Three-dimensional evolution of the flow unsteadiness in the S-shape of pump-turbines and its correlation with the runner geometry. (January 2023) - Zanetti, Giacomo; Cavazzini, Giovanna; Santolin, Alberto
Abstract: Pump-turbines (RTP) are the most common mechanical equipment adopted in pumped-hydro power plants and, for grid balancing purposes, are required to sharply switch from pumping to generating mode, and to extend their operative, jeopardizing not only the machine operability but also its life. New design approaches to avoid the onset of unstable behaviours are still far from being defined, and control strategies for accelerating start-up/shut-down procedures are still not effective since these are based on semi-empirical approaches, due to the lack of identification of precursors of the unstable behavior. In this paper, a numerical analysis of the unstable behavior of an RPT during the transition from partial load up to the turbine-brake area was carried out. The fluid-dynamics in different operating points (partial load, run-away condition, turbine brake) was deeply investigated, identifying the rotor-stator mechanisms causing the 3D evolution of the flow field leading to the development of the unstable behavior. Three evolution phases (inception, growth and consolidation) were identified and clearly correlated with the runner geometry and with the S-Shape of the RPT characteristic curve. Customized signal processing strategies were adopted for spectrally characterizing each phase so as to identify potential triggers for new monitoring and control strategies. Moreover, for the first time, a clear fluid-dynamic explanation of the empirical results found in literature on the influence of the runner geometry is provided. Highlights: Characterization of the unstable behavior of pump-turbine in the S-Shape Identification of three evolution phases: inception, growth and consolidation Definition of the correlation between fluid-dynamics and runner geometry Identification of low-frequency precursors for predictive monitoring strategies