Abstract
This study suggests a new method for online enhancement of multimachine system stability. Two steps centered on adjusting power system stabilizers (PSSs) are examined. Firstly, the PSS parameters are tuned off-line using an elitist optimization technique based on genetic algorithms symbolized by NSGAII over a large set of operating conditions. NSGAII was employed to move all electromechanical modes in a pre-specified area in the s-plan. Then, a flexible fuzzy logic-based neural network is proposed to adjust the parameters of the PSSs at any operating condition that can be outside the offline set by exploiting the off-line results. The suggested controllers are tested by using multi-machine system over some scenarios of serious faults and system configurations. Simulations results show the efficiency and sturdiness of the suggested stabilizers in enhancing the overall system dynamics in realtime at any loading condition selected arbitrarily. (C) 2017 The Authors. Published by IASE.