Kalman filtering with a new state-space model for three-phase systems: Application to the identification of symmetrical components

Abstract

In electrical energy transportation challenges, power quality issues like reducing harmonic pollution, reactive power and load unbalance, necessarily have to identify the symmetrical components of the three phases in a fast and precise way. This paper introduces a new state-space model to be used with an Extended Kalman Filter (EKF) in order to estimate in real-time the symmetrical components of distorted and time-changing power systems. The proposed model is therefore able to detect and to quantify the unbalance of general three-phase power systems. Indeed, the symmetrical components of the power system, i.e., their amplitude and phase angle values, can be deduced at each iteration from the proposed state-space model. The effectiveness of the method has been evaluated. Results and comparisons of online symmetrical components identification show the efficiency of the proposed method for disturbed and changing power systems.