Multi-objective Grasshopper Optimization Algorithm based Reconfiguration of Distribution Networks
Network reconfiguration is a nonlinear optimization procedure which calculates a radial structure to optimize the power losses and improve the network reliability index while meeting practical constraints. In this paper, a multi-objective framework is proposed for optimal network reconfiguration wit...
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| Format: | Article |
| Language: | English |
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University of Mohaghegh Ardabili
2019-10-01
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| Series: | Journal of Operation and Automation in Power Engineering |
| Subjects: | |
| Online Access: | http://joape.uma.ac.ir/article_785_448c4a5e8e4557f7608dee267f4bc684.pdf |
| _version_ | 1811267813703155712 |
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| author | M.A. Tavakoli Ghazi Jahani P. Nazarian A. Safari M.R. Haghifam |
| author_facet | M.A. Tavakoli Ghazi Jahani P. Nazarian A. Safari M.R. Haghifam |
| author_sort | M.A. Tavakoli Ghazi Jahani |
| collection | DOAJ |
| description | Network reconfiguration is a nonlinear optimization procedure which calculates a radial structure to optimize the power losses and improve the network reliability index while meeting practical constraints. In this paper, a multi-objective framework is proposed for optimal network reconfiguration with the objective functions of minimization of power losses and improvement of reliability index. The optimization problem is solved by multi-objective grasshopper optimization algorithm (MOGOA) which is one of the most modern heuristic optimization tools. To solve an optimization problem, the suggested algorithm mathematically mimics and formulates the behavior of grasshopper swarms. The modifying comfort zone coefficient needs grasshoppers to balance exploration and exploitation, which helps the MOGOA to find an exact approximation of global optimization and not trapped in local optima. The efficiency of the suggested technique is approved regarding the 33-bus and 69-bus test systems. Optimization results expressed that the suggested technique not only presents the intensified exploration ability but also has a better solution compared with previous algorithms. |
| first_indexed | 2024-04-12T21:10:33Z |
| format | Article |
| id | doaj.art-7d0487ce820444b6b8d686e2709b755a |
| institution | Directory Open Access Journal |
| issn | 2322-4576 |
| language | English |
| last_indexed | 2024-04-12T21:10:33Z |
| publishDate | 2019-10-01 |
| publisher | University of Mohaghegh Ardabili |
| record_format | Article |
| series | Journal of Operation and Automation in Power Engineering |
| spelling | doaj.art-7d0487ce820444b6b8d686e2709b755a2022-12-22T03:16:36ZengUniversity of Mohaghegh ArdabiliJournal of Operation and Automation in Power Engineering2322-45762019-10-017214815610.22098/joape.2019.5841.1437785Multi-objective Grasshopper Optimization Algorithm based Reconfiguration of Distribution NetworksM.A. Tavakoli Ghazi Jahani0P. Nazarian1A. Safari2M.R. Haghifam3Department of Electrical Engineering, Zanjan Branch, Islamic Azad University, Zanjan, Iran.Department of Electrical Engineering, Zanjan Branch, Islamic Azad University, Zanjan, Iran.Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, IranDepartment of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran.Network reconfiguration is a nonlinear optimization procedure which calculates a radial structure to optimize the power losses and improve the network reliability index while meeting practical constraints. In this paper, a multi-objective framework is proposed for optimal network reconfiguration with the objective functions of minimization of power losses and improvement of reliability index. The optimization problem is solved by multi-objective grasshopper optimization algorithm (MOGOA) which is one of the most modern heuristic optimization tools. To solve an optimization problem, the suggested algorithm mathematically mimics and formulates the behavior of grasshopper swarms. The modifying comfort zone coefficient needs grasshoppers to balance exploration and exploitation, which helps the MOGOA to find an exact approximation of global optimization and not trapped in local optima. The efficiency of the suggested technique is approved regarding the 33-bus and 69-bus test systems. Optimization results expressed that the suggested technique not only presents the intensified exploration ability but also has a better solution compared with previous algorithms.http://joape.uma.ac.ir/article_785_448c4a5e8e4557f7608dee267f4bc684.pdfReconfigurationPowe lossReliabilityMulti-objective grasshopper optimization algorithmMulti-objective optimization |
| spellingShingle | M.A. Tavakoli Ghazi Jahani P. Nazarian A. Safari M.R. Haghifam Multi-objective Grasshopper Optimization Algorithm based Reconfiguration of Distribution Networks Journal of Operation and Automation in Power Engineering Reconfiguration Powe loss Reliability Multi-objective grasshopper optimization algorithm Multi-objective optimization |
| title | Multi-objective Grasshopper Optimization Algorithm based Reconfiguration of Distribution Networks |
| title_full | Multi-objective Grasshopper Optimization Algorithm based Reconfiguration of Distribution Networks |
| title_fullStr | Multi-objective Grasshopper Optimization Algorithm based Reconfiguration of Distribution Networks |
| title_full_unstemmed | Multi-objective Grasshopper Optimization Algorithm based Reconfiguration of Distribution Networks |
| title_short | Multi-objective Grasshopper Optimization Algorithm based Reconfiguration of Distribution Networks |
| title_sort | multi objective grasshopper optimization algorithm based reconfiguration of distribution networks |
| topic | Reconfiguration Powe loss Reliability Multi-objective grasshopper optimization algorithm Multi-objective optimization |
| url | http://joape.uma.ac.ir/article_785_448c4a5e8e4557f7608dee267f4bc684.pdf |
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