A Procedure to Identify the Linear Models of Auxiliary Controllers of a Synchronous Machine

• Published in: IEEE transactions on power systems 2018-09, Vol.33 (5), p.5006-5015
• Main Authors: Rupasinghe, B. W. H. A., Annakkage, U. D., Karawita, Chandana
• Format: Article
• Language: English
• Subjects: Analytical models; Black-boxed models; Control methods; Eigenvalues; Eigenvalues and eigenfunctions; Identification methods; Mathematical model; Mathematical models; Parameter identification; Power system stability; small signal stability analysis; Synchronous machines; System identification; transfer function identification; Transfer functions
• ISSN: 0885-8950; 1558-0679
• DOI: 10.1109/TPWRS.2018.2816851

The absence of complete model data of a power system hinders complete eigenvalue analysis of that system. System identification methods have been used to identify operating-point-dependent equivalent linear model of a power system. Such identified models do not allow a complete eigenvalue analysis. To resolve this, the identification problem can be formulated in such a way to utilize any a-priori knowledge of the system. Model data of a synchronous machine consists of machine data and controller parameters. Methods to determine synchronous machine parameters are well established. In this paper, knowledge of the machine data and knowledge of eigenvalues of the system at multiple distinct operating points, extracted by a system identification method, are used to determine auxiliary controller parameters of the synchronous machine. Model data that are determined by the proposed method is independent of the operating point. Therefore, it can be easily integrated into a complete small signal stability study at any operating point of the synchronous machine.