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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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 |
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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. |
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55613455300 |
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55613455300 Saharuddin N.Z. Abidin I.Z. Mokhlis H. |
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Saharuddin N.Z. Abidin I.Z. Mokhlis H. |
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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 |
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Institute of Advanced Engineering and Science |
publishDate |
2023 |
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1806427544627445760 |