Dynamic State Estimation of Electric Power Systems Using Kalman Filtering Techniques

Abstract

The Kalman filter (KF) algorithm analyses power system state estimation using a number of specific equations to reduce the mean squared error. The Kalman filter is used to calculate the dynamic states of a power system network, including voltage and its angle at all buses (rotor angle) with respect to a synchronously rotating reference frame (in radians) and relative angular speed (in rad./sec) of all the generators in the system. Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) approaches were developed on the Anderson & Fouad 9-bus test power system in this proposed work, and the performance of the aforementioned techniques was examined for state estimation effectiveness.