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Investigation on water injection characteristics and its influence on the performance of twin-screw steam compressor

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  • Tian, Yafen
  • Geng, Yanting
  • Yuan, Hao
  • Zhao, Zhaorui

Abstract

Water injected twin-screw steam compressor has great energy-saving potential in mechanical vapor compression, high temperature heat pump and steam production applications. To investigate the water injection characteristics and its influence on compressor performance under different operating conditions, a detailed thermodynamic model was developed for the working process. Heat and mass transfer between injected water and compressed vapor were considered, together with leakage of two-phase flow and power consumption of excess liquid water. Comparison between simulated results and experimental results show reasonable agreement with an error of ±5%. With the validated model, the effects of operating parameters on compressor performance and optimum injected water flowrate were investigated. Results proves water injection to be an efficient approach to improve compressor performance if properly applied. Compared with no water injection, the volumetric efficiency and isentropic efficiency with injection can be promoted by 11.9% and 17.2% respectively. As the injected water flowrate increases, the compressor efficiency firstly increases to a maximum value and then reduces when the injected flowrate is superabundant. The optimum injected water flowrate is dominated by rotating speed and nearly proportional to the rotating speed, while the optimum mass ratio of the injected water to the compressed vapor varies between 8.9% and 10.4%.

Suggested Citation

  • Tian, Yafen & Geng, Yanting & Yuan, Hao & Zhao, Zhaorui, 2022. "Investigation on water injection characteristics and its influence on the performance of twin-screw steam compressor," Energy, Elsevier, vol. 259(C).
    • Handle: RePEc:eee:energy:v:259:y:2022:i:c:s0360544222017893
    DOI: 10.1016/j.energy.2022.124886
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    References listed on IDEAS

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    Cited by:

    1. Tao Wang & Qiang Qi & Wei Zhang & Dengyi Zhan, 2023. "Research on Optimization of Profile Parameters in Screw Compressor Based on BP Neural Network and Genetic Algorithm," Energies, MDPI, vol. 16(9), pages 1-17, April.

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