An adaptive fuzzy controller gain scheduling for power system load-frequency control

In this paper, an adaptive fuzzy controller gain scheduling scheme for power system load-frequency control is designed to damp the frequency oscillations and to track its error to zero at steady state. A Sugeno type inference system is used in the proposed controller to adapt the scaling gains of a single fuzzy controller through a classical on-line monitoring of the most sensitive parameters of the system. The proposed controller avoids excessive patterns and training time compared to neural network based adaptive schemes. A typical single-area nonreheat power system is considered. Simulation results indicate that the proposed controller is insensitive to parameter changes in a wide range of operating condition, and to the generation rate constraints. Furthermore, it is simple to implement.