Abstract
Due to the integration of new renewable energies, the electrical grid undergoes instabilities. Hydroelectric power plants are key players for grid control thanks to pumped storage power plants. However, this objective requires extending the operating range of the machines and increasing the number of start-up, stand-by, and shut-down procedures, which reduces the lifespan of the machines. CFD based on standard URANS turbulence modeling is currently able to predict accurately the performances of the hydraulic turbines for operating points close to the Best Efficiency Point (BEP). However, far from the BEP, the standard URANS approach is less efficient to capture the dynamics of 3D flows. The current study focuses on a hydraulic turbine, which has been investigated at the BEP and at the Speed-No-Load (SNL) operating conditions. Several “advanced” URANS models such as the Scale-Adaptive Simulation (SAS) SST k - ω and the BSL- EARSM have been considered and compared with the SST k - ω model. The main conclusion of this study is that, at the SNL operating condition, the prediction of the topology and the dynamics of the flow on the suction side of the runner blade channels close to the trailing edge are influenced by the turbulence model.
Highlights
Hydropower is the main renewable source of energy generation in the world with 3.7% of the total final energy consumption [1]
This last result was used as an initial guess to compute 6.25 additional runner revolutions simulated using: the Stress Transport (SST) model with the activation of the Curvature Correction and the Production limiter (SST-CC-Plim), the SST-Organised Eddy Simulation (OES) model with a value of β∗ = 0.02, the SST-Scale-Adaptive Simulation (SAS) model, and the Baseline k − ω model (BSL)-Explicit Algebraic Reynolds Stress Models (EARSM) model
A low frequency was observed on both factors for each turbulence model except for the SST-OES model, which seemed to converge to a stable operating point
Summary
Hydropower is the main renewable source of energy generation in the world with 3.7% of the total final energy consumption [1]. Excluding the resolution of the turbulent eddies, Explicit Algebraic Reynolds Stress Models (EARSM) and Reynolds Stress Models (RSM) are able to capture the flows characterized by stagnation points and streamline curvature Such models have been used for instance by Mössinger et al [32] to compute the flow in a high head Francis turbine including part load, BEP, and full load operating conditions. They concluded that the EARSM or RSM model does not improve the results compared to the SST model. The results are compared with the ones provided by the standard SST k − ω model and with experimental data
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