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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
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    References listed on IDEAS

    as
    1. 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).
    2. 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.
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    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.

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