi, Jacopo C. & Renzi, Massimiliano & Righetti, Maurizio & Menapace, Andrea, 2023. "Micro hydro power generation in water distribution networks through the optimal pumps-as-turbines sizing and control," Applied Energy, Elsevier, vol. 351(C).
    19. Juan Li & Ying Wu & Wenjun Zheng & Changgang Lu, 2021. "A Model-Based Bayesian Framework for Pipeline Leakage Enumeration and Location Estimation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(13), pages 4381-4397, October.
    20. Aditya Dinesh Gupta & Prerna Pandey & Andrés Feijóo & Zaher Mundher Yaseen & Neeraj Dhanraj Bokde, 2020. "Smart Water Technology for Efficient Water Resource Management: A Review," Energies, MDPI, vol. 13(23), pages 1-23, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:11:y:2023:i:7:p:1582-:d:1106627. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.