Reconfiguration and displacement of DG and EVs in distribution networks using a hybrid GA–SFLA multi-objective optimization algorithm
A combined algorithm for reconfiguring and placement of energy storage systems, electric vehicles, and distributed generation (DG) in a distribution network is presented in this paper. The impact of this technique on increasing the network’s resilience during critical periods is investigated, as wel...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-12-01
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| Series: | Frontiers in Energy Research |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenrg.2023.1304055/full |
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| author | Yazeed Yasin Ghadi Hossam Kotb Kareem M. Aboras Mohammed Alqarni Amr Yousef Amr Yousef Masoud Dashtdar Abdulaziz Alanazi |
| author_facet | Yazeed Yasin Ghadi Hossam Kotb Kareem M. Aboras Mohammed Alqarni Amr Yousef Amr Yousef Masoud Dashtdar Abdulaziz Alanazi |
| author_sort | Yazeed Yasin Ghadi |
| collection | DOAJ |
| description | A combined algorithm for reconfiguring and placement of energy storage systems, electric vehicles, and distributed generation (DG) in a distribution network is presented in this paper. The impact of this technique on increasing the network’s resilience during critical periods is investigated, as well as improvements in the network’s technical and economic characteristics. The three objective functions in this regard are the network losses, voltage profile, and running costs, which include the costs of purchasing electrical energy from the upstream network and the devices used, as well as the cost of load shedding. In addition, the impacts of the presence of DG on power flow and the modeling of the problem’s objective function are examined. To solve the problem of reconfiguration and placement of a multi-objective distribution feeder, a genetic algorithm (GA) and shuffled frog leaping algorithm (SFLA) hybrid algorithm is used. The proposed GA–SFLA algorithm is used to solve the problem with changes in its structure and its combination in three stages. Finally, the proposed method is implemented on the 33-bus distribution network. The simulation results show that the proposed method has an effective performance in improving the considered objective functions and by establishing a suitable fit between the different objective functions based on the three-dimensional Pareto front. Moreover, it introduced a more optimized architecture with lower loss, lower operating costs, and greater reliability compared to other optimization algorithms. |
| first_indexed | 2024-03-08T22:07:45Z |
| format | Article |
| id | doaj.art-a7431eca36284139b40e1292423df31e |
| institution | Directory Open Access Journal |
| issn | 2296-598X |
| language | English |
| last_indexed | 2024-03-08T22:07:45Z |
| publishDate | 2023-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Energy Research |
| spelling | doaj.art-a7431eca36284139b40e1292423df31e2023-12-19T08:07:55ZengFrontiers Media S.A.Frontiers in Energy Research2296-598X2023-12-011110.3389/fenrg.2023.13040551304055Reconfiguration and displacement of DG and EVs in distribution networks using a hybrid GA–SFLA multi-objective optimization algorithmYazeed Yasin Ghadi0Hossam Kotb1Kareem M. Aboras2Mohammed Alqarni3Amr Yousef4Amr Yousef5Masoud Dashtdar6Abdulaziz Alanazi7Department of Computer Science and Software Engineering, Al Ain University, Abu Dhabi, United Arab EmiratesDepartment of Electrical Power and Machines, Faculty of Engineering, Alexandria University, Alexandria, EgyptDepartment of Electrical Power and Machines, Faculty of Engineering, Alexandria University, Alexandria, EgyptElectrical Engineering Department, University of Business and Technology, Jeddah, Saudi ArabiaElectrical Engineering Department, University of Business and Technology, Jeddah, Saudi ArabiaEngineering Mathematics Department, Faculty of Engineering, Alexandria University, Alexandria, EgyptDepartment of Electrical Engineering, Faculty of Sciences and Technologies Fez, Sidi Mohamed Ben Abdullah University, Fes, MoroccoDepartment of Electrical Engineering, College of Engineering, Northern Border University, Arar, Saudi ArabiaA combined algorithm for reconfiguring and placement of energy storage systems, electric vehicles, and distributed generation (DG) in a distribution network is presented in this paper. The impact of this technique on increasing the network’s resilience during critical periods is investigated, as well as improvements in the network’s technical and economic characteristics. The three objective functions in this regard are the network losses, voltage profile, and running costs, which include the costs of purchasing electrical energy from the upstream network and the devices used, as well as the cost of load shedding. In addition, the impacts of the presence of DG on power flow and the modeling of the problem’s objective function are examined. To solve the problem of reconfiguration and placement of a multi-objective distribution feeder, a genetic algorithm (GA) and shuffled frog leaping algorithm (SFLA) hybrid algorithm is used. The proposed GA–SFLA algorithm is used to solve the problem with changes in its structure and its combination in three stages. Finally, the proposed method is implemented on the 33-bus distribution network. The simulation results show that the proposed method has an effective performance in improving the considered objective functions and by establishing a suitable fit between the different objective functions based on the three-dimensional Pareto front. Moreover, it introduced a more optimized architecture with lower loss, lower operating costs, and greater reliability compared to other optimization algorithms.https://www.frontiersin.org/articles/10.3389/fenrg.2023.1304055/fullmulti-objective functionsenergy storagedistributed generationelectric vehiclesreconfigurationplacement |
| spellingShingle | Yazeed Yasin Ghadi Hossam Kotb Kareem M. Aboras Mohammed Alqarni Amr Yousef Amr Yousef Masoud Dashtdar Abdulaziz Alanazi Reconfiguration and displacement of DG and EVs in distribution networks using a hybrid GA–SFLA multi-objective optimization algorithm Frontiers in Energy Research multi-objective functions energy storage distributed generation electric vehicles reconfiguration placement |
| title | Reconfiguration and displacement of DG and EVs in distribution networks using a hybrid GA–SFLA multi-objective optimization algorithm |
| title_full | Reconfiguration and displacement of DG and EVs in distribution networks using a hybrid GA–SFLA multi-objective optimization algorithm |
| title_fullStr | Reconfiguration and displacement of DG and EVs in distribution networks using a hybrid GA–SFLA multi-objective optimization algorithm |
| title_full_unstemmed | Reconfiguration and displacement of DG and EVs in distribution networks using a hybrid GA–SFLA multi-objective optimization algorithm |
| title_short | Reconfiguration and displacement of DG and EVs in distribution networks using a hybrid GA–SFLA multi-objective optimization algorithm |
| title_sort | reconfiguration and displacement of dg and evs in distribution networks using a hybrid ga sfla multi objective optimization algorithm |
| topic | multi-objective functions energy storage distributed generation electric vehicles reconfiguration placement |
| url | https://www.frontiersin.org/articles/10.3389/fenrg.2023.1304055/full |
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