Network reconfiguration and optimal distributed generations allocation with whale optimizer algorithm
Power distribution networks have become more interested in Distributed Generations (DG) due to their potential for reducing power loss and improving system dependability. Discovering the optimal site, size, and reconfiguration strategy for a DG-based distribution network using a metaheuristic algor...
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| Language: | English |
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OICC Press
2025-03-01
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| Series: | Majlesi Journal of Electrical Engineering |
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| Online Access: | https://oiccpress.com/mjee/article/view/10854 |
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| author | Ahmadreza Abdollahi Chirani |
| author_facet | Ahmadreza Abdollahi Chirani |
| author_sort | Ahmadreza Abdollahi Chirani |
| collection | DOAJ |
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Power distribution networks have become more interested in Distributed Generations (DG) due to their potential for reducing power loss and improving system dependability. Discovering the optimal site, size, and reconfiguration strategy for a DG-based distribution network using a metaheuristic algorithm is the main goal of this study. The multi-objective and multi-constrained feature of the Whale Optimization Algorithm (WOA) makes it a useful optimization technique for network reconfiguration. In this paper, the forward-backward load flow technique is employed due to its easy implementation, quick and reliable convergence. The recommended approach is validated through two different test systems. Four different scenarios are considered. Improvements in power loss reduction and voltage profile illustrate the effectiveness of the proposed technique. The obtained results showed that DG allocation after network reconfiguration resulted in a greater reduction of power losses and refinement of the voltage profile of the network. Also, a comparison is employed with other optimization methods, it can be seen that the suggested method’s performance is clearly superior, as shown by the numerical data. Losses were reduced by 67.8% and 63.21% on IEEE 33 and 69 bus systems, respectively, when using the suggested strategy. All the simulations are conducted through MATLAB.
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| format | Article |
| id | doaj-art-9cd14401c1014ceb9166bb9d90d1fee2 |
| institution | OA Journals |
| issn | 2345-377X 2345-3796 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | OICC Press |
| record_format | Article |
| series | Majlesi Journal of Electrical Engineering |
| spelling | doaj-art-9cd14401c1014ceb9166bb9d90d1fee22025-08-20T02:26:09ZengOICC PressMajlesi Journal of Electrical Engineering2345-377X2345-37962025-03-01191 (March 2025)10.57647/j.mjee.2025.1901.04Network reconfiguration and optimal distributed generations allocation with whale optimizer algorithmAhmadreza Abdollahi Chirani0https://orcid.org/0000-0002-6903-4378Faculty of Engineering, University of Guilan, Rasht, Iran Power distribution networks have become more interested in Distributed Generations (DG) due to their potential for reducing power loss and improving system dependability. Discovering the optimal site, size, and reconfiguration strategy for a DG-based distribution network using a metaheuristic algorithm is the main goal of this study. The multi-objective and multi-constrained feature of the Whale Optimization Algorithm (WOA) makes it a useful optimization technique for network reconfiguration. In this paper, the forward-backward load flow technique is employed due to its easy implementation, quick and reliable convergence. The recommended approach is validated through two different test systems. Four different scenarios are considered. Improvements in power loss reduction and voltage profile illustrate the effectiveness of the proposed technique. The obtained results showed that DG allocation after network reconfiguration resulted in a greater reduction of power losses and refinement of the voltage profile of the network. Also, a comparison is employed with other optimization methods, it can be seen that the suggested method’s performance is clearly superior, as shown by the numerical data. Losses were reduced by 67.8% and 63.21% on IEEE 33 and 69 bus systems, respectively, when using the suggested strategy. All the simulations are conducted through MATLAB. https://oiccpress.com/mjee/article/view/10854Distribution generationPower loss reductionReconfigurationVoltage profile improvementWhale optimizer algorithm |
| spellingShingle | Ahmadreza Abdollahi Chirani Network reconfiguration and optimal distributed generations allocation with whale optimizer algorithm Majlesi Journal of Electrical Engineering Distribution generation Power loss reduction Reconfiguration Voltage profile improvement Whale optimizer algorithm |
| title | Network reconfiguration and optimal distributed generations allocation with whale optimizer algorithm |
| title_full | Network reconfiguration and optimal distributed generations allocation with whale optimizer algorithm |
| title_fullStr | Network reconfiguration and optimal distributed generations allocation with whale optimizer algorithm |
| title_full_unstemmed | Network reconfiguration and optimal distributed generations allocation with whale optimizer algorithm |
| title_short | Network reconfiguration and optimal distributed generations allocation with whale optimizer algorithm |
| title_sort | network reconfiguration and optimal distributed generations allocation with whale optimizer algorithm |
| topic | Distribution generation Power loss reduction Reconfiguration Voltage profile improvement Whale optimizer algorithm |
| url | https://oiccpress.com/mjee/article/view/10854 |
| work_keys_str_mv | AT ahmadrezaabdollahichirani networkreconfigurationandoptimaldistributedgenerationsallocationwithwhaleoptimizeralgorithm |