Simulation Of Generators Operating In Parallel And Adaptive Control Of Generator Excitation Systems

Generator excitation control for multi-machine systems is helpful to improve the stability of power systems. Developing a mathematical and simulation model of the representative two-machine system is very helpful in both understanding the operating state and studying the stability of the independent system. In recent years, lots of advanced control methods are successfully used in the Synchronous generator excitation control system, PID controller is widely used in industrial control systems. According to the characteristics of strong nonlinearity, load disturbance and timevarying uncertainty, conventional PID control schemes cannot meet the high quality requirement of excitation control for two-machine systems. For the above reason, it is very important to research adaptive PID controller from theoretical and practical point of view.In this paper, in order to describe the nonlinear characteristic of the simulation system, a five-order synchronous generator model is analyzed and a simulation model of a two-machine system is build using Matlab/Simulink. A Resource Allocation Network(RAN) based neural PID adaptive generator excitation control is proposed for two-machine systems. The parameters of the PID controller can be adjusted dynamically according to the RAN-enabled online model. For the two-machine system, the neural PID control are simulated and the effectiveness of this novel approach is illustrated by simulation results. In order to explain the input and output logically, a fuzzy self-turning controller is designed to control the two-machine systems. For the two-machine system, IEEE Type 1 excitation control, neural PID control and fuzzy self-turning PID control are simulated and compared. The simulation results show that the self-turning PID controller has good robustness and antijamming ability.