Analysis of Extended Kalman Filter based Dynamic State Estimator’s performance under Anomalous Measurement Conditions for Power System

Abstract

State estimation, at the center of the energy man- agement system, is an important requirement for system moni- toring. It leads to better control and stability of electric power system. Accurate state estimation at faster rate is a backbone for reliable operation of vastly complex electric power system. Phasor measurement unit based measurement system makes it feasible to feed measurement data to state estimator with high throughput and good accuracy. Hence, it is possible to predict states dynamically using dynamic state estimators. In literatures, the extended Kalman filter based dynamic state estimator is suc- cessfully employed under varying noise content in measurement and measurement data update rates. It is worthwhile to observe the tracking ability in a rare condition, when measurement data are unavailable to EKF based estimator algorithm for short duration. The paper investigates the EKF’s tracking capability under such anomalous measurement conditions and result are deliberated.