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A methodology to forecast the main non-dimensional performance parameters of pumps-as-turbines (PaTs) operating at Best Efficiency Point (BEP)

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  • Renzi, Massimiliano
  • Nigro, Alessandra
  • Rossi, Mosè

Abstract

This work presents a model based on analytical equations to identify the Best Efficiency Point (BEP) of Pumps-as-Turbines (PaTs). The equations are developed exploiting an experimental data-set of 59 PaTs, obtained in both pump and turbine modes, in form of non-dimensional parameters. Data analysis shows a linear correlation between specific speeds in pump and turbine modes, as well as between specific diameters in both operating modes. In addition, the prediction of the PaT efficiency in turbine mode, whose evaluation is often disregarded in literature works, is presented: a second order polynomial equation to forecast the mechanical efficiency of PaTs in turbine mode is developed using the values of specific speed and mechanical efficiency in pump mode as independent variables. Performance experimental data of four PaTs, which were not used in the development of the model, are employed to validate and assess the accuracy of the proposed analytical equations. The prediction capability of the model is also compared to other four models available in literature. Results demonstrate a good forecast capability and a general better agreement with experimental data. A further improvement of the model can be achieved by extending the experimental data-set with additional PaTs typologies.

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  • Renzi, Massimiliano & Nigro, Alessandra & Rossi, Mosè, 2020. "A methodology to forecast the main non-dimensional performance parameters of pumps-as-turbines (PaTs) operating at Best Efficiency Point (BEP)," Renewable Energy, Elsevier, vol. 160(C), pages 16-25.
  • Handle: RePEc:eee:renene:v:160:y:2020:i:c:p:16-25
    DOI: 10.1016/j.renene.2020.05.165
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    Cited by:

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    2. 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).
    3. 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).
    4. 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).
    5. 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).
    6. Kandi, Ali & Moghimi, Mahdi & Tahani, Mojtaba & Derakhshan, Shahram, 2021. "Optimization of pump selection for running as turbine and performance analysis within the regulation schemes," Energy, Elsevier, vol. 217(C).
    7. Hongyu, Guan & Wei, Jiang & Yuchuan, Wang & Hui, Tian & Ting, Li & Diyi, Chen, 2021. "Numerical simulation and experimental investigation on the influence of the clocking effect on the hydraulic performance of the centrifugal pump as turbine," Renewable Energy, Elsevier, vol. 168(C), pages 21-30.
    8. Maxime Binama & Kan Kan & Huixiang Chen & Yuan Zheng & Daqing Zhou & Alexis Muhirwa & Godfrey M. Bwimba, 2021. "Investigation into Pump Mode Flow Dynamics for a Mixed Flow PAT with Adjustable Runner Blades," Energies, MDPI, vol. 14(9), pages 1-28, May.
    9. Wang, Tao & Xiang, Ru & Yu, He & Zhou, Min, 2023. "Performance improvement of forward-curved impeller with an adequate outlet swirl using in centrifugal pump as turbine," Renewable Energy, Elsevier, vol. 204(C), pages 67-76.

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