Power System Dynamic State Estimation Using Kalman Filtering Technique

Abstract

State estimation is an essential for online monitoring, control and security analysis of power systems. State estimator filters the information to get an accurate systems state. This paper presents Static and Dynamic state estimations. Weighted least square method is used for Static state estimation and Holt's exponential smoothing method as well as Kalman Filter Technique for dynamic state estimation. The accuracy of state estimation process is discussed based on the comparison of Kalman Filter technique with Holt's methods for various load conditions.