PSS Tuning of the Combined Cycle Power Station by Neural Network
نویسندگان
چکیده
This paper presents a parameter modeling to Power System Stabilizers (PSS) using MLP and RBF neural networks. The application of neural networks in PSS aims to improve the dynamic stability of electric power systems by reducing the machine eletromechanic damping oscillation when a disturbance occurs. According to the current plant operating conditions, the PSS parameters are automatically adjusted by the neural network in sense to give a satisfactory control. The observed performance for the proposed approach is tested in simulations, using a nonlinear dynamic model of infinite bus machine-type. The results show that it is possible to improve the power system dynamic performance with the new modeling.
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