Damping Enhancement of Multi-Machine Power System Using Adaptive Generator Control System with Neural Networks

Abstract

The authors proposed a nonlinear adaptive generator control system with neural networks for improving damp-ing of power systems and showed its effectiveness in a one-machine infinite bus test power system in the previous paper. The proposed neuro-control system adaptively generates appropriate supplementary control signals to the conventional controllers such as automatic voltage regulator and speed governor so as to enhance transient stability and damping of the power system.
In this paper, the applicability of the proposed neuro-control system to multi-machine power systems is dis-cussed. Digital time simulations are carried out for a 4-machine test power system, where one or several synchronous generators are equipped with the neuro-control system. As a result, also in the multi-machine power system, the proposed adaptive neuro-control systems improve the system damping effectively and they work adaptively against the wide changes of the operating conditions and the network configuration.