4.7 Article

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

Journal

ENERGY
Volume 267, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2022.126583

Keywords

Gas turbine; Sensitivity analysis; Semi -analytical model; Power output; Thermal efficiency

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This paper presents an improved validated semi-analytical gas turbine (GT) model that can simulate GT performance under various intake air conditions. The improved model overcomes three limitations of previous models by not assuming constant volumetric flow rate of intake air, constant output temperature of the combustion chamber (CC), and by evaluating the performance of the GT power plant directly from compressor intake air conditions. Deviations between model results and experimental data are less than 3%. Additionally, sensitivity analysis of both ambient conditions and GT characteristics is conducted as a sample application of the new model.
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.

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