Abstract :
Recently there has been increasing interest shown in utilising self-tuning control for stability enhancement of power systems. This paper proposes a new method of designing a self-tuning stabiliser for excitation or governor control for stability enhancement of power systems. In this method, a linear discrete-time model of preassumed order is used for the stabiliser design. Based on this model, a modified version of a conventional quadratic performance index is so defined that upon minimization, the resulting optimal stabiliser possesses an additional derivative term not found in the conventional stabiliser. The method also employs the recursive least squares algorithm for the purpose of estimating the model parameters every sampling interval. Based on the latest parameter estimate, the optimal stabilising signal is computed and applied to the power system under control. The proposed strategy is, therefore, self-tuning. Fig. 1 shows the block diagram of the proposed strategy for self-tuning excitation or governor control of a power system. An advantage of the derivative control term is that it possesses an anticipatory characteristic and initiates an early stabilising action. Consequently, the proposed self-tuning stabiliser is suitable for improving the damping characteristics of power systems. In fact, simulation results show that the damping characteristics of a power system, under different disturbances and over a wide range of operating conditions, can be enhanced when the proposed stabiliser is applied to the excitation or governor loop. Fig. 2 shows a set of typical nonlinear test results.
