Application of system identification techniques to modelling a turbogenerator

The paper is concerned with the derivation of low-order linear models of a turbogenerator from test data. Data are obtained using a computer-based data-acquisition system, which injects small disturbances to the set points of plant controllers and monitors the response of the unit. The information is processed by identification algorithms, to provide models of the plant dynamics over a range of operating conditions. These state-space models can be obtained online, and provide a basis for multivariable control system design. Tests were performed on a 271 MW unit, onload and connected to the grid. The results include comparisons of plant and model responses and show that accurate models were obtained.