Multiobjective reconfiguration of unbalanced distribution networks using improved transient search optimization algorithm considering power quality and reliability metrics
Abstract This paper proposes a new intelligent algorithm named improved transient search optimization algorithm (ITSOA) integrated with multiobjective optimization for determining the optimal configuration of an unbalanced distribution network. The conventional transient search optimization algorith...
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| 格式: | 文件 |
| 语言: | English |
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Nature Portfolio
2022-08-01
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| 丛编: | Scientific Reports |
| 在线阅读: | https://doi.org/10.1038/s41598-022-17881-x |
| _version_ | 1828437780286406656 |
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| author | Mohana Alanazi Abdulaziz Alanazi Ahmad Almadhor Zulfiqar Ali Memon |
| author_facet | Mohana Alanazi Abdulaziz Alanazi Ahmad Almadhor Zulfiqar Ali Memon |
| author_sort | Mohana Alanazi |
| collection | DOAJ |
| description | Abstract This paper proposes a new intelligent algorithm named improved transient search optimization algorithm (ITSOA) integrated with multiobjective optimization for determining the optimal configuration of an unbalanced distribution network. The conventional transient search optimization algorithm (TSOA) is improved with opposition learning and nonlinearly decreasing strategies for enhancing the convergence to find the global solution and obtain a desirable balance between local and global search. The multiobjective function includes different objectives such as power loss reduction, enhancement of voltage sag and unbalance, and network energy not supplied minimization. The decision variables of the reconfiguration problem including opened switches or identification of optimal network configuration are determined using ITSOA and satisfying operational and radiality constraints. The proposed methodology is implemented on unbalanced 13-bus and 118-bus networks. The results showed that the proposed ITSOA is capable to find the optimal network configuration for enhancing the different objectives in loading conditions. The results cleared the proposed methodology's good effectiveness, especially in power quality and reliability enhancement, without compromising the different objectives. Comparing ITSOA to conventional TSOA, particle swarm optimization (PSO), gray wolf optimization (GWO), bat algorithm (BA), manta ray foraging optimization (MRFO), and ant lion Optimizer (ALO), and previous approaches, it is concluded that ITSOA in improving the different objectives. |
| first_indexed | 2024-12-10T19:51:41Z |
| format | Article |
| id | doaj.art-6a78f973b034496596a9dae9c9fd40c1 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-10T19:51:41Z |
| publishDate | 2022-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-6a78f973b034496596a9dae9c9fd40c12022-12-22T01:35:45ZengNature PortfolioScientific Reports2045-23222022-08-0112111910.1038/s41598-022-17881-xMultiobjective reconfiguration of unbalanced distribution networks using improved transient search optimization algorithm considering power quality and reliability metricsMohana Alanazi0Abdulaziz Alanazi1Ahmad Almadhor2Zulfiqar Ali Memon3Department of Electrical Engineering, College of Engineering, Jouf UniversityDepartment of Electrical Engineering, College of Engineering, Northern Border UniversityDepartment of Computer Engineering and Networks, College of Computer and Information Sciences, Jouf UniversityDepartment of Electrical and Computer Engineering, College of Engineering and Information Technology, Ajman UniversityAbstract This paper proposes a new intelligent algorithm named improved transient search optimization algorithm (ITSOA) integrated with multiobjective optimization for determining the optimal configuration of an unbalanced distribution network. The conventional transient search optimization algorithm (TSOA) is improved with opposition learning and nonlinearly decreasing strategies for enhancing the convergence to find the global solution and obtain a desirable balance between local and global search. The multiobjective function includes different objectives such as power loss reduction, enhancement of voltage sag and unbalance, and network energy not supplied minimization. The decision variables of the reconfiguration problem including opened switches or identification of optimal network configuration are determined using ITSOA and satisfying operational and radiality constraints. The proposed methodology is implemented on unbalanced 13-bus and 118-bus networks. The results showed that the proposed ITSOA is capable to find the optimal network configuration for enhancing the different objectives in loading conditions. The results cleared the proposed methodology's good effectiveness, especially in power quality and reliability enhancement, without compromising the different objectives. Comparing ITSOA to conventional TSOA, particle swarm optimization (PSO), gray wolf optimization (GWO), bat algorithm (BA), manta ray foraging optimization (MRFO), and ant lion Optimizer (ALO), and previous approaches, it is concluded that ITSOA in improving the different objectives.https://doi.org/10.1038/s41598-022-17881-x |
| spellingShingle | Mohana Alanazi Abdulaziz Alanazi Ahmad Almadhor Zulfiqar Ali Memon Multiobjective reconfiguration of unbalanced distribution networks using improved transient search optimization algorithm considering power quality and reliability metrics Scientific Reports |
| title | Multiobjective reconfiguration of unbalanced distribution networks using improved transient search optimization algorithm considering power quality and reliability metrics |
| title_full | Multiobjective reconfiguration of unbalanced distribution networks using improved transient search optimization algorithm considering power quality and reliability metrics |
| title_fullStr | Multiobjective reconfiguration of unbalanced distribution networks using improved transient search optimization algorithm considering power quality and reliability metrics |
| title_full_unstemmed | Multiobjective reconfiguration of unbalanced distribution networks using improved transient search optimization algorithm considering power quality and reliability metrics |
| title_short | Multiobjective reconfiguration of unbalanced distribution networks using improved transient search optimization algorithm considering power quality and reliability metrics |
| title_sort | multiobjective reconfiguration of unbalanced distribution networks using improved transient search optimization algorithm considering power quality and reliability metrics |
| url | https://doi.org/10.1038/s41598-022-17881-x |
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