Issue |
E3S Web Conf.
Volume 320, 2021
Energy Systems Environmental Impacts (ESEI 2021)
|
|
---|---|---|
Article Number | 04008 | |
Number of page(s) | 9 | |
Section | Power Engineering | |
DOI | https://doi.org/10.1051/e3sconf/202132004008 | |
Published online | 09 November 2021 |
Prediction of Runaway Characteristics of Kaplan Turbines Using CFD Analysis
1
JSC Power Machines Saint Petersburg, Russia
2
Institute of Computational Technologies SB RAS, Novosibirsk, Russia
* Corresponding author: semenova_av@power-m.ru
In case of disconnection of generator from the network and failure of the governor, the rotational speed of the rotor rapidly increases and achieves maximum value, called the runaway speed. Prediction of the runaway speed at the stage of runner design would allow to select a runner considering this characteristic. Given in this paper is the numerical prediction of the runaway speed for a Kaplan turbine. Two approaches for numerical simulation were discussed. In the first one, the flow in the turbine flow passage was simulated using 3-D RANS equations of incompressible fluid using k-ε turbulence model. In the second approach, cavitation phenomena were taken into account using two-phase Zwart-Gerber-Belamri (ZGB) cavitation model. CFD calculations were carried out with using CADRUN flow solver. When setting the boundary conditions, the turbine head, being the difference of energies in the inlet and outlet cross-sections, is pre-set as a constant value, while the discharge and the runner torque are determined in the process of computation. The computed runaway speed is compared to that obtained in the model tests. It is shown that the numerical prediction of the runaway speed using the cavitation model achieves better matching with the experimental data.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.