Estimación de estado Dinámico en Sistemas Eléctricos de Potencia Usando Filtros Extendidos de Kalman

The method for solving State Estimation problems using extended Kalman filters in electrical power systems is presented in this work. The estimators work with real time information from different measurement devices installed in the system and form a database that is concentrated in the control center through SCADA, this information works as filters against incorrect data. The weighted least squares (WLS) technique is commonly used to solve the estimation problem due to its statistical properties. However, other dynamic state estimation techniques are structured with several variations of the Kalman filter. The Extended Kalman Filter (EKF), as an algorithm for nonlinear state estimation systems, is efficient. Implementation complexity, computational accuracy and efficiency, robustness to measurement errors, and sensitivity to system scaling are analyzed on a standard IEEE 14-bar system.