A Dynamic Estimator for Tracking the State of a Power System

Abstract

The problem of real-time estimation of the state of a power system is treated from the point of view of the theory of least-squares estimation (Kalman-Bucy filtering). Since under normal operating conditions, the power system behaves in a quasi- static manner, a simple model for the time behavior of the power system is derived. This model, together with the real-time measurement system, enables the design of a tracking state-estimator algorithm. The proposed algorithm has several advantages over the previously suggested static estimator algorithm in regard to its computational aspects, real-time implementation, and the accuracy of the estimated state.