The purpose of this paper is to propose the intelligent controller of an SSSC to damp the inter-area power system oscillations.

Design/methodology/approach: This intelligent controller is based on adjusting the PID’s gains using auto-tuning neurons. The main difference of an auto-tuning neuron and a typical neuron is that parameters of the activation function employed in an auto-tuning neuron can be adjusted. In this paper, the activation function of auto-tuning neurons is a modified hyperbolic tangent function which has two adjustable parameters to flexibly determine the magnitude and the shape of function. Such auto-tuning neurons are then utilized to find gains of the PID controller which is tuned in on-line mode by using certain adaptation laws.

Findings: The proposed controller is used to damp the inter-area oscillations of a two-area four-machine power system. The simulation results are employed to demonstrate the performance of the proposed controller. It is shown that proposed approach can damp the power system oscillations in different situation of the power system. Simplicity and practicality of the proposed controller with its excellent performance make it ideal to be implemented in real excitation systems.

Originality/value: The proposed approach is interesting for the design of an intelligent control scheme based on non-linear model to damp the inter-area oscillations. In this suggested controller, the system conditions and requirements adjust the PID gains. In other words, to damp the inter-area oscillations, PID gains are intelligently set by the auto-tuning neurons. The main contributions of this paper are: the overall control system is globally stable and hence, the inter-area oscillations of the power system are mitigated; the control error can be reduced to zero by appropriate chosen parameters; and the proposed controller can achieve favorable controlling performance.

The purpose of this paper is to propose the intelligent controller of an SSSC to damp the inter-area power system oscillations.