PID Controller Tuning Performance Evaluation for an Isolated Power System

• Published in: 2022 IEEE International Conference on Power Systems Technology (POWERCON) pp. 1 - 6
• Main Authors: Sabo, Aliyu, Yunus, Bashir, Sani, Eeman, Nwachukwu, Matthew, Auta, Daniel, Danladi, Abdulkadir, Mordi, Michael, Aliyu, Nura, David, Yammai, Oluwadamilare, Paul
• Format: Conference Proceeding
• Language: English
• Published: IEEE 12.09.2022
• Subjects: Artificial Intelligence (AI); Artificial neural networks; Artificial Neural Networks (ANN); Genetic Algorithms (GA); Particle swarm optimization; Particle Swarm Optimization (PSO); Performance evaluation; Power system dynamics; Time-frequency analysis; Training; Transient analysis
• DOI: 10.1109/POWERCON53406.2022.9929451

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.