The Extended Kalman Filter and the Particle Filter in the Dynamic State Estimation of Electrical Power Systems

Abstract

The state estimation (SE) and the load flow (LF) are critical subjects in the analysis and management of electrical power systems (EPS). This article provides a solution for dynamic state estimation (DSE) in EPS based in the Particle Filter (PF) and the Extended Kalman Filter (EKF) that uses the Holt method to linearize the process model. The performance of the methods was analyzed through the comparison of the results considering the error index (ε). In this work, an IEEE 14 and 30 buses test cases were utilized. The results show that the PF method has better accuracy than the EKF method.