This paper proposes an inlet guide vane control law optimization technique for improving the off-design working condition thermal efficiency of triaxial gas turbine. Gas turbine dynamic and steady component-level simulation models are established in MATLAB/SIMULINK via Newton-Raphson algorithm based on component characteristic maps. After validating the models against experimental data and Gasturb software, they are applied to determine the effects of guide vane angle on gas turbine performance parameters.

High Efficiency Mode (HEM) is utilized to adjust the power turbine inlet guide vanes to enhance the gas turbine efficiency and decrease the specific fuel consumption under off-design working conditions on account of the above gas turbine overall performance analysis results. The optimal angles of power turbine inlet guide vanes for various working conditions are acquired based on the steady gas turbine model as-established. HEM enhances the gas turbine’s thermal efficiency without exceeding its temperature or rotational speed constraints. The Radial Basis Function (RBF), a three-layer, feedforward neural network, is employed to fit the optimal guide vane angles and establish the corresponding relationship between the angles and various working conditions by system identification. The control strategy and gas turbine dynamic simulation model are tested in MATLAB/SIMULINK to verify their effects on gas turbine performance. The guide vane angle is found to significantly influence the gas turbine operating parameters, and HEM to effectively optimize gas turbine performance even within unpredictable atmospheric environment and working conditions.

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