A novel PSS controller based on artificial neural network for damping power system oscillations Heidari Mohammadamina,1, Abadi Reaza Ashrafi Habibb aDepartment of Electrical Engineering, Fasa Branch, Islamic Azad University, Fasa, Fars, Iran bDepartment of Electrical Engineering, Natanz Branch, Islamic Azad University, Natanz, Isfahan, Iran 1Corresponding author
Online published on 31 January, 2014. Abstract Power system stabilizers (PSS) have been extensively used in large power systems for enhancing stability of the system. For this purpose there are verities of methods for determining of the controller coefficients of the system stabilizers. This paper presents a novel approach for designing a self-tuning power system stabilizer (PSS) controller based on artificial neural network (ANN). The nodes in the input layer of the ANN receive generator real power output, generator reactive power output, and generator terminal voltage. While the nodes in the output layer provide the optimum PSS parameters, e.g. stabilizing gain, time constants. Moreover Effects of changing generator real power on the parameters of the power system stabilizer is studied. Finally, in order to show effectiveness of proposed methodology some simulation results on a power system in different operational points are provided and compared with conventional PSS controller. Top Keywords Power System Stabilizers, Artificial Neural Network, Generator. Top |