Open AccessAutomatic Voltage Regulator (AVR) Optimization Based on PID Using the Hybrid Grey Wolf Optimization - Genetic Algorithm (HGWGA) Method
Author(s) -
Anas Setiawan,
Panca Mudjirahardjo,
. Wijono
Publication year - 2021
Publication title -
international journal of computer applications technology and research
Language(s) - English
Resource type - Journals
ISSN - 2319-8656
DOI - 10.7753/ijcatr1006.1002
Subject(s) - pid controller , voltage regulator , genetic algorithm , fitness function , computer science , control theory (sociology) , voltage , generator (circuit theory) , controller (irrigation) , algorithm , control engineering , control (management) , artificial intelligence , engineering , temperature control , machine learning , power (physics) , biology , physics , electrical engineering , quantum mechanics , agronomy
In the generator set (genset), the voltage stability system is affected by the excitation system controlled by control circuit called AVR (Automatic Voltage Regulator). One of the important components in the AVR system is the algorithm of the controller. The application of the PID control method has been widely used in the design of AVR controllers. This study applies the GWO-GA (Grey Wolf Optimization - Genetic Algorithm) hybrid method on PID parameters setting. The best transient automatic voltage regulator (AVR) response results were obtained when using the hybrid genetic algorithm - grey wolf optimization (HGAGW) method with a fitness score of 4.3039, the Grey wolf optimization (GWO) method with a fitness score of 4.5059, and the genetic algorithm (GA) method with a fitness score of 6.0214.