Citation
Abstract
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.
Download File
Full text not available from this repository.
Official URL or Download Paper: https://ieeexplore.ieee.org/document/9929451
|
Additional Metadata
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Divisions: | Faculty of Engineering |
| DOI Number: | https://doi.org/10.1109/POWERCON53406.2022.9929451 |
| Publisher: | IEEE |
| Keywords: | Artificial Intelligence (AI); Artificial Neural Networks (ANN); Genetic Algorithms (GA); Particle Swarm Optimization (PSO) |
| Depositing User: | Ms. Nuraida Ibrahim |
| Date Deposited: | 28 Aug 2023 02:19 |
| Last Modified: | 29 Aug 2023 04:09 |
| Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/POWERCON53406.2022.9929451 |
| URI: | http://psasir.upm.edu.my/id/eprint/37117 |
| Statistic Details: | View Download Statistic |
Actions (login required)
 |
View Item |