In this paper the performance of four system identification methods is evaluated for the analysis of different power system configurations. The methods considered are: nonlinear least squares (NLS), Prony method, sub-space state space system identification (N4SID) and the prediction error method (PEM). Artificially created data distorted by noise are used to represent real-world conditions. The analysis verifies the practical value of system identification methods for power system dynamic analysis and also illustrates practical issues and solutions encountered in their application.
|Number of pages||7|
|Publication status||Published - 5 Nov 2014|
- nonliner least-squares
- phasor measurements
- system identification
Papadopoulos, T. A., Kontis, E. O., Papadopoulos, P., & Papagiannis, G. K. (2014). System identification techniques for power systems analysis using distorted data. https://doi.org/10.1049/cp.2014.1653