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Discrete evolutionary programming for network splitting strategy: Different mutation technique

Network splitting is performed to prevent the power system network from blackout event during severe cascading failures. This action will split the power system network into few islands by disconnecting the proper transmission lines. It is very important to select the optimal splitting solution (tra...

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Main Authors: Saharuddin N.Z., Abidin I.Z., Mokhlis H.
Other Authors: 55613455300
Format: Article
Published: Institute of Advanced Engineering and Science 2023
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spelling my.uniten.dspace-236782023-05-29T14:50:58Z Discrete evolutionary programming for network splitting strategy: Different mutation technique Saharuddin N.Z. Abidin I.Z. Mokhlis H. 55613455300 35606640500 8136874200 Network splitting is performed to prevent the power system network from blackout event during severe cascading failures. This action will split the power system network into few islands by disconnecting the proper transmission lines. It is very important to select the optimal splitting solution (transmission lines to be removed) to ensure that the implementation of network splitting does not cause the system to worsen. Therefore, this paper investigates two different mutation techniques; single-level and three-level mutation, utilized in Discrete Evolutionary Programming (DEP) optimization to find the optimal splitting solution following a critical line outage. Initial cutsets based heuristic technique is employed to help the convergence of the DEP optimization with minimal power flow disruptions as its fitness function. The techniques are validated using the IEEE 30 and IEEE 118-bus system. The results show that three-level mutation technique produces better optimal splitting solution as compared to single mutation technique. � 2018 Institute of Advanced Engineering and Science All rights reserved. Final 2023-05-29T06:50:58Z 2023-05-29T06:50:58Z 2018 Article 10.11591/ijeecs.v12.i1.pp261-268 2-s2.0-85051268826 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051268826&doi=10.11591%2fijeecs.v12.i1.pp261-268&partnerID=40&md5=7c5468945cd37a6d87ef65ea6e0fffc3 https://irepository.uniten.edu.my/handle/123456789/23678 12 1 261 268 All Open Access, Green Institute of Advanced Engineering and Science 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
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description Network splitting is performed to prevent the power system network from blackout event during severe cascading failures. This action will split the power system network into few islands by disconnecting the proper transmission lines. It is very important to select the optimal splitting solution (transmission lines to be removed) to ensure that the implementation of network splitting does not cause the system to worsen. Therefore, this paper investigates two different mutation techniques; single-level and three-level mutation, utilized in Discrete Evolutionary Programming (DEP) optimization to find the optimal splitting solution following a critical line outage. Initial cutsets based heuristic technique is employed to help the convergence of the DEP optimization with minimal power flow disruptions as its fitness function. The techniques are validated using the IEEE 30 and IEEE 118-bus system. The results show that three-level mutation technique produces better optimal splitting solution as compared to single mutation technique. � 2018 Institute of Advanced Engineering and Science All rights reserved.
author2 55613455300
author_facet 55613455300
Saharuddin N.Z.
Abidin I.Z.
Mokhlis H.
format Article
author Saharuddin N.Z.
Abidin I.Z.
Mokhlis H.
spellingShingle Saharuddin N.Z.
Abidin I.Z.
Mokhlis H.
Discrete evolutionary programming for network splitting strategy: Different mutation technique
author_sort Saharuddin N.Z.
title Discrete evolutionary programming for network splitting strategy: Different mutation technique
title_short Discrete evolutionary programming for network splitting strategy: Different mutation technique
title_full Discrete evolutionary programming for network splitting strategy: Different mutation technique
title_fullStr Discrete evolutionary programming for network splitting strategy: Different mutation technique
title_full_unstemmed Discrete evolutionary programming for network splitting strategy: Different mutation technique
title_sort discrete evolutionary programming for network splitting strategy: different mutation technique
publisher Institute of Advanced Engineering and Science
publishDate 2023
_version_ 1806427544627445760
score 13.211869

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