Comparative analysis of bacterial foraging optimization algorithm and evolutionary programming for load shedding in power system

This paper presents a comparative analysis of Bacterial Foraging Optimization Algorithm (BFOA) and Evolutionary Programming (EP) in determining the locations and amount of load to be shed in power systems for optimal load shedding. Load shedding is done by removing a certain amount of loads at appoi...

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書目詳細資料
發表在:International Journal of Simulation: Systems, Science and Technology
主要作者: 2-s2.0-85017215654
格式: Article
語言:English
出版: UK Simulation Society 2017
在線閱讀:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85017215654&doi=10.5013%2fIJSSST.a.17.41.18&partnerID=40&md5=b648a46a892db1c4189585771a1ad147
id Wan Afandie W.N.E.A.; Rahman T.K.A.; Zakaria Z.
spelling Wan Afandie W.N.E.A.; Rahman T.K.A.; Zakaria Z.
2-s2.0-85017215654
Comparative analysis of bacterial foraging optimization algorithm and evolutionary programming for load shedding in power system
2017
International Journal of Simulation: Systems, Science and Technology
17
41
10.5013/IJSSST.a.17.41.18
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85017215654&doi=10.5013%2fIJSSST.a.17.41.18&partnerID=40&md5=b648a46a892db1c4189585771a1ad147
This paper presents a comparative analysis of Bacterial Foraging Optimization Algorithm (BFOA) and Evolutionary Programming (EP) in determining the locations and amount of load to be shed in power systems for optimal load shedding. Load shedding is done by removing a certain amount of loads at appointed locations of a bus system. By doing so, the stability of the system can be improved, as well as the total power losses. The objective functions of total power losses and voltage stability index values are used in determining the optimal load shedding in that particular system. In this research, the technique is implemented into IEEE 30-bus bus system. Simulations of BFAO proved that a better result can be obtained than EP when compared to the base case values of total power losses and voltage stability index values of that particular bus system. Results obtained from BFOA are also compared with Evolutionary Programing to determine the performance. © 2017, UK Simulation Society. All rights reserved.
UK Simulation Society
14738031
English
Article

author 2-s2.0-85017215654
spellingShingle 2-s2.0-85017215654
Comparative analysis of bacterial foraging optimization algorithm and evolutionary programming for load shedding in power system
author_facet 2-s2.0-85017215654
author_sort 2-s2.0-85017215654
title Comparative analysis of bacterial foraging optimization algorithm and evolutionary programming for load shedding in power system
title_short Comparative analysis of bacterial foraging optimization algorithm and evolutionary programming for load shedding in power system
title_full Comparative analysis of bacterial foraging optimization algorithm and evolutionary programming for load shedding in power system
title_fullStr Comparative analysis of bacterial foraging optimization algorithm and evolutionary programming for load shedding in power system
title_full_unstemmed Comparative analysis of bacterial foraging optimization algorithm and evolutionary programming for load shedding in power system
title_sort Comparative analysis of bacterial foraging optimization algorithm and evolutionary programming for load shedding in power system
publishDate 2017
container_title International Journal of Simulation: Systems, Science and Technology
container_volume 17
container_issue 41
doi_str_mv 10.5013/IJSSST.a.17.41.18
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85017215654&doi=10.5013%2fIJSSST.a.17.41.18&partnerID=40&md5=b648a46a892db1c4189585771a1ad147
description This paper presents a comparative analysis of Bacterial Foraging Optimization Algorithm (BFOA) and Evolutionary Programming (EP) in determining the locations and amount of load to be shed in power systems for optimal load shedding. Load shedding is done by removing a certain amount of loads at appointed locations of a bus system. By doing so, the stability of the system can be improved, as well as the total power losses. The objective functions of total power losses and voltage stability index values are used in determining the optimal load shedding in that particular system. In this research, the technique is implemented into IEEE 30-bus bus system. Simulations of BFAO proved that a better result can be obtained than EP when compared to the base case values of total power losses and voltage stability index values of that particular bus system. Results obtained from BFOA are also compared with Evolutionary Programing to determine the performance. © 2017, UK Simulation Society. All rights reserved.
publisher UK Simulation Society
issn 14738031
language English
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