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Parametric Design of an Ultrahigh-Head Pump-Turbine Runner Based on Multiobjective Optimization

Author

Listed:
  • Linhai Liu

    (Department of Thermal Engineering, State Key Laboratory of Hydro Science and Engineering, Tsinghua University, Beijing 100084, China)

  • Baoshan Zhu

    (Department of Thermal Engineering, State Key Laboratory of Hydro Science and Engineering, Tsinghua University, Beijing 100084, China)

  • Li Bai

    (School of Energy and Power Engineering, Xihua University, Chengdu 610039, China)

  • Xiaobing Liu

    (School of Energy and Power Engineering, Xihua University, Chengdu 610039, China)

  • Yue Zhao

    (Harbin Institute of Large Electrical Machinery, Harbin 150040, China)

Abstract

Pumped hydro energy storage (PHES) is currently the only proven large-scale energy storage technology. Frequent changes between pump and turbine operations pose significant challenges in the design of a pump-turbine runner with high efficiency and stability, especially for ultrahigh-head reversible pump-turbine runners. In the present paper, a multiobjective optimization design system is used to develop an ultrahigh-head runner with good overall performance. An optimum configuration was selected from the optimization results. The effects of key design parameters—namely blade loading and blade lean—were then investigated in order to determine their effects on runner efficiency and cavitation characteristics. The paper highlights the guidelines for application of inverse design method to high-head reversible pump-turbine runners. Middle-loaded blade loading distribution on the hub, back-loaded distribution on the shroud, and large positive blade lean angle on the high pressure side are good for the improvement of runner power performance. The cavitation characteristic is mainly influenced by the blade loading distribution near the low pressure side, and large blade lean angles have a negative impact on runner cavitation characteristics.

Suggested Citation

  • Linhai Liu & Baoshan Zhu & Li Bai & Xiaobing Liu & Yue Zhao, 2017. "Parametric Design of an Ultrahigh-Head Pump-Turbine Runner Based on Multiobjective Optimization," Energies, MDPI, vol. 10(8), pages 1-16, August.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:8:p:1169-:d:107554
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    References listed on IDEAS

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    1. Pugliese, Francesco & De Paola, Francesco & Fontana, Nicola & Giugni, Maurizio & Marini, Gustavo, 2016. "Experimental characterization of two Pumps As Turbines for hydropower generation," Renewable Energy, Elsevier, vol. 99(C), pages 180-187.
    2. Zijie Wang & Baoshan Zhu & Xuhe Wang & Daqing Qin, 2017. "Pressure Fluctuations in the S-Shaped Region of a Reversible Pump-Turbine," Energies, MDPI, vol. 10(1), pages 1-13, January.
    3. Emma Frosina & Dario Buono & Adolfo Senatore, 2017. "A Performance Prediction Method for Pumps as Turbines (PAT) Using a Computational Fluid Dynamics (CFD) Modeling Approach," Energies, MDPI, vol. 10(1), pages 1-19, January.
    4. Zhu, Baoshan & Wang, Xuhe & Tan, Lei & Zhou, Dongyue & Zhao, Yue & Cao, Shuliang, 2015. "Optimization design of a reversible pump–turbine runner with high efficiency and stability," Renewable Energy, Elsevier, vol. 81(C), pages 366-376.
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    Citations

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    Cited by:

    1. Wei Yang & Benqing Liu & Ruofu Xiao, 2019. "Three-Dimensional Inverse Design Method for Hydraulic Machinery," Energies, MDPI, vol. 12(17), pages 1-19, August.
    2. Wang, Kaijie & Wang, Shuli & Meng, Puyu & Wang, Chengpeng & Li, Yuhai & Zheng, Wenxian & Liu, Jun & Kou, Jiawen, 2023. "Strategies employed in the design and optimization of pump as turbine runner," Renewable Energy, Elsevier, vol. 216(C).
    3. Hu, Jinhong & Zhao, Zhigao & He, Xianghui & Zeng, Wei & Yang, Jiebin & Yang, Jiandong, 2023. "Design techniques for improving energy performance and S-shaped characteristics of a pump-turbine with splitter blades," Renewable Energy, Elsevier, vol. 212(C), pages 333-349.
    4. Hu, Zanao & Cheng, Yongguang & Liu, Demin & Chen, Hongyu & Ji, Bin & Ding, Jinghuan, 2023. "Broadening the operating range of pump-turbine to deep-part load by runner optimization," Renewable Energy, Elsevier, vol. 207(C), pages 73-88.
    5. Jianzhong Zhou & Zhigao Zhao & Chu Zhang & Chaoshun Li & Yanhe Xu, 2017. "A Real-Time Accurate Model and Its Predictive Fuzzy PID Controller for Pumped Storage Unit via Error Compensation," Energies, MDPI, vol. 11(1), pages 1-24, December.
    6. Zhang, Yuning & Zheng, Xianghao & Li, Jinwei & Du, Xiaoze, 2019. "Experimental study on the vibrational performance and its physical origins of a prototype reversible pump turbine in the pumped hydro energy storage power station," Renewable Energy, Elsevier, vol. 130(C), pages 667-676.
    7. Rui Xiong & Hailong Li & Xuan Zhou, 2017. "Advanced Energy Storage Technologies and Their Applications (AESA2017)," Energies, MDPI, vol. 10(9), pages 1-3, September.
    8. Di Zhu & Ruofu Xiao & Ran Tao & Fujun Wang, 2018. "Designing Incidence-Angle-Targeted Anti-Cavitation Foil Profiles Using a Combination Optimization Strategy," Energies, MDPI, vol. 11(11), pages 1-15, November.
    9. Zhe Ma & Baoshan Zhu & Cong Rao & Yonghong Shangguan, 2019. "Comprehensive Hydraulic Improvement and Parametric Analysis of a Francis Turbine Runner," Energies, MDPI, vol. 12(2), pages 1-20, January.

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