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Experimental and numerical assessment of a methodology for performance prediction of Pumps-as-Turbines (PaTs) operating in off-design conditions

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

Abstract

In this work, an extensive assessment of a predicting model used to evaluate Pumps-as-Turbines’ (PaTs) characteristic curves is presented, with specific attention to the off-design operating conditions. The novelty of the proposed model consists in the possibility to reconstruct the performance curves of a PaT only by knowing a limited number of operating data in turbine mode at the Best Efficiency Point (BEP), which, in many applications, represents a design constraint. The availability of the off-design performance curves supplies important indications for technical and economic evaluations in those applications where a constant flow rate cannot be granted. The predicting model was derived by re-elaborating a wide experimental data-set based on the most relevant scientific literature related to several PaTs operating in turbine mode. The prediction’s capability of the model was validated with experimental tests and confirmed by numerical simulations. The experimental tests were carried on in both direct and reverse modes by inspecting several flow rates. The model data were compared with the experimental ones in order to validate the Computational Fluid Dynamics (CFD) analyses. Subsequently, the numerical model was used to investigate the performances of other two PaTs operating in turbine mode. The study of the performance obtained with the CFD analyses allowed to evaluate the effectiveness of the predicting model, highlighting its pros together with its possible improvements. In general, it is possible to conclude that the proposed model is able to predict the performances of the studied PaTs with errors included in the range of ±7% with respect to the Best Efficiency Point (BEP) in turbine mode.

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  • 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.
  • Handle: RePEc:eee:appene:v:248:y:2019:i:c:p:555-566
    DOI: 10.1016/j.apenergy.2019.04.123
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    References listed on IDEAS

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    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. 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).
    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. 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.
    5. 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).
    6. 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).
    7. Postacchini, Matteo & Di Giuseppe, Elisa & Eusebi, Anna Laura & Pelagalli, Leonardo & Darvini, Giovanna & Cipolletta, Giulia & Fatone, Francesco, 2022. "Energy saving from small-sized urban contexts: Integrated application into the domestic water cycle," Renewable Energy, Elsevier, vol. 199(C), pages 1300-1317.
    8. 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.
    9. 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).
    10. 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.
    11. 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).
    12. Diamantis Karakatsanis & Nicolaos Theodossiou, 2022. "Smart Hydropower Water Distribution Networks, Use of Artificial Intelligence Methods and Metaheuristic Algorithms to Generate Energy from Existing Water Supply Networks," Energies, MDPI, vol. 15(14), pages 1-21, July.
    13. Longyan Wang & Stephen Ntiri Asomani & Jianping Yuan & Desmond Appiah, 2020. "Geometrical Optimization of Pump-As-Turbine (PAT) Impellers for Enhancing Energy Efficiency with 1-D Theory," Energies, MDPI, vol. 13(16), pages 1-30, August.
    14. 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.
    15. Frank A Plua & Francisco-Javier Sánchez-Romero & Victor Hidalgo & P. Amparo López-Jiménez & Modesto Pérez-Sánchez, 2021. "New Expressions to Apply the Variation Operation Strategy in Engineering Tools Using Pumps Working as Turbines," Mathematics, MDPI, vol. 9(8), pages 1-17, April.
    16. 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.
    17. Andrade Furtado, Gilton Carlos de & Amarante Mesquita, André Luiz & Morabito, Alessandro & Hendrick, Patrick & Hunt, Julian D., 2020. "Using hydropower waterway locks for energy storage and renewable energies integration," Applied Energy, Elsevier, vol. 275(C).
    18. 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.
    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. Jacopo Carlo Alberizzi & Massimiliano Renzi & Maurizio Righetti & Giuseppe Roberto Pisaturo & Mosè Rossi, 2019. "Speed and Pressure Controls of Pumps-as-Turbines Installed in Branch of Water-Distribution Network Subjected to Highly Variable Flow Rates," Energies, MDPI, vol. 12(24), pages 1-18, December.

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