Design of optimal multi-objective-based facts component with proportional-integral-derivative controller using swarm optimization approach

This study proposes a multi-objective-based swarm intelligence method to improve angle stability. An optimization operation with single objective function only improves the performance of one perspective and ignores the other. The combination of two objective functions which derived from real and im...

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Main Authors: Khawaja, Abdul Waheed, Nor Azwan, Mohamed Kamari, Ismail, Musirin, Mohd Asyraf, Zulkifley, Muhamad Zahim, Sujod
Format: Article
Language:English
Published: Accent Social and Welfare Society 2021
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/32369/1/Design%20of%20optimal%20multi-objective-based%20facts%20component.pdf
http://umpir.ump.edu.my/id/eprint/32369/
http://dx.doi.org/10.19101/IJATEE.2020.762132
http://dx.doi.org/10.19101/IJATEE.2020.762132
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Institution: Universiti Malaysia Pahang
Language: English
id my.ump.umpir.32369
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spelling my.ump.umpir.323692021-11-10T04:31:33Z http://umpir.ump.edu.my/id/eprint/32369/ Design of optimal multi-objective-based facts component with proportional-integral-derivative controller using swarm optimization approach Khawaja, Abdul Waheed Nor Azwan, Mohamed Kamari Ismail, Musirin Mohd Asyraf, Zulkifley Muhamad Zahim, Sujod TK Electrical engineering. Electronics Nuclear engineering This study proposes a multi-objective-based swarm intelligence method to improve angle stability. An optimization operation with single objective function only improves the performance of one perspective and ignores the other. The combination of two objective functions which derived from real and imaginary components of eigenvalue are able to provide better performance beyond the optimization capabilities of single objective function. Tested using MATLAB, the simulation is performed using a single machine attached to the infinite bus (SMIB) system equipped with static var compensator (SVC) that attached with PID controller (SVC-PID). The objective of this experiment is to explore the excellent parameters in SVC-PID to produce a more stable system. In addition to the comparison of objective functions, this study also compares particle swarm optimization (PSO) capabilities with evolutionary programming (EP) and artificial immune system (AIS) techniques. Accent Social and Welfare Society 2021-02 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/32369/1/Design%20of%20optimal%20multi-objective-based%20facts%20component.pdf Khawaja, Abdul Waheed and Nor Azwan, Mohamed Kamari and Ismail, Musirin and Mohd Asyraf, Zulkifley and Muhamad Zahim, Sujod (2021) Design of optimal multi-objective-based facts component with proportional-integral-derivative controller using swarm optimization approach. International Journal of Advanced Technology and Engineering Exploration, 8 (75). 391 -404. ISSN 2394-5443 http://dx.doi.org/10.19101/IJATEE.2020.762132 http://dx.doi.org/10.19101/IJATEE.2020.762132
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Khawaja, Abdul Waheed
Nor Azwan, Mohamed Kamari
Ismail, Musirin
Mohd Asyraf, Zulkifley
Muhamad Zahim, Sujod
Design of optimal multi-objective-based facts component with proportional-integral-derivative controller using swarm optimization approach
description This study proposes a multi-objective-based swarm intelligence method to improve angle stability. An optimization operation with single objective function only improves the performance of one perspective and ignores the other. The combination of two objective functions which derived from real and imaginary components of eigenvalue are able to provide better performance beyond the optimization capabilities of single objective function. Tested using MATLAB, the simulation is performed using a single machine attached to the infinite bus (SMIB) system equipped with static var compensator (SVC) that attached with PID controller (SVC-PID). The objective of this experiment is to explore the excellent parameters in SVC-PID to produce a more stable system. In addition to the comparison of objective functions, this study also compares particle swarm optimization (PSO) capabilities with evolutionary programming (EP) and artificial immune system (AIS) techniques.
format Article
author Khawaja, Abdul Waheed
Nor Azwan, Mohamed Kamari
Ismail, Musirin
Mohd Asyraf, Zulkifley
Muhamad Zahim, Sujod
author_facet Khawaja, Abdul Waheed
Nor Azwan, Mohamed Kamari
Ismail, Musirin
Mohd Asyraf, Zulkifley
Muhamad Zahim, Sujod
author_sort Khawaja, Abdul Waheed
title Design of optimal multi-objective-based facts component with proportional-integral-derivative controller using swarm optimization approach
title_short Design of optimal multi-objective-based facts component with proportional-integral-derivative controller using swarm optimization approach
title_full Design of optimal multi-objective-based facts component with proportional-integral-derivative controller using swarm optimization approach
title_fullStr Design of optimal multi-objective-based facts component with proportional-integral-derivative controller using swarm optimization approach
title_full_unstemmed Design of optimal multi-objective-based facts component with proportional-integral-derivative controller using swarm optimization approach
title_sort design of optimal multi-objective-based facts component with proportional-integral-derivative controller using swarm optimization approach
publisher Accent Social and Welfare Society
publishDate 2021
url http://umpir.ump.edu.my/id/eprint/32369/1/Design%20of%20optimal%20multi-objective-based%20facts%20component.pdf
http://umpir.ump.edu.my/id/eprint/32369/
http://dx.doi.org/10.19101/IJATEE.2020.762132
http://dx.doi.org/10.19101/IJATEE.2020.762132
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