Decentralized Nonlinear Adaptive Control for Multimachine Power Systems Via High-Gain Perturbation Observer

This paper presents two novel decentralized nonlinear adaptive controllers (DNAC) for large-scale interconnected power systems, via state-feedback and output-feedback strategies respectively. In the both controllers, system perturbation, which includes all subsystem nonlinearities and interactions between subsystems, is estimated by a high-gain observer and then involved the decentralized adaptive feedback linearizing control law. For the first DNAC, when all subsystem states are available, a second-order high-gain perturbation observer is designed to estimate the system perturbation, which leads to a decentralized nonlinear adaptive state-feedback controller. For the second, a decentralized nonlinear adaptive output-feedback controller is designed using a high-gain states and perturbation observer, when only one subsystem state is measured. The stability of the closed-loop controller/observer system is analyzed by the Lyapunov direct method. Both the controllers have been evaluated in a simulation study based on a three-machine power system. The results show that with a simple structure, both the controllers have robust performance of improving the transient stability and damping of multimode oscillations, under different power-system operation and fault conditions.