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Performance analysis of large-scale industrial gas turbine considering stable combustor operation using novel blended fuel

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  • Park, Yeseul
  • Choi, Minsung
  • Kim, Dongmin
  • Lee, Joongsung
  • Choi, Gyungmin

Abstract

The allowable Wobbe index (WI) range proposed by gas turbine companies spans from 0 to 5%. System tuning is required when out-of-range fuel is used. In this study, thermodynamic analysis is conducted to study the gas turbine performance and operability of each component with the fuel exceeding 5% of WI. The novel diluting fuel supply system is employed to apply novel fuel compositions for the J-class gas turbine system. High-hydrocarbon and hydrogen blending fuels are used to study the operability and main parameters of each component. The largest diluent mass flow is required when 100% hydrogen fuel is used with nitrogen diluent method. The compressor cannot be operated with 100% hydrogen fuel due to the compressor surge. The maximum turbine blade temperature with steam diluent methods increases up to 80 °C. The power output and efficiency are enhanced with the increasing blending ratio of high-hydrocarbon and hydrogen employing two diluent methods. When the novel fuel supply system is considered for the stable operability of combustor, both its power and efficiency are increased; however, the operability of compressor and turbine is not always stable, especially with hydrogen fuel.

Suggested Citation

  • Park, Yeseul & Choi, Minsung & Kim, Dongmin & Lee, Joongsung & Choi, Gyungmin, 2021. "Performance analysis of large-scale industrial gas turbine considering stable combustor operation using novel blended fuel," Energy, Elsevier, vol. 236(C).
    • Handle: RePEc:eee:energy:v:236:y:2021:i:c:s036054422101656x
    DOI: 10.1016/j.energy.2021.121408
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    1. Park, Yeseul & Choi, Minsung & Choi, Gyungmin, 2023. "Thermodynamic performance study of large-scale industrial gas turbine with methane/ammonia/hydrogen blended fuels," Energy, Elsevier, vol. 282(C).
    2. Yan, Peiliang & Fan, Weijun & Zhang, Rongchun, 2023. "Predicting the NOx emissions of low heat value gas rich-quench-lean combustor via three integrated learning algorithms with Bayesian optimization," Energy, Elsevier, vol. 273(C).
    3. Park, Yeseul & Li, Xinzhuo & Choi, Minsung & Kim, Dongmin & Lee, Joongsung & Choi, Gyungmin, 2022. "Fuel interchangeability investigation of new Russian PNG for conventional gas appliances," Energy, Elsevier, vol. 260(C).
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    5. Skabelund, Brent B. & Stechel, Ellen B. & Milcarek, Ryan J., 2023. "Thermodynamic analysis of a gas turbine utilizing ternary CH4/H2/NH3 fuel blends," Energy, Elsevier, vol. 282(C).

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