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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Universitas Ahmad Dahlan
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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 |
_version_ |
1809677600551862272 |