Performance comparison of adaptive estimation techniques for power system small-signal stability assessment

Abstract EN

This paper demonstrates the assessment of the small-signal stability of a single-machine infinite- bus power system under widely varying loading conditions using the concept of synchronizing and damping torques coefficients.

The coefficients are calculated from the time responses of the rotor angle, speed, and torque of the synchronous generator.

Three adaptive computation algorithms including Kalman filtering, Adaline, and recursive least squares have been compared to estimate the synchronizing and damping torque coefficients.

The steady-state performance of the three adaptive techniques is compared with the conventional static least squares technique by conducting computer simulations at different loading conditions.

The algorithms are compared to each other in terms of speed of convergence and accuracy.

The recursive least squares estimation offers several advantages including significant reduction in computing time and computational complexity.

The tendency of an unsupplemented static exciter to degrade the system damping for medium and heavy loading is verified.

Consequently, a power system stabilizer whose parameters are adjusted to compensate for variations in the system loading is designed using phase compensation method.

The effectiveness of the stabilizer in enhancing the dynamic stability over wide range of operating conditions is verified through the calculation of the synchronizing and damping torque coefficients using recursive least square technique.