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Damping enhancement of multimachine power system using adaptive generator control system with neural networks
Authors:Takenori Kobayashi  Yasuo Morioka  Akihiko Yokoyama
Abstract:The authors proposed a nonlinear adaptive generator control system with neutral networks for improving damping of power systems, and showed its effectiveness in a one-machine infinite bus test power system in a previous paper. The proposed neurocontrol system adaptively generates appropriate supplementary control signals to the conventional controllers such as the 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 neurocontrol system to multimachine power systems is discussed. Digital time simulations are carried out for a 4-machine test power system, where one or several synchronous generators is equipped with the neurocontrol system. As a result, also in the multimachine power system, the proposed adaptive neurocontrol systems improve the system damping effectively and they work adaptively against the wide changes of the operating conditions and the network configuration.
Keywords:Neural network  generator control  multimachine power system  damping enhancement  adaptive control  multivariable control  decentralized control
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