Blind Identification of the Electromechanical Modes of a Power System using a Wiener Model
Abstract
In this thesis, a blind system identification technique using a Wiener model is used to estimate the power system modes. A Wiener model, a universal approximator consisting of a dynamic linear system followed by a memoryless nonlinear element, is used to estimate the power system nonlinearities. It also constructs a set of intermediate data, which can be used by a linear estimation technique such as subspace identification for estimating the power system electromechanical modes. In this research, a blind variant of a subspace method, Numerical Algorithm for Subspace State Space System IDentification (N4SID), is used.
The algorithm is tested with simulation data from the Kundur two-area network. The accuracy and reliability of these estimates are accessed by carrying out Monte Carlo simulations. The estimated results obtained from the simulated system using a Wiener model were very accurate with reduced prediction errors and was a good fit for the power system.
Description
Keywords
Engineering--Electronics and Electrical
Citation
Hossain, T. (2016). Blind Identification of the Electromechanical Modes of a Power System using a Wiener Model (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/25148