An intelligent system-centric control approach to power system stabilization using linear adaptive and optimal DHP controller

In this paper, we propose an intelligent approach to power system stabilization using a system-centric controller. This architecture uses a control algorithm based on a supervisory loop concept implemented with a system centric controller combining both a Dual Heuristic Programming (DHP) and Model Reference Adaptive Controller (MRAC) controller. The controller performance is tested on a Single Machine Infinite Bus (SMIB) power network and also on a five generator, eight bus, two area power network. Simulation studies indicate that the proposed controller is capable of improving the stabilization of the generator over the use of MRAC alone while continuously improving its performance through the use of online learning.