Development of a Cavitation Indicator for Prediction of Failure in Pump-As-Turbines Using Numerical Simulation

Maciej Janiszkiewicz and Aonghus McNabola ()
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Maciej Janiszkiewicz: Department of Civil, Structural and Environmental Engineering, Trinity College Dublin, D02 PN40 Dublin, Ireland
Aonghus McNabola: School of Engineering, RMIT University, 124 La Trobe Street, Melbourne, VIC 3000, Australia

Energies, 2025, vol. 18, issue 16, 1-21

Abstract: The increasing deployment of pumps-as-turbines in small-scale hydropower applications in off-design conditions strengthens the need for the monitoring of the operation and maintenance (O&M) needs. PATs (pumps-as-turbines, pumps operated in reverse to generate electric current) are increasingly used because of their low cost as micro-hydropower plants; however, limited research has focused on their maintenance needs during operation. This is an important consideration given their use under conditions for which they were not originally designed. One of the most challenging O&M issues in hydromachinery is cavitation, which can harm turbines and reduce their efficiency. In this study, Computational Fluid Dynamics (CFD) was used for 15 different simulations of PAT configurations and their cavitation behaviour was investigated under varying inlet pressure and mass flow conditions. A cavitation strength indicator was developed using linear regression, describing the strength of cavitation from 0 (no cavitation) to 100 (extreme cavitation). This parameter depends on mass flow rate and head, which are easily measured parameters using standard sensors. With this approach, it is possible to monitor cavitation status in a continuous manner in a working PAT without the need for complex sensors. With this application, it is also possible to avoid costly damage, shutting down turbines when cavitation strength is exceptionally high.

Keywords: pumps-as-turbine; cavitation; CFD; hydropower; condition monitoring (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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