On-line adaptive assessment of the synchronizing and damping torque coefficients using Kalman filtering

Abstract

This paper presents an on-line optimal approach for dynamic stability assessment of a single-machine infinite-bus system. The approach is based on estimating the synchronizing and damping torque coefficients of the synchronous machine using a two-state linear Kalman filter. The coefficients are estimated from the time responses of the changes in the rotor angle, rotor speed, and electromagnetic torque. These coefficients can be used as indices to provide insight into the relative stability of the synchronous machine. The two indices can also predict the possible unstable conditions and hence help the operator to take the correct control action beforehand. The performance of the Kalman filter is compared with the least-square error technique. The effect of system noise on the performance of the Kalman filter is also investigated. Compared with the least square technique, the paper shows that the Kalman filter offers several advantages. This includes significant reduction in computing time and storage needed for the estimation of the synchronizing and damping torque coefficients and its robustness in dealing with noisy measurements. This approach results in a remarkable reduction in the computational complexity associated with this problem and hence allows for on-line implementation needed for continuous monitoring of the dynamic stability indices.