Development of a Dynamic Model of a Two-Shaft Turbine for Control Tuning and Testing

Abstract An accurate prediction of the dynamic performance of gas turbines is still of primary importance in industrial applications, both for control development and diagnostic purposes. In this study, a dynamic model of a two-shaft low-emission gas turbine based on a grey-box approach is proposed. As a first step, a grey-box static model of the turbine was developed in Matlab Simulink based a dataset of multiple simulations of a commercial tool. The results of the grey-box model turned out to be able to predict both machine performance and operating thermodynamic conditions of its components. Starting from these results, a dynamic model was developed of the machine operating in open loop conditions by using time series data from the field. Pattern search and genetic algorithms have been employed to optimize the matching between model and machine outputs. The accuracy and reliability of the dynamic model were tested by using historical data of engine performance. Finally, the model was used in a closed-loop configuration by linking the control software simulator with the system simulator in Simulink, creating a co-simulation between the two environments. This co-simulation allowed for the accurate simulation of the closed-loop system and has proven to be a solid foundation for future developments.