The pressure pulsations in the vaneless space of pump-turbines are extremely intense and always experience rapid time variations during transient scenarios, causing structural vibrations and even more serious accidents. In this study, the mechanism behind the rapid time variations of the vaneless space pressure pulsations in a model pump-turbine during runaway was analyzed through three-dimensional (3D) numerical simulations. These results show that the high-frequency pressure pulsation components originating from rotor–stator interactions (RSI) are dominant during the whole process. These components fluctuate significantly in frequency when the working point goes through the S-shaped region of the characteristic curve, with the amplitudes increasing. Meanwhile, some low-frequency pulsations are also enhanced and become obvious. These features can be attributed to the transitions of the inter blade vortex structures (IBVSs) to the forward flow vortex structures (FFVSs) and the back flow vortex structures (BFVSs) at the impeller entrance, when the pump-turbine operates in the region with S-shaped characteristics. The FFVSs mainly cause decreases in frequency and introduce low-frequency pulsations, while the BFVSs are responsible for the unstable fluctuations. These findings contribute to the understanding of how transient flow patterns evolve and may provide new ideas about avoiding severe pressure pulsations caused by rotating stalls in the pump-turbine during transient scenarios.

Frequent working condition conversions in pumped-storage power stations often induce stability problems, especially when the operating point enters the S-shaped region, during which flow transitions and pressure fluctuations are serious. The pump-turbines with different specific speed values show different characteristics, but their differences in stability features are still not clear. In this study, four different pump-turbines were selected to simulate the runaway processes from turbine modes. The similarities and differences of flow patterns and pressure fluctuations were analyzed. For the similarities, pressure pulsations increase gradually and fluctuate suddenly once the backflows occur at the runner inlets. For the differences, the evolutions of backflows and pressure pulsations are related to specific speeds and runner shapes. Firstly, it is easier for the lower specific speed turbines to enter the reverse pump mode. Secondly, the blade lean angle influences the position where backflows occur, because it determines the pressure gradient at the runner inlets. Thirdly, the runner inlet height influences pressure pulsations in the vaneless space, because the relative range of backflow transitions will be enlarged with the decrease of specific speed. Overall, investigating the mechanisms of flow pattern transitions and pressure variations is important for runner design and transient process control.

Load rejection is one of the most dangerous transients in pumped-storage plants, during which cavitation in pump-turbines is normally inevitable. In this study, we applied the one-dimensional and three-dimensional coupled computational fluid dynamics method to simulate the 100% load rejection transient process of a middle-head plant, analysed the evolution and influence of cavitation cavities, and evaluated the safety. During the guide-vane closing process, a spiral-shaped cavitation cavity under the runner cone and nine wedge-shaped cavitation cavities inside the blade channel outlets occur successively. Although no water column separation happens in the draft tube inlet, the collapses of the wedge-shaped cavities induce obvious impacts on the runner, causing axial force fluctuations, to which attention should be paid in the plant design phase. This study further validated the feasibility of the coupled method and revealed the mechanism of the dynamic cavitation phenomenon, which provides references for research and engineering design.

The clearance flow around the pump-turbine runner has significant influences on unit vibrations, which may cause accidents in transient processes. The dynamic hydraulic forces and flow patterns in the clearance flow channel (CFC) of a low specific-speed pump-turbine were analyzed based on 3D CFD simulations during the runaway oscillating process. It is shown that the axial force of the runner periodically fluctuates with large amplitudes, and its components in CFC and the main flow channel (MFC) demonstrate a similar significance level. The CFC component was formulated as a function of the clearance inlet pressure and rotational speed, while the MFC component as a function of the momentum changing rate and the runner outlet pressure force. The fluctuation of runner radial force is mainly caused by the flow evolution in MFC, however, the flow in CFC aggravates it. The pressure in CFC shows a few pulsating signals from MFC, and the radial pressure drop in CFC is proportional to the square of both radius and rotational speed. In CFC, strong rotating shear flow containing a velocity core region in the circumferential direction is formed, and rotational speed is the dominant factor.

The pumped-storage power station is an efficient stability regulator of the power grid. However, due to the instability of the pump-turbine in the S-shaped characteristic region, rotational speed fluctuation is easy to occur in the speed no-load condition, making synchronization with and connection to the grid difficult. To investigate the key factors of these difficult grid connections, the start-up processes of a practical pump-turbine under the lowest head condition were simulated by using the three-dimensional CFD method, in which the governor regulating equations with different regulating parameters were integrated successfully. The results show that the working points oscillate with the fluctuations of rotational speed, discharge, and torque, and different regulating parameters have a significant influence on the dynamic histories. In addition, the internal flow patterns, especially the backflows at the runner inlet, keep apparent values at the middle span (0.5 span) but have regular transitions near the shroud side (0.7–0.8 span). The faster the guide vanes adjust, the faster the backflows change, and the larger the macro parameters fluctuate. Overall, the instability of the start-up is the result of the periodical evolutions of backflows at the runner inlet, because the trend and period of the radial velocities at different inlet span locations are consistent with those of the discharge.

Stall flow patterns occur frequently in pump turbines under off-design operating conditions. These flow patterns may cause intensive pressure pulsations, sudden increases in the hydraulic forces of the runner, or other adverse consequences, and are some of the most notable subjects in the study of pump turbines. Existing methods for identifying stall flow patterns are not, however, sufficiently objective and accurate. In this study, a convolutional neural network (CNN) is built to identify and analyze stall flow patterns. The CNN consists of input, convolutional, downsampling, fully connected, and output layers. The runner flow field data from a model pump–turbine are simulated with three-dimensional computational fluid dynamics and part of the classifiable data are used to train and test the CNN. The testing results show that the CNN can predict whether or not a blade channel is stalled with an accuracy of 100%. Finally, the CNN is used to predict the flow status of the unclassifiable part of the simulated data, and the correlation between the flow status and the relative flow rate in the runner blade channel is analyzed and discussed. The results show that the CNN is more reliable in identifying stall flow patterns than using the existing methods.