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Performance prediction of a centrifugal pump as turbine using rotor-volute matching principle

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  • Huang, Si
  • Qiu, Guangqi
  • Su, Xianghui
  • Chen, Junrong
  • Zou, Wenlang

Abstract

A large number of studies have been reported on the prediction of head and flow rate conversion factors (h and q) at the best efficiency point (BEP) between pump and turbine mode, but the theoretical and experimental correlations are usually valid only within a certain range of specific speeds for pumps. In this paper, an innovative theoretical approach is introduced to predict the flow rate and head at BEP both for pump and turbine mode, according to the principle of characteristic matching between rotor and volute. A theoretical formula of rotor characteristic in turbine mode was derived, based on Euler equation of rotomachinery and velocity relations at the inlet and the outlet of the rotor. The formulas were accordingly obtained for predicting the flow rate and head at BEP in both pump and turbine modes. The proposed method is universally effective and practical, related to the major geometry parameters of rotor and volute without restriction of performance data and statistical/empiric range in pump mode. The proposed method was verified by experimental results of three types of pumps in both pump and turbine modes and yielded more accurate results of h and q comparing to several major predicted methods.

Suggested Citation

  • Huang, Si & Qiu, Guangqi & Su, Xianghui & Chen, Junrong & Zou, Wenlang, 2017. "Performance prediction of a centrifugal pump as turbine using rotor-volute matching principle," Renewable Energy, Elsevier, vol. 108(C), pages 64-71.
    • Handle: RePEc:eee:renene:v:108:y:2017:i:c:p:64-71
    DOI: 10.1016/j.renene.2017.02.045
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    References listed on IDEAS

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    1. Nautiyal, Himanshu & Varun & Kumar, Anoop, 2010. "Reverse running pumps analytical, experimental and computational study: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(7), pages 2059-2067, September.
    2. Yang, Sun-Sheng & Derakhshan, Shahram & Kong, Fan-Yu, 2012. "Theoretical, numerical and experimental prediction of pump as turbine performance," Renewable Energy, Elsevier, vol. 48(C), pages 507-513.
    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. Su, Xianghui & Huang, Si & Zhang, Xuejiao & Yang, Sunsheng, 2016. "Numerical research on unsteady flow rate characteristics of pump as turbine," Renewable Energy, Elsevier, vol. 94(C), pages 488-495.
    5. Jain, Sanjay V. & Patel, Rajesh N., 2014. "Investigations on pump running in turbine mode: A review of the state-of-the-art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 841-868.
    6. Arriaga, Mariano, 2010. "Pump as turbine – A pico-hydro alternative in Lao People's Democratic Republic," Renewable Energy, Elsevier, vol. 35(5), pages 1109-1115.
    7. 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.
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    Cited by:

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    13. Crespo Chacón, Miguel & Rodríguez Díaz, Juan Antonio & García Morillo, Jorge & McNabola, Aonghus, 2020. "Hydropower energy recovery in irrigation networks: Validation of a methodology for flow prediction and pump as turbine selection," Renewable Energy, Elsevier, vol. 147(P1), pages 1728-1738.
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    15. Tahani, Mojtaba & Kandi, Ali & Moghimi, Mahdi & Houreh, Shahram Derakhshan, 2020. "Rotational speed variation assessment of centrifugal pump-as-turbine as an energy utilization device under water distribution network condition," Energy, Elsevier, vol. 213(C).
    16. Pei, Yingju & Liu, Qingyou & Wang, Chuan & Wang, Guorong, 2021. "Energy efficiency prediction model and energy characteristics of subsea disc pump based on velocity slip and similarity theory," Energy, Elsevier, vol. 229(C).
    17. Rossi, Mosè & Nigro, Alessandra & Renzi, Massimiliano, 2019. "Experimental and numerical assessment of a methodology for performance prediction of Pumps-as-Turbines (PaTs) operating in off-design conditions," Applied Energy, Elsevier, vol. 248(C), pages 555-566.
    18. Binama, Maxime & Su, Wen-Tao & Cai, Wei-Hua & Li, Xiao-Bin & Muhirwa, Alexis & Li, Biao & Bisengimana, Emmanuel, 2019. "Blade trailing edge position influencing pump as turbine (PAT) pressure field under part-load conditions," Renewable Energy, Elsevier, vol. 136(C), pages 33-47.
    19. 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.
    20. Nishi, Yasuyuki & Itoh, Natsumi & Fukutomi, Junichiro, 2022. "Performance and radial thrust of single-blade reverse running pump turbine," Renewable Energy, Elsevier, vol. 201(P1), pages 499-513.
    21. 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.
    22. Rossi, Mosè & Renzi, Massimiliano, 2018. "A general methodology for performance prediction of pumps-as-turbines using Artificial Neural Networks," Renewable Energy, Elsevier, vol. 128(PA), pages 265-274.

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