On Line Electric Power Systems State Estimation Using Kalman Filtering (RESEARCH NOTE)

Abstract

In this paper principles of extended Kalman filtering theory is developed and applied to simulated on-line electric power systems state estimation in order to trace the operating condition changes through the redundant and noisy measurements. Test results on IEEE 14 - bus test system are included. Three case systems are tried; through the comparing of their results, it is concluded that the proposed dynamic estimator have great advantage over the static state estimation in its accuracy and real time implementation.