Visual Validation of Estimated Parametric Models of Power Systems Under Ambient Conditions

Abstract

With the advent of synchrophasors, a number of measurement–based algorithms have been developed to estimate system modes using ambient data. The accuracy of these mode estimates depends on a number of factors, such as selection of the system order and data channels. To validate these mode estimates, two methods are proposed in this paper based on how well they agree with the observed data using the estimated parametric system model and observed data. In the proposed methods, the contribution of each mode estimate is analyzed to obtain a combination of system mode estimates to represent the model. The methodology of the proposed methods are illustrated using least–squares ARMA (LS–ARMA) method, which gives a parametric system model estimates. Results obtained by implementing the proposed methods on measured and simulated data validate the effectiveness of the proposed methods.