Power systems are large non-linear systems that are often subject to low frequency electromechanical oscillations with a frequency of 0.5–2.5 Hz. Power system stabilizers (PSS) are commonly used as effective and economically efficient means to dampen electromechanical oscillations of generators and increase the stability of power systems. PSS can increase the power transmission stability limits by adding a stabilizing signal through the channels of the automatic excitation control system. The article presents the results of training a neural network based on which a fuzzy logic PSS is obtained for increasing the stability of electric power systems. The synchronous generator rotor speed deviation and acceleration were taken as input data for the fuzzy logic controller. These variables have a significant effect on damping the rotor's electromechanical oscillations. The characteristics of the power system equipped with the proposed fuzzy logic based PSS are compared with its characteristics with a PSS with non-optimized parameters and without a PSS.
ON-LINE IDENTIFICATION OF LOW-FREQUENCY MODES OF ELECTROMECHANICAL OSCILLATIONS IN POWER SYSTEMS