Design of a power system stabilizer using decentralized adaptive model following tracking control approach

This paper presents the design of a power system stabilizer using decentralized adaptive model following tracking control (DAMFTC) approach to damp oscillations of generators in transient response subjected to uncertainties and generating fault actuators. The power system is represented as a collection of interconnected dynamical subsystems each described by a set of differential/algebraic equations using a clear representation of load voltage magnitude with matched and unmatched time-varying uncertainties. All adaptive learning algorithms in this control system are derived in the sense of Lyapunov stability analysis subject to state errors due to uncertainties and fault section, so that stability and robustness of the closed-loop system are ensured and asymptotic-state tracking can be achieved. An adaptive bound estimation algorithm is investigated to relax the requirement for the bound of uncertainties. The effectiveness of the proposed approach is demonstrated by distributing a detailed simulation of the three-machine nine-bus system with nonlinear interactions, uncertainties, and fault actuators. The simulation includes the effects of network and stator transients. Copyright (C) 2009 John Wiley & Sons, Ltd.