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An improved semi-analytical model for evaluating performance of gas turbine power plants

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  • Pourhedayat, Samira
  • Hu, Eric
  • Chen, Lei

Abstract

The hot intake air would compromise the power generation performance of a gas turbine (GT). Therefore, GT pre-cooling technologies are studied and applied for GT plants. This paper proposes an improved validated semi-analytical GT model, which can be used to simulate the performance of GT plants under a wide range of intake air conditions. The new model developed is improved, compared to previous models, in the following three aspects: 1) the volumetric flow rate of intake air is no longer assumed to be constant when the temperature of intake air changes; 2) the output temperature of the combustion chamber (CC) is no longer assumed to be a constant either, but depending on air temperature/humidity into the CC and the fuel/air ratio, and 3) the improved model can evaluate the performance of the GT power plant, in terms of power output and thermal efficiency of the plant, directly and explicitly from the intake air conditions of the compressor, which was not possible in the previous models. Deviations between results of the present model and experimental data are less than 3%. In addition, sensitivity analysis of both ambient conditions and GT characteristics is performed as a sample application of the new model which is programed using Engineering Equation Solver (EES) software.

Suggested Citation

  • Pourhedayat, Samira & Hu, Eric & Chen, Lei, 2023. "An improved semi-analytical model for evaluating performance of gas turbine power plants," Energy, Elsevier, vol. 267(C).
    • Handle: RePEc:eee:energy:v:267:y:2023:i:c:s0360544222034703
    DOI: 10.1016/j.energy.2022.126583
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    References listed on IDEAS

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    1. Zongming Yang & Mykola Radchenko & Andrii Radchenko & Dariusz Mikielewicz & Roman Radchenko, 2022. "Gas Turbine Intake Air Hybrid Cooling Systems and a New Approach to Their Rational Designing," Energies, MDPI, vol. 15(4), pages 1-18, February.
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    1. Gong, Linjuan & Hou, Guolian & Li, Jun & Gao, Haidong & Gao, Lin & Wang, Lin & Gao, Yaokui & Zhou, Junbo & Wang, Mingkun, 2023. "Intelligent fuzzy modeling of heavy-duty gas turbine for smart power generation," Energy, Elsevier, vol. 277(C).

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