Optimal proportional integral derivative controller for automatic voltage regulator system using particle swarm optimization algorithm

Voltage control is very important in electrical power system to ensure safe operating condition for equipment. The purpose of this project is to investigate the application of Particle Swarm Optimization (PSO) algorithm in fine-tuning the Proportional, Integral and Derivative (PID) parameter of PID...

Full description

Saved in:

Bibliographic Details
Main Author:	Wan Hassan, Wan Zakaria
Format:	Thesis
Language:	English
Published:	2015
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/48896/25/WanZakariaWanMFKE2015.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-utm-ep.48896
record_format	uketd_dc
spelling	my-utm-ep.488962020-07-05T06:58:12Z Optimal proportional integral derivative controller for automatic voltage regulator system using particle swarm optimization algorithm 2015-01 Wan Hassan, Wan Zakaria TK Electrical engineering. Electronics Nuclear engineering Voltage control is very important in electrical power system to ensure safe operating condition for equipment. The purpose of this project is to investigate the application of Particle Swarm Optimization (PSO) algorithm in fine-tuning the Proportional, Integral and Derivative (PID) parameter of PID controller for Power System’s Automatic Voltage Regulator (AVR). AVR system is employed widely in exciter control system, mainly used in areas where the supply voltage is not stable and fluctuation of load occurs. The generator excitation system maintains generator terminal voltage and controls the reactive power flow using an AVR. A practical high order and linearized Power System AVR is modelled with four main components namely Amplifier, Exciter, Generator and Sensor. The proposed PSO algorithm had superior computational efficiency, stable convergence characteristic, and easy implementation. Fast tuning of optimum PID controller parameters yields high quality solution. To estimate the performance of optimal PID controller, a fitness function that use frequency-domain and time-domain were defined. A conventional technique, Ziegler-Nichols (ZN) tuning technique was used as the comparison for proposed algorithm. Simulation result shows that PID tuned by ZN technique improved the transient response of AVR but due to high order of AVR system, it is difficult to achieve optimal PID of AVR using ZN technique which is achievable using PSO algorithm. 2015-01 Thesis http://eprints.utm.my/id/eprint/48896/ http://eprints.utm.my/id/eprint/48896/25/WanZakariaWanMFKE2015.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:86746 masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Wan Hassan, Wan Zakaria Optimal proportional integral derivative controller for automatic voltage regulator system using particle swarm optimization algorithm
description	Voltage control is very important in electrical power system to ensure safe operating condition for equipment. The purpose of this project is to investigate the application of Particle Swarm Optimization (PSO) algorithm in fine-tuning the Proportional, Integral and Derivative (PID) parameter of PID controller for Power System’s Automatic Voltage Regulator (AVR). AVR system is employed widely in exciter control system, mainly used in areas where the supply voltage is not stable and fluctuation of load occurs. The generator excitation system maintains generator terminal voltage and controls the reactive power flow using an AVR. A practical high order and linearized Power System AVR is modelled with four main components namely Amplifier, Exciter, Generator and Sensor. The proposed PSO algorithm had superior computational efficiency, stable convergence characteristic, and easy implementation. Fast tuning of optimum PID controller parameters yields high quality solution. To estimate the performance of optimal PID controller, a fitness function that use frequency-domain and time-domain were defined. A conventional technique, Ziegler-Nichols (ZN) tuning technique was used as the comparison for proposed algorithm. Simulation result shows that PID tuned by ZN technique improved the transient response of AVR but due to high order of AVR system, it is difficult to achieve optimal PID of AVR using ZN technique which is achievable using PSO algorithm.
format	Thesis
qualification_level	Master's degree
author	Wan Hassan, Wan Zakaria
author_facet	Wan Hassan, Wan Zakaria
author_sort	Wan Hassan, Wan Zakaria
title	Optimal proportional integral derivative controller for automatic voltage regulator system using particle swarm optimization algorithm
title_short	Optimal proportional integral derivative controller for automatic voltage regulator system using particle swarm optimization algorithm
title_full	Optimal proportional integral derivative controller for automatic voltage regulator system using particle swarm optimization algorithm
title_fullStr	Optimal proportional integral derivative controller for automatic voltage regulator system using particle swarm optimization algorithm
title_full_unstemmed	Optimal proportional integral derivative controller for automatic voltage regulator system using particle swarm optimization algorithm
title_sort	optimal proportional integral derivative controller for automatic voltage regulator system using particle swarm optimization algorithm
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2015
url	http://eprints.utm.my/id/eprint/48896/25/WanZakariaWanMFKE2015.pdf
_version_	1747817498206535680

Optimal proportional integral derivative controller for automatic voltage regulator system using particle swarm optimization algorithm

Similar Items