IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i21p12318-d674462.html
   My bibliography  Save this article

Stochastic Approach for Optimal Positioning of Pumps As Turbines (PATs)

Author

Listed:
  • Mariacrocetta Sambito

    (Department of Engineering, University of Palermo, Viale delle Scienze, Ed. 8, 90100 Palermo, Italy)

  • Stefania Piazza

    (School of Engineering and Architecture, University of Enna “Kore”, 94100 Enna, Italy)

  • Gabriele Freni

    (School of Engineering and Architecture, University of Enna “Kore”, 94100 Enna, Italy)

Abstract

A generic water system consists of a series of works that allow the collection, conveyance, storage and finally the distribution of water in quantities and qualities such as to satisfy the needs of end users. In places characterized by high altitude differences between the intake works and inhabited centres, the potential energy of the water is very high. This energy is attributable to high pressures, which could compromise the functionality of the pipelines; it is therefore necessary to dissipate part of this energy. A common alternative to dissipation is the possibility of exploiting this energy by inserting a hydraulic turbine. The present study aims to evaluate the results obtained from a stochastic approach for the solution of the multi-objective optimization problem of PATs (Pumps As Turbines) in water systems. To this end, the Bayesian Monte Carlo optimisation method was chosen for the optimization of three objective functions relating to pressure, energy produced and plant costs. The case study chosen is the Net 3 literature network available in the EPANET software manual. The same problem was addressed using the NSGA-III (Nondominated Sorting Genetic Algorithm) to allow comparison of the results, since the latter is more commonly used. The two methods have different peculiarities and therefore perform better in different contexts.

Suggested Citation

  • Mariacrocetta Sambito & Stefania Piazza & Gabriele Freni, 2021. "Stochastic Approach for Optimal Positioning of Pumps As Turbines (PATs)," Sustainability, MDPI, vol. 13(21), pages 1-12, November.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:12318-:d:674462
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/21/12318/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/21/12318/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Paul Feliot & Julien Bect & Emmanuel Vazquez, 2017. "A Bayesian approach to constrained single- and multi-objective optimization," Journal of Global Optimization, Springer, vol. 67(1), pages 97-133, January.
    2. 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).
    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. Przemysław Średziński & Martyna Świętochowska & Kamil Świętochowski & Joanna Gwoździej-Mazur, 2022. "Analysis of the Use of the PV Installation in the Power Supply of the Water Pumping Station," Energies, MDPI, vol. 15(24), pages 1-13, December.
    2. 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.
    3. Linghua Kong & Jingwei Cao & Xiangyang Li & Xulei Zhou & Haihong Hu & Tao Wang & Shuxin Gui & Wenfa Lai & Zhongfeng Zhu & Zhengwei Wang & Yan Liu, 2022. "Numerical Analysis on the Hydraulic Thrust and Dynamic Response Characteristics of a Turbine Pump," Energies, MDPI, vol. 15(4), pages 1-15, February.
    4. Abdulbasit Nasir & Edessa Dribssa & Misrak Girma & Habtamu Bayera Madessa, 2023. "Selection and Performance Prediction of a Pump as a Turbine for Power Generation Applications," Energies, MDPI, vol. 16(13), pages 1-16, June.
    5. Dariusz Andraka & Wojciech Kruszyński & Jacek Tyniec & Joanna Gwoździej-Mazur & Bartosz Kaźmierczak, 2023. "Practical Aspects of the Energy Efficiency Evaluation of a Water Distribution Network Using Hydrodynamic Modeling—A Case Study," Energies, MDPI, vol. 16(8), pages 1-17, April.

    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. Ávila, Carlos Andrés Macías & Sánchez-Romero, Francisco-Javier & López-Jiménez, P. Amparo & Pérez-Sánchez, Modesto, 2021. "Optimization tool to improve the management of the leakages and recovered energy in irrigation water systems," Agricultural Water Management, Elsevier, vol. 258(C).
    2. Dawei Zhan & Huanlai Xing, 2020. "Expected improvement for expensive optimization: a review," Journal of Global Optimization, Springer, vol. 78(3), pages 507-544, November.
    3. Linghua Kong & Jingwei Cao & Xiangyang Li & Xulei Zhou & Haihong Hu & Tao Wang & Shuxin Gui & Wenfa Lai & Zhongfeng Zhu & Zhengwei Wang & Yan Liu, 2022. "Numerical Analysis on the Hydraulic Thrust and Dynamic Response Characteristics of a Turbine Pump," Energies, MDPI, vol. 15(4), pages 1-15, February.
    4. Elsir, Mohamed & Al-Sumaiti, Ameena Saad & El Moursi, Mohamed Shawky & Al-Awami, Ali Taleb, 2023. "Coordinating the day-ahead operation scheduling for demand response and water desalination plants in smart grid," Applied Energy, Elsevier, vol. 335(C).
    5. Telikani, Akbar & Rossi, Mosé & Khajehali, Naghmeh & Renzi, Massimiliano, 2023. "Pumps-as-Turbines’ (PaTs) performance prediction improvement using evolutionary artificial neural networks," Applied Energy, Elsevier, vol. 330(PA).
    6. Stefanizzi, M. & Filannino, D. & Capurso, T. & Camporeale, S.M. & Torresi, M., 2023. "Optimal hydraulic energy harvesting strategy for PaT installation in Water Distribution Networks," Applied Energy, Elsevier, vol. 344(C).
    7. Koziel, Slawomir & Pietrenko-Dabrowska, Anna, 2022. "Constrained multi-objective optimization of compact microwave circuits by design triangulation and pareto front interpolation," European Journal of Operational Research, Elsevier, vol. 299(1), pages 302-312.
    8. Maxime Binama & Kan Kan & Hui-Xiang Chen & Yuan Zheng & Da-Qing Zhou & Wen-Tao Su & Xin-Feng Ge & Janvier Ndayizigiye, 2021. "A Numerical Investigation into the PAT Hydrodynamic Response to Impeller Rotational Speed Variation," Sustainability, MDPI, vol. 13(14), pages 1-22, July.
    9. Duro, João A. & Ozturk, Umud Esat & Oara, Daniel C. & Salomon, Shaul & Lygoe, Robert J. & Burke, Richard & Purshouse, Robin C., 2023. "Methods for constrained optimization of expensive mixed-integer multi-objective problems, with application to an internal combustion engine design problem," European Journal of Operational Research, Elsevier, vol. 307(1), pages 421-446.
    10. Audet, Charles & Bigeon, Jean & Cartier, Dominique & Le Digabel, Sébastien & Salomon, Ludovic, 2021. "Performance indicators in multiobjective optimization," European Journal of Operational Research, Elsevier, vol. 292(2), pages 397-422.
    11. C. P. Brás & A. L. Custódio, 2020. "On the use of polynomial models in multiobjective directional direct search," Computational Optimization and Applications, Springer, vol. 77(3), pages 897-918, December.
    12. Candelieri Antonio, 2021. "Sequential model based optimization of partially defined functions under unknown constraints," Journal of Global Optimization, Springer, vol. 79(2), pages 281-303, February.

    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:jsusta:v:13:y:2021:i:21:p:12318-:d:674462. 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.