Joint Estimation of State and Parameter With Synchrophasors—Part II: Parameter Tracking

Abstract

An approach to joint state and parameter estimation with synchrophasor data in complex situations is presented. It consists of two loosely-coupled parts: state tracking and parameter tracking. This paper focuses on the parameter tracking and the techniques dealing with the coupling. The state tracking is presented in Part I. A new prediction model for parameters with moving means is adopted. The uncertainty in the voltages is covered by pseudo measurement errors resulting in prediction-measurement-error correlation. An error-ensemble-evolution method is proposed to evaluate the correlation. An adaptive filter based on the optimal filtering with the evaluated correlation is developed, where a sliding-window method is used to detect and adapt the moving tendency of parameters. Simulations indicate that the proposed approach yields accurate parameter estimates and improves the accuracy of the state estimation, compared with existing methods.