Optimal SVC allocation via symbiotic organisms search for voltage security improvement

It is desirable that a power system operation is in a normal operating condition. However, the increase of load demand in a power system has forced the system to operate near to its stability limit whereby an increase in load poses a threat to the power system security. In solving this issue, optima...

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Published in:Telkomnika (Telecommunication Computing Electronics and Control)
Main Author: Zamani M.K.M.; Musirin I.; Mustaffa S.A.S.; Suliman S.I.
Format: Article
Language:English
Published: Universitas Ahmad Dahlan 2019
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070852907&doi=10.12928%2fTELKOMNIKA.V17I3.9905&partnerID=40&md5=295fa3282943f44dabed66e8298c7626
id 2-s2.0-85070852907
spelling 2-s2.0-85070852907
Zamani M.K.M.; Musirin I.; Mustaffa S.A.S.; Suliman S.I.
Optimal SVC allocation via symbiotic organisms search for voltage security improvement
2019
Telkomnika (Telecommunication Computing Electronics and Control)
17
3
10.12928/TELKOMNIKA.V17I3.9905
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070852907&doi=10.12928%2fTELKOMNIKA.V17I3.9905&partnerID=40&md5=295fa3282943f44dabed66e8298c7626
It is desirable that a power system operation is in a normal operating condition. However, the increase of load demand in a power system has forced the system to operate near to its stability limit whereby an increase in load poses a threat to the power system security. In solving this issue, optimal reactive power support via SVC allocation in a power system has been proposed. In this paper, Symbiotic Organisms Search (SOS) algorithm is implemented to solve for optimal allocation of SVC in the power system. IEEE 26 Bus Reliability Test System is used as the test system. Comparative studies are also conducted concerning Particle Swarm Optimization (PSO) and Evolutionary Programming (EP) techniques based on several case studies. Based on the result, SOS has proven its superiority by producing higher quality solutions compared to PSO and EP. The results of this study can benefit the power system operators in planning for optimal power system operations. © 2019 Universitas Ahmad Dahlan.
Universitas Ahmad Dahlan
16936930
English
Article
All Open Access; Green Open Access; Hybrid Gold Open Access
author Zamani M.K.M.; Musirin I.; Mustaffa S.A.S.; Suliman S.I.
spellingShingle Zamani M.K.M.; Musirin I.; Mustaffa S.A.S.; Suliman S.I.
Optimal SVC allocation via symbiotic organisms search for voltage security improvement
author_facet Zamani M.K.M.; Musirin I.; Mustaffa S.A.S.; Suliman S.I.
author_sort Zamani M.K.M.; Musirin I.; Mustaffa S.A.S.; Suliman S.I.
title Optimal SVC allocation via symbiotic organisms search for voltage security improvement
title_short Optimal SVC allocation via symbiotic organisms search for voltage security improvement
title_full Optimal SVC allocation via symbiotic organisms search for voltage security improvement
title_fullStr Optimal SVC allocation via symbiotic organisms search for voltage security improvement
title_full_unstemmed Optimal SVC allocation via symbiotic organisms search for voltage security improvement
title_sort Optimal SVC allocation via symbiotic organisms search for voltage security improvement
publishDate 2019
container_title Telkomnika (Telecommunication Computing Electronics and Control)
container_volume 17
container_issue 3
doi_str_mv 10.12928/TELKOMNIKA.V17I3.9905
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070852907&doi=10.12928%2fTELKOMNIKA.V17I3.9905&partnerID=40&md5=295fa3282943f44dabed66e8298c7626
description It is desirable that a power system operation is in a normal operating condition. However, the increase of load demand in a power system has forced the system to operate near to its stability limit whereby an increase in load poses a threat to the power system security. In solving this issue, optimal reactive power support via SVC allocation in a power system has been proposed. In this paper, Symbiotic Organisms Search (SOS) algorithm is implemented to solve for optimal allocation of SVC in the power system. IEEE 26 Bus Reliability Test System is used as the test system. Comparative studies are also conducted concerning Particle Swarm Optimization (PSO) and Evolutionary Programming (EP) techniques based on several case studies. Based on the result, SOS has proven its superiority by producing higher quality solutions compared to PSO and EP. The results of this study can benefit the power system operators in planning for optimal power system operations. © 2019 Universitas Ahmad Dahlan.
publisher Universitas Ahmad Dahlan
issn 16936930
language English
format Article
accesstype All Open Access; Green Open Access; Hybrid Gold Open Access
record_format scopus
collection Scopus
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