TCSC Optimization for Loss Minimization in Power System Using Computational Intelligence Techniques

Minimizing power loss in transmission systems is crucial for achieving energy efficiency, lowering temperature rise and less monetary losses leading to sustainable power system network. Flexible AC Transmission Systems (FACTs) has been vastly adopted in minimizing the power loss in power transmissio...

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Published in:Lecture Notes in Electrical Engineering
Main Author: Balasubramaniam N.; Musirin I.; Kamari N.A.M.; Ibrahim A.A.
Format: Conference paper
Language:English
Published: Springer Science and Business Media Deutschland GmbH 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205104383&doi=10.1007%2f978-981-97-3851-9_27&partnerID=40&md5=646304c1f284553cbd03f951028ac348
id 2-s2.0-85205104383
spelling 2-s2.0-85205104383
Balasubramaniam N.; Musirin I.; Kamari N.A.M.; Ibrahim A.A.
TCSC Optimization for Loss Minimization in Power System Using Computational Intelligence Techniques
2024
Lecture Notes in Electrical Engineering
1213 LNEE

10.1007/978-981-97-3851-9_27
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205104383&doi=10.1007%2f978-981-97-3851-9_27&partnerID=40&md5=646304c1f284553cbd03f951028ac348
Minimizing power loss in transmission systems is crucial for achieving energy efficiency, lowering temperature rise and less monetary losses leading to sustainable power system network. Flexible AC Transmission Systems (FACTs) has been vastly adopted in minimizing the power loss in power transmission systems. However, the effectiveness of FACTs devices in achieving these benefits relies heavily on their optimal placement and sizing within the transmission system. Suboptimal solutions on FACTs devices location and sizing results to under-compensation or over-compensation, both of which are undesirable outcomes. Therefore, robust optimization techniques are necessary to attain optimal solutions. This study applies evolutionary programming (EP) and artificial immune system (AIS) as the computational intelligence techniques to examine the effects of thyristor controlled static compensators (TCSC) for loss minimization in power system. This study shows that the installation of TCSC substantially minimizes the power system loss. The IEEE 30-Bus Reliability Test System (RTS) is used to validate the proposed application and compensation scheme. The application of evolutionary programming and artificial immune system techniques provides valuable insights and solutions to power loss reduction ultimately improving the performance of transmission power systems. It was discovered that both techniques are comparable in minimizing the transmission loss in the system. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
Springer Science and Business Media Deutschland GmbH
18761100
English
Conference paper

author Balasubramaniam N.; Musirin I.; Kamari N.A.M.; Ibrahim A.A.
spellingShingle Balasubramaniam N.; Musirin I.; Kamari N.A.M.; Ibrahim A.A.
TCSC Optimization for Loss Minimization in Power System Using Computational Intelligence Techniques
author_facet Balasubramaniam N.; Musirin I.; Kamari N.A.M.; Ibrahim A.A.
author_sort Balasubramaniam N.; Musirin I.; Kamari N.A.M.; Ibrahim A.A.
title TCSC Optimization for Loss Minimization in Power System Using Computational Intelligence Techniques
title_short TCSC Optimization for Loss Minimization in Power System Using Computational Intelligence Techniques
title_full TCSC Optimization for Loss Minimization in Power System Using Computational Intelligence Techniques
title_fullStr TCSC Optimization for Loss Minimization in Power System Using Computational Intelligence Techniques
title_full_unstemmed TCSC Optimization for Loss Minimization in Power System Using Computational Intelligence Techniques
title_sort TCSC Optimization for Loss Minimization in Power System Using Computational Intelligence Techniques
publishDate 2024
container_title Lecture Notes in Electrical Engineering
container_volume 1213 LNEE
container_issue
doi_str_mv 10.1007/978-981-97-3851-9_27
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205104383&doi=10.1007%2f978-981-97-3851-9_27&partnerID=40&md5=646304c1f284553cbd03f951028ac348
description Minimizing power loss in transmission systems is crucial for achieving energy efficiency, lowering temperature rise and less monetary losses leading to sustainable power system network. Flexible AC Transmission Systems (FACTs) has been vastly adopted in minimizing the power loss in power transmission systems. However, the effectiveness of FACTs devices in achieving these benefits relies heavily on their optimal placement and sizing within the transmission system. Suboptimal solutions on FACTs devices location and sizing results to under-compensation or over-compensation, both of which are undesirable outcomes. Therefore, robust optimization techniques are necessary to attain optimal solutions. This study applies evolutionary programming (EP) and artificial immune system (AIS) as the computational intelligence techniques to examine the effects of thyristor controlled static compensators (TCSC) for loss minimization in power system. This study shows that the installation of TCSC substantially minimizes the power system loss. The IEEE 30-Bus Reliability Test System (RTS) is used to validate the proposed application and compensation scheme. The application of evolutionary programming and artificial immune system techniques provides valuable insights and solutions to power loss reduction ultimately improving the performance of transmission power systems. It was discovered that both techniques are comparable in minimizing the transmission loss in the system. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
publisher Springer Science and Business Media Deutschland GmbH
issn 18761100
language English
format Conference paper
accesstype
record_format scopus
collection Scopus
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