Dynamic Performance Simulation of an Aeroderivative Gas Turbine Using the Matlab Simulink Environment

Abstract

In fossil fuel applications, such as air transportation and power generation systems, gas turbine is the prime mover which governs the aircraft’s propulsive and the plant’s thermal efficiency, respectively. Therefore, an accurate engine performance simulation has a significant impact on the operation and maintenance of gas turbines as far as reliability and availability considerations are concerned. Current trends in achieving stable engine operation, reliable fault diagnosis and prognosis requirements do motivate the development and implementation of real-time dynamic simulators for gas turbines that are sufficiently complex, highly nonlinear, have high fidelity and include fast response modules. This paper presents a gas turbine performance model for predicting the transient dynamic behavior of an aeroderivative engine that is suitable for both mechanical drive and power generation applications. The engine model has been developed in the Matlab/Simulink environment and combines both the inter-component volume and the constant mass flow methods. Dynamic equations of the mass momentum and the energy balance are incorporated into the steady state thermodynamic equations. This allows one to represent the engine model by a set of first order differential and algebraic equations. The developed Simulink model in an object oriented environment, can be easily adapted to any kind of gas turbine configuration. The model consists of a number of subsystems for representing the gas turbine’s components and the thermodynamic relationships among them. The components are represented by a set of suitable performance maps that are available from the open literature. The engine model has been validated with an established gas turbine performance simulation software. Time responses of the main variables that describe the gas turbine dynamic behavior are also included. The proposed gas turbine model with its dynamic simulation characteristics is a useful tool for development of real-time model-based diagnostics and prognostics technologies.