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Experimental study and modelling of the ventilation power and maximum temperature of low-pressure steam turbine last stages at low load

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  • Mambro, Antonio
  • Congiu, Francesco
  • Galloni, Enzo
  • Canale, Laura

Abstract

Experimental investigations on the behavior of a low-pressure turbine operating at low volume flow have been carried out. Detailed analysis of the measurements reveal a series of macroscopic correlations useful for both understanding and modelling the whole low volume flow phenomenon. A novel concept of blade saturation temperature has been introduced, while a non-dimensional group has been identified in order to provide the best correlation with the measured ventilation power. A comparison of existing ventilation power equations has been carried out, showing a clear improvement of the proposed correlation over existing ones. Finally, a simplified approach able to predict both ventilation power and maximum flow temperature is presented.

Suggested Citation

  • Mambro, Antonio & Congiu, Francesco & Galloni, Enzo & Canale, Laura, 2019. "Experimental study and modelling of the ventilation power and maximum temperature of low-pressure steam turbine last stages at low load," Applied Energy, Elsevier, vol. 241(C), pages 59-72.
    • Handle: RePEc:eee:appene:v:241:y:2019:i:c:p:59-72
    DOI: 10.1016/j.apenergy.2019.03.003
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    References listed on IDEAS

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    1. Eser, Patrick & Singh, Antriksh & Chokani, Ndaona & Abhari, Reza S., 2016. "Effect of increased renewables generation on operation of thermal power plants," Applied Energy, Elsevier, vol. 164(C), pages 723-732.
    2. Brouwer, Anne Sjoerd & van den Broek, Machteld & Seebregts, Ad & Faaij, André, 2015. "Operational flexibility and economics of power plants in future low-carbon power systems," Applied Energy, Elsevier, vol. 156(C), pages 107-128.
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    Cited by:

    1. Sun, Lei & Liu, Tianyuan & Xie, Yonghui & Zhang, Di & Xia, Xinlei, 2021. "Real-time power prediction approach for turbine using deep learning techniques," Energy, Elsevier, vol. 233(C).

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