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A computational intelligence-based technique for the installation of multi-type facts devices

As power demand rises, the power system becomes more stressed, potentially leading to an increase in power losses. When compared to lower power losses, higher power losses result in higher power system operating cost. Flexible AC Transmission System (FACTS) devices help to reduce power losses. This...

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Main Authors: Yen W.C.M., Mansor M.H., Shaaya S.A., Musirin I.
Other Authors: 57320550100
Format: Article
Published: Semnan University, Center of Excellence in Nonlinear Analysis and Applications 2023
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spelling my.uniten.dspace-264832023-05-29T17:11:03Z A computational intelligence-based technique for the installation of multi-type facts devices Yen W.C.M. Mansor M.H. Shaaya S.A. Musirin I. 57320550100 56372667100 16022846200 8620004100 As power demand rises, the power system becomes more stressed, potentially leading to an increase in power losses. When compared to lower power losses, higher power losses result in higher power system operating cost. Flexible AC Transmission System (FACTS) devices help to reduce power losses. This paper describes the use of a computational intelligence-based technique, in this case the Artificial Immune System (AIS), to solve the installation of Thyristor Controlled Static Compensator (TCSC) and Static VAR Compensator (SVC) in a power system while ensuring optimal sizing of both devices. The goal of determining the best locations and sizes for the multi-type FACTS devices is to minimize system power loss. Three case studies are presented to investigate the effectiveness of the proposed AIS optimization technique in solving the multi-type FACTS device installation problem under various power system conditions. The optimization results generated by the proposed AIS are beneficial in improving the power system, particularly in terms of system power loss minimization, which also contributes to power system operating cost minimization. As a result, the likelihood of this being sustainable and able to be implemented for an extended period is greater. � 2021, Semnan University, Center of Excellence in Nonlinear Analysis and Applications. All rights reserved. Final 2023-05-29T09:11:03Z 2023-05-29T09:11:03Z 2021 Article 10.22075/IJNAA.2021.5571 2-s2.0-85118358012 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118358012&doi=10.22075%2fIJNAA.2021.5571&partnerID=40&md5=bde72766b267befb49be7ae8bc2c9e9e https://irepository.uniten.edu.my/handle/123456789/26483 12 Special Issue 1091 1102 Semnan University, Center of Excellence in Nonlinear Analysis and Applications Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description As power demand rises, the power system becomes more stressed, potentially leading to an increase in power losses. When compared to lower power losses, higher power losses result in higher power system operating cost. Flexible AC Transmission System (FACTS) devices help to reduce power losses. This paper describes the use of a computational intelligence-based technique, in this case the Artificial Immune System (AIS), to solve the installation of Thyristor Controlled Static Compensator (TCSC) and Static VAR Compensator (SVC) in a power system while ensuring optimal sizing of both devices. The goal of determining the best locations and sizes for the multi-type FACTS devices is to minimize system power loss. Three case studies are presented to investigate the effectiveness of the proposed AIS optimization technique in solving the multi-type FACTS device installation problem under various power system conditions. The optimization results generated by the proposed AIS are beneficial in improving the power system, particularly in terms of system power loss minimization, which also contributes to power system operating cost minimization. As a result, the likelihood of this being sustainable and able to be implemented for an extended period is greater. � 2021, Semnan University, Center of Excellence in Nonlinear Analysis and Applications. All rights reserved.
author2 57320550100
author_facet 57320550100
Yen W.C.M.
Mansor M.H.
Shaaya S.A.
Musirin I.
format Article
author Yen W.C.M.
Mansor M.H.
Shaaya S.A.
Musirin I.
spellingShingle Yen W.C.M.
Mansor M.H.
Shaaya S.A.
Musirin I.
A computational intelligence-based technique for the installation of multi-type facts devices
author_sort Yen W.C.M.
title A computational intelligence-based technique for the installation of multi-type facts devices
title_short A computational intelligence-based technique for the installation of multi-type facts devices
title_full A computational intelligence-based technique for the installation of multi-type facts devices
title_fullStr A computational intelligence-based technique for the installation of multi-type facts devices
title_full_unstemmed A computational intelligence-based technique for the installation of multi-type facts devices
title_sort computational intelligence-based technique for the installation of multi-type facts devices
publisher Semnan University, Center of Excellence in Nonlinear Analysis and Applications
publishDate 2023
_version_ 1806427963505246208
score 13.211869

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