Neural-network-based adaptive control with application to power systems

This paper first addresses the power system stability issue involving the regular, generator-angle, transient stability and load-driven voltage instability. Transient stabilization of simplified power systems equipped with a FACTS device, the thyristor controlled series capacitor, is studied with the consideration of the unknown load. A number of novel techniques are developed to synthesize robust, near-time-optimal, neurocontrollers. The simulations illustrate the performance of the synthesized neural controllers. The results developed can be readily generalized to more general nonlinear systems