PID Controller Tuning Performance Evaluation for an Isolated Power System

In this work, an isolated power system requiring a Load Frequency Control (LFC) by the application of a PID controller is designed in the MATLAB/Simulink environment. To acquire the PID gain parameters for an optimum dynamic load frequency control, several optimization procedures are applied. Genetic algorithms (GA) and Particle Swarm Optimization (PSO) technique were used to determine the proportional gain (KP), integral gain (KI), and deferential gain (KD) of the controller. Artificial Neural Network (ANN) training was is also caried out for the PID tuning and the comparative analysis of the results obtained shows that the Particle Swarm optimization (PSO) has the best performance, with an overshoot of 0.58 percent and a settling time of 0.52 seconds.