Simultaneous Network Reconfiguration and DG Sizing Using Evolutionary Programming and Genetic Algorithm to Minimize Power Losses
Distribution network planning and operation require the identification of the best topological configuration that is able to fulfill the power demand with minimum power loss. This paper presents an effective method based on Evolutionary Programming (EP) and Genetic Algorithm (GA) to identify the swi...
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| Format: | Article |
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Springer Verlag (Germany)
2014
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| _version_ | 1825720081249730560 |
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| author | Dahalan, W.M. Mokhlis, Hazlie Ahmad, R. Bakar, Ab Halim Abu Musirin, I. |
| author_facet | Dahalan, W.M. Mokhlis, Hazlie Ahmad, R. Bakar, Ab Halim Abu Musirin, I. |
| author_sort | Dahalan, W.M. |
| collection | UM |
| description | Distribution network planning and operation require the identification of the best topological configuration that is able to fulfill the power demand with minimum power loss. This paper presents an effective method based on Evolutionary Programming (EP) and Genetic Algorithm (GA) to identify the switching operation plan for feeder reconfiguration and distributed generation size simultaneously. The main objectives of this paper are to gain the lowest reading of real power losses, upgrade the voltage profile in the system as well as satisfying other operating constraints. Their impacts on the network real power losses and voltage profiles are investigated. A comprehensive performance analysis is carried out on IEEE 33-bus radial distribution systems to prove the efficiency of the proposed methodology. The test result on the system showed the power loss reduction, and voltage profile improvement of the EP is superior to the GA method. |
| first_indexed | 2024-03-06T05:29:34Z |
| format | Article |
| id | um.eprints-11779 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:29:34Z |
| publishDate | 2014 |
| publisher | Springer Verlag (Germany) |
| record_format | dspace |
| spelling | um.eprints-117792019-10-10T02:33:18Z http://eprints.um.edu.my/11779/ Simultaneous Network Reconfiguration and DG Sizing Using Evolutionary Programming and Genetic Algorithm to Minimize Power Losses Dahalan, W.M. Mokhlis, Hazlie Ahmad, R. Bakar, Ab Halim Abu Musirin, I. TA Engineering (General). Civil engineering (General) Distribution network planning and operation require the identification of the best topological configuration that is able to fulfill the power demand with minimum power loss. This paper presents an effective method based on Evolutionary Programming (EP) and Genetic Algorithm (GA) to identify the switching operation plan for feeder reconfiguration and distributed generation size simultaneously. The main objectives of this paper are to gain the lowest reading of real power losses, upgrade the voltage profile in the system as well as satisfying other operating constraints. Their impacts on the network real power losses and voltage profiles are investigated. A comprehensive performance analysis is carried out on IEEE 33-bus radial distribution systems to prove the efficiency of the proposed methodology. The test result on the system showed the power loss reduction, and voltage profile improvement of the EP is superior to the GA method. Springer Verlag (Germany) 2014-08 Article PeerReviewed Dahalan, W.M. and Mokhlis, Hazlie and Ahmad, R. and Bakar, Ab Halim Abu and Musirin, I. (2014) Simultaneous Network Reconfiguration and DG Sizing Using Evolutionary Programming and Genetic Algorithm to Minimize Power Losses. Arabian Journal for Science and Engineering, 39 (8). pp. 6327-6338. ISSN 1319-8025, DOI https://doi.org/10.1007/s13369-014-1299-9 <https://doi.org/10.1007/s13369-014-1299-9>. http://link.springer.com/article/10.1007%2Fs13369-014-1299-9 http://dx.doi.org/10.1007/s13369-014-1299-9 |
| spellingShingle | TA Engineering (General). Civil engineering (General) Dahalan, W.M. Mokhlis, Hazlie Ahmad, R. Bakar, Ab Halim Abu Musirin, I. Simultaneous Network Reconfiguration and DG Sizing Using Evolutionary Programming and Genetic Algorithm to Minimize Power Losses |
| title | Simultaneous Network Reconfiguration and DG Sizing Using Evolutionary Programming and Genetic Algorithm to Minimize Power Losses |
| title_full | Simultaneous Network Reconfiguration and DG Sizing Using Evolutionary Programming and Genetic Algorithm to Minimize Power Losses |
| title_fullStr | Simultaneous Network Reconfiguration and DG Sizing Using Evolutionary Programming and Genetic Algorithm to Minimize Power Losses |
| title_full_unstemmed | Simultaneous Network Reconfiguration and DG Sizing Using Evolutionary Programming and Genetic Algorithm to Minimize Power Losses |
| title_short | Simultaneous Network Reconfiguration and DG Sizing Using Evolutionary Programming and Genetic Algorithm to Minimize Power Losses |
| title_sort | simultaneous network reconfiguration and dg sizing using evolutionary programming and genetic algorithm to minimize power losses |
| topic | TA Engineering (General). Civil engineering (General) |
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