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Development of a Predicting Model for Calculating the Geometry and the Characteristic Curves of Pumps Running as Turbines in Both Operating Modes

Author

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  • Silvio Barbarelli

    (Department of Mechanical, Energy and Management Engineering, University of Calabria, Via Ponte P. Bucci Cubo 44/C, 87036 Rende, Italy)

  • Vincenzo Pisano

    (Department of Mechanical, Energy and Management Engineering, University of Calabria, Via Ponte P. Bucci Cubo 44/C, 87036 Rende, Italy)

  • Mario Amelio

    (Department of Mechanical, Energy and Management Engineering, University of Calabria, Via Ponte P. Bucci Cubo 44/C, 87036 Rende, Italy)

Abstract

This article is part of a scientific research project dedicated to the study of plants generating electricity from hydraulic sources by exploiting the technology of inverted flow centrifugal pumps, also known as PAT. The main purpose is to provide a contribution to the methodologies already existing in the literature, creating a one-dimensional model capable of predicting the characteristic curves of the machine, in both operating modes, without knowing its geometry. The first part of the work is therefore focused on the description of the fluid dynamic model, capable of determining the losses in the various sections of the machine, using different calculation approaches. The development of this model was carried out using a set of six centrifugal pumps, measured at the DIMEG Department of the University of Calabria and at the University of Trento. For this range of pumps, the characteristic curves were therefore obtained, both in pump and turbine operation. The second part of this work focuses on the description of the geometric model, useful as generally few data are provided in the manufacturer’s catalog, which is necessary for the correct installation of the machine. The geometric model can determine, using these parameters and through good design techniques and statistical diagrams, the entire geometry of the machine. This model refers to a pump prototype, having a simplified geometry, for which the characteristic curves of the PAT are obtained in pump operation. These curves are compared with those present in the manufacturer’s catalog, and if they show too high deviations, it is possible to act on some geometric parameters, chosen based on a sensitivity analysis. Once satisfactory results have been obtained, it is possible to obtain the characteristic curves also in turbine operation. This procedure has been finally applied to another PAT, taken as an example.

Suggested Citation

  • Silvio Barbarelli & Vincenzo Pisano & Mario Amelio, 2022. "Development of a Predicting Model for Calculating the Geometry and the Characteristic Curves of Pumps Running as Turbines in Both Operating Modes," Energies, MDPI, vol. 15(7), pages 1-28, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:7:p:2669-:d:787502
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    References listed on IDEAS

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    1. Morabito, Alessandro & Vagnoni, Elena & Di Matteo, Mariano & Hendrick, Patrick, 2021. "Numerical investigation on the volute cutwater for pumps running in turbine mode," Renewable Energy, Elsevier, vol. 175(C), pages 807-824.
    2. Williams, A.A., 1996. "Pumps as turbines for low cost micro hydro power," Renewable Energy, Elsevier, vol. 9(1), pages 1227-1234.
    3. Barbarelli, S. & Amelio, M. & Florio, G., 2016. "Predictive model estimating the performances of centrifugal pumps used as turbines," Energy, Elsevier, vol. 107(C), pages 103-121.
    4. Silvio Barbarelli & Benedetto Nastasi, 2021. "Tides and Tidal Currents—Guidelines for Site and Energy Resource Assessment," Energies, MDPI, vol. 14(19), pages 1-20, September.
    5. Lima, Gustavo Meirelles & Luvizotto, Edevar & Brentan, Bruno M., 2017. "Selection and location of Pumps as Turbines substituting pressure reducing valves," Renewable Energy, Elsevier, vol. 109(C), pages 392-405.
    6. Mario Amelio & Silvio Barbarelli & Domenico Schinello, 2020. "Review of Methods Used for Selecting Pumps as Turbines (PATs) and Predicting Their Characteristic Curves," Energies, MDPI, vol. 13(23), pages 1-20, December.
    7. Venturini, Mauro & Manservigi, Lucrezia & Alvisi, Stefano & Simani, Silvio, 2018. "Development of a physics-based model to predict the performance of pumps as turbines," Applied Energy, Elsevier, vol. 231(C), pages 343-354.
    8. Tan, Xu & Engeda, Abraham, 2016. "Performance of centrifugal pumps running in reverse as turbine: Part Ⅱ- systematic specific speed and specific diameter based performance prediction," Renewable Energy, Elsevier, vol. 99(C), pages 188-197.
    9. Barbarelli, S. & Florio, G. & Amelio, M. & Scornaienchi, N.M., 2018. "Preliminary performance assessment of a novel on-shore system recovering energy from tidal currents," Applied Energy, Elsevier, vol. 224(C), pages 717-730.
    10. Mohammad Omidi & Shu-Jie Liu & Soheil Mohtaram & Hui-Tian Lu & Hong-Chao Zhang, 2019. "Improving Centrifugal Compressor Performance by Optimizing the Design of Impellers Using Genetic Algorithm and Computational Fluid Dynamics Methods," Sustainability, MDPI, vol. 11(19), pages 1-18, September.
    11. Barbarelli, Silvio & Florio, Gaetano & Lo Zupone, Giacomo & Scornaienchi, Nino Michele, 2018. "First techno-economic evaluation of array configuration of self-balancing tidal kinetic turbines," Renewable Energy, Elsevier, vol. 129(PA), pages 183-200.
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    Cited by:

    1. Balacco, Gabriella & Fiorese, Gaetano Daniele & Alfio, Maria Rosaria & Totaro, Vincenzo & Binetti, Mario & Torresi, Marco & Stefanizzi, Michele, 2023. "PaT-ID: A tool for the selection of the optimal pump as turbine for a water distribution network," Energy, Elsevier, vol. 282(C).
    2. 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).
    3. Maria Castorino, Giulia Anna & Manservigi, Lucrezia & Barbarelli, Silvio & Losi, Enzo & Venturini, Mauro, 2023. "Development and validation of a comprehensive methodology for predicting PAT performance curves," Energy, Elsevier, vol. 274(C).

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