Volume 10, Issue 2 (June 2014)                   IJEEE 2014, 10(2): 124-132 | Back to browse issues page

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Gallehdari Z, Dehghani M, Nikravesh K. Online State Space Model Parameter Estimation in Synchronous Machines. IJEEE 2014; 10 (2) :124-132
URL: http://ijeee.iust.ac.ir/article-1-546-en.html
Online State Space Model Parameter Estimation in Synchronous Machines
Z. Gallehdari , M. Dehghani , K. Nikravesh
Abstract:   (5653 Views)
The purpose of this paper is to present a new approach based on the Least Squares Error method for estimating the unknown parameters of the nonlinear 3rd order synchronous generator model. The proposed method uses the mathematical relationships between the machine parameters and on-line input/output measurements to estimate the parameters of the nonlinear state space model. The field voltage is considered as the input and the rotor angle and the active power are considered as the generator outputs. In fact, the third order nonlinear state space model is converted to only two linear regression equations. Then, easy-implemented regression equations are used to estimate the unknown parameters of the nonlinear model. The suggested approach is evaluated for a sample synchronous machine model. Estimated parameters are tested for different inputs at different operating conditions. The effect of noise is also considered in this study. Simulation results show that the proposed approach provides good accuracy for parameter estimation.
Keywords: Synchronous Machine , State Space Model , Identification , Nonlinear Model , Regression Equation
Full-Text [PDF 219 kb]   (4824 Downloads)    
Type of Study: Research Paper | Subject: Parameter Estimation
Received: 2013/01/16 | Revised: 2014/06/23 | Accepted: 2014/06/23
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© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.