IDEAS home Printed from https://ideas.repec.org/r/eee/energy/v107y2016icp103-121.html

Predictive model estimating the performances of centrifugal pumps used as turbines

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Štefan, David & Rossi, Mosè & Hudec, Martin & Rudolf, Pavel & Nigro, Alessandra & Renzi, Massimiliano, 2020. "Study of the internal flow field in a pump-as-turbine (PaT): Numerical investigation, overall performance prediction model and velocity vector analysis," Renewable Energy, Elsevier, vol. 156(C), pages 158-172.
  2. 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.
  3. 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).
  4. Alemi Arani, Hamed & Fathi, Mohammad & Raisee, Mehrdad & Nourbakhsh, Seyed Ahmad, 2019. "The effect of tongue geometry on pump performance in reverse mode: An experimental study," Renewable Energy, Elsevier, vol. 141(C), pages 717-727.
  5. 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.
  6. Mauro Venturini & Stefano Alvisi & Silvio Simani & Lucrezia Manservigi, 2018. "Comparison of Different Approaches to Predict the Performance of Pumps As Turbines (PATs)," Energies, MDPI, vol. 11(4), pages 1-17, April.
  7. 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.
  8. Xiuli Mao & Andrea Dal Monte & Ernesto Benini & Yuan Zheng, 2017. "Numerical Study on the Internal Flow Field of a Reversible Turbine during Continuous Guide Vane Closing," Energies, MDPI, vol. 10(7), pages 1-22, July.
  9. 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).
  10. Zarei Manoujan, Amin & Hosseinpour, Milad & Mohebbi, Arash & Riasi, Alireza, 2025. "Technical and economic analysis of pump-as-turbine systems versus commercial turbines for harnessing energy from small water potentials," Energy, Elsevier, vol. 334(C).
  11. 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).
  12. Fengxia Shi & Xuexue Zong & Guangbiao Zhao & Denghui Zhang & Pengcheng Wang & Haonan Zhan, 2025. "Study on the Influence of Split Blades on the Force Characteristics and Fluid–Structure Coupling Characteristics of Pumps as Turbines," Energies, MDPI, vol. 18(7), pages 1-19, March.
  13. Mauro Venturini & Stefano Alvisi & Silvio Simani & Lucrezia Manservigi, 2017. "Energy Production by Means of Pumps As Turbines in Water Distribution Networks," Energies, MDPI, vol. 10(10), pages 1-13, October.
  14. Florian Julian Lugauer & Josef Kainz & Matthias Gaderer, 2021. "Techno-Economic Efficiency Analysis of Various Operating Strategies for Micro-Hydro Storage Using a Pump as a Turbine," Energies, MDPI, vol. 14(2), pages 1-18, January.
  15. Binama, Maxime & Su, Wen-Tao & Li, Xiao-Bin & Li, Feng-Chen & Wei, Xian-Zhu & An, Shi, 2017. "Investigation on pump as turbine (PAT) technical aspects for micro hydropower schemes: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 148-179.
  16. Wang, Tao & Wang, Chuan & Kong, Fanyu & Gou, Qiuqin & Yang, Sunsheng, 2017. "Theoretical, experimental, and numerical study of special impeller used in turbine mode of centrifugal pump as turbine," Energy, Elsevier, vol. 130(C), pages 473-485.
  17. Chacón, Miguel Crespo & Rodríguez Díaz, Juan Antonio & Morillo, Jorge García & McNabola, Aonghus, 2021. "Evaluation of the design and performance of a micro hydropower plant in a pressurised irrigation network: Real world application at farm-level in Southern Spain," Renewable Energy, Elsevier, vol. 169(C), pages 1106-1120.
  18. Liu, Ming & Tan, Lei & Cao, Shuliang, 2019. "Theoretical model of energy performance prediction and BEP determination for centrifugal pump as turbine," Energy, Elsevier, vol. 172(C), pages 712-732.
  19. Moghaddam, Ali & Kutschelis, Boris & Holz, Frank & Skoda, Romuald, 2024. "Experiments and three-dimensional flow simulations on twin-screw pumps operated as control valves for energy recovery," Energy, Elsevier, vol. 306(C).
  20. Shojaeefard, Mohammad Hassan & Saremian, Salman, 2022. "Effects of impeller geometry modification on performance of pump as turbine in the urban water distribution network," Energy, Elsevier, vol. 255(C).
  21. Renzi, Massimiliano & Rudolf, Pavel & Štefan, David & Nigro, Alessandra & Rossi, Mosè, 2019. "Installation of an axial Pump-as-Turbine (PaT) in a wastewater sewer of an oil refinery: A case study," Applied Energy, Elsevier, vol. 250(C), pages 665-676.
  22. Lin, Tong & Zhu, Zuchao & Li, Xiaojun & Li, Jian & Lin, Yanpi, 2021. "Theoretical, experimental, and numerical methods to predict the best efficiency point of centrifugal pump as turbine," Renewable Energy, Elsevier, vol. 168(C), pages 31-44.
  23. Shojaeefard, Mohammad Hassan & Saremian, Salman, 2024. "Analyzing the impact of blade geometrical parameters on energy recovery and efficiency of centrifugal pump as turbine installed in the pressure-reducing station," Energy, Elsevier, vol. 289(C).
  24. Rossi, Mosè & Comodi, Gabriele & Piacente, Nicola & Renzi, Massimiliano, 2020. "Energy recovery in oil refineries by means of a Hydraulic Power Recovery Turbine (HPRT) handling viscous liquids," Applied Energy, Elsevier, vol. 270(C).
  25. 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.
  26. 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.
  27. Le Marre, Maël & Mandin, Philippe & Lanoisellé, Jean-Louis & Zilliox, Erik & Rammal, Farah & Kim, Myeongsub (Mike) & Inguanta, Rosalinda, 2022. "Pumps as turbines regulation study through a decision-support algorithm," Renewable Energy, Elsevier, vol. 194(C), pages 561-570.
  28. Wang, Tao & Kong, Fanyu & Xia, Bin & Bai, Yuxing & Wang, Chuan, 2017. "The method for determining blade inlet angle of special impeller using in turbine mode of centrifugal pump as turbine," Renewable Energy, Elsevier, vol. 109(C), pages 518-528.
  29. Manoujan, Amin Zarei & Riasi, Alireza, 2024. "Optimal selection of parallel pumps running as turbines for energy harvesting in water transmission lines considering economic parameters," Applied Energy, Elsevier, vol. 359(C).
  30. Qi, Bing & Bai, Xiaobang & Li, Yibin & Wang, Xiaohui & Zhang, Xiaoze & Zhang, Desheng, 2024. "Research on the influence mechanism of internal flow characteristics on energy conversion in radial energy recovery turbines under multiple conditions," Energy, Elsevier, vol. 296(C).
  31. 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.
  32. 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).
  33. Emma Frosina & Dario Buono & Adolfo Senatore, 2017. "A Performance Prediction Method for Pumps as Turbines (PAT) Using a Computational Fluid Dynamics (CFD) Modeling Approach," Energies, MDPI, vol. 10(1), pages 1-19, January.
  34. 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.
  35. 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.
  36. Stefanizzi, Michele & Capurso, Tommaso & Balacco, Gabriella & Binetti, Mario & Camporeale, Sergio Mario & Torresi, Marco, 2020. "Selection, control and techno-economic feasibility of Pumps as Turbines in Water Distribution Networks," Renewable Energy, Elsevier, vol. 162(C), pages 1292-1306.
  37. 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.
  38. 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.
  39. Morabito, Alessandro & Hendrick, Patrick, 2019. "Pump as turbine applied to micro energy storage and smart water grids: A case study," Applied Energy, Elsevier, vol. 241(C), pages 567-579.
  40. Huang, Renfang & Zhang, Zhen & Zhang, Wei & Mou, Jiegang & Zhou, Peijian & Wang, Yiwei, 2020. "Energy performance prediction of the centrifugal pumps by using a hybrid neural network," Energy, Elsevier, vol. 213(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.