An improved decentralized finite-time approach for excitation control of multi-area power systems

Abstract

The complexity of modern power systems has introduced more challenging aspects for stability. These challenges are due to the increase in stressed and constraint conditions. To resolve this issue, a novel adaptive fuzzy decentralized-based finite-time excitation control scheme has been proposed. The proposed scheme is aimed to be deployed for a large scale power systems with output and input constraint requirements. To handle these constraints, the backstepping design with a tan-type barrier Lyapunov function (BLF) is presented. Also, the parametric system uncertainties that model the power system dynamics are approximated using the fuzzy logic systems. This would eventually make the design completely decentralized due to bound-free interactions and constraints. While considering the time-varying constraint requirements on the power system outputs, a finite-time convergence of the power system output tracking errors into a small set around zero is further guaranteed. The proposed control scheme is then validated on a four-area interconnected power system subject to load fluctuations. Numerical results show the efficacy of the proposed approach.