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Performance improvement of a 500-kW Francis turbine based on CFD

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  • Teran, Leonel Alveyro
  • Larrahondo, Francisco Jose
  • Rodríguez, Sara Aida

Abstract

In this work, a Computational Fluid Dynamics (CFD) analysis was performed to obtain a new geometry that provides increased efficiency in a 500-kW Francis turbine. This analysis was developed in two parts: The first stage of the work was focused on the elements of the turbine that are not related to the runner’s blade profile, such as the covers, the stay vanes/guide vanes and certain zones of the runner. The second stage of the work was focused on improving the blade profile. To this end, due to the complexity of the geometry, a methodology that combines factorial experiments, Artificial Neural Networks (ANN), and optimizations based on Genetic Algorithms (GA) was implemented. In the first stage of the process, the modifications increased the efficiency by six points. In the second stage, the recirculation of fluid and the cavitation phenomenon in the runner blade were reduced, the latter being the main cause of wear in the current runner. The final geometry was simulated in a CFD solver, which predicted an increase of 14.77% in the efficiency of the current point for the highest power. Finally, static strength, fatigue and resonance were verified in turbine components affected by the modifications.

Suggested Citation

  • Teran, Leonel Alveyro & Larrahondo, Francisco Jose & Rodríguez, Sara Aida, 2016. "Performance improvement of a 500-kW Francis turbine based on CFD," Renewable Energy, Elsevier, vol. 96(PA), pages 977-992.
    • Handle: RePEc:eee:renene:v:96:y:2016:i:pa:p:977-992
    DOI: 10.1016/j.renene.2016.05.044
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    References listed on IDEAS

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    1. Kumar, Pardeep & Saini, R.P., 2010. "Study of cavitation in hydro turbines--A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(1), pages 374-383, January.
    2. Choi, Hyen-Jun & Zullah, Mohammed Asid & Roh, Hyoung-Woon & Ha, Pil-Su & Oh, Sueg-Young & Lee, Young-Ho, 2013. "CFD validation of performance improvement of a 500 kW Francis turbine," Renewable Energy, Elsevier, vol. 54(C), pages 111-123.
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    Citations

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    Cited by:

    1. Laouari, Ahmed & Ghenaiet, Adel, 2021. "Investigation of steady and unsteady cavitating flows through a small Francis turbine," Renewable Energy, Elsevier, vol. 172(C), pages 841-861.
    2. Yu, Zhi-Feng & Wang, Wen-Quan & Yan, Yan & Liu, Xing-Shun, 2021. "Energy loss evaluation in a Francis turbine under overall operating conditions using entropy production method," Renewable Energy, Elsevier, vol. 169(C), pages 982-999.
    3. Gabl, Roman & Innerhofer, Daniel & Achleitner, Stefan & Righetti, Maurizio & Aufleger, Markus, 2018. "Evaluation criteria for velocity distributions in front of bulb hydro turbines," Renewable Energy, Elsevier, vol. 121(C), pages 745-756.
    4. Zhang, Han & Gao, Xueping & Sun, Bowen & Qin, Zixue & Zhu, Hongtao, 2020. "Parameter analysis and performance optimization for the vertical pipe intake-outlet of a pumped hydro energy storage station," Renewable Energy, Elsevier, vol. 162(C), pages 1499-1518.
    5. Geng, Xinmin & Zhou, Ye & Zhao, Weiqiang & Shi, Li & Chen, Diyi & Bi, Xiaojian & Xu, Beibei, 2024. "Pricing ancillary service of a Francis hydroelectric generating system to promote renewable energy integration in a clean energy base: Tariff compensation of deep peak regulation," Renewable Energy, Elsevier, vol. 226(C).
    6. Teran, L.A. & Aponte, R.D. & Muñoz-Cubillos, J. & Roa, C.V. & Coronado, J.J. & Ladino, J.A. & Larrahondo, F.J. & Rodríguez, S.A., 2016. "Analysis of economic impact from erosive wear by hard particles in a run-of-the-river hydroelectric plant," Energy, Elsevier, vol. 113(C), pages 1188-1201.
    7. Xuanlin Peng & Jianzhong Zhou & Chu Zhang & Ruhai Li & Yanhe Xu & Diyi Chen, 2017. "An Intelligent Optimization Method for Vortex-Induced Vibration Reducing and Performance Improving in a Large Francis Turbine," Energies, MDPI, vol. 10(11), pages 1-17, November.

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