Dynamic reconfiguration of multiobjective distribution networks considering the variation of load and DG using a novel LDEDBO algorithm
Abstract To address the challenges related to active power dissipation and node voltage fluctuation in the practical transformation of power grids in the field of new energy such as wind and photovoltaic power generation, an improved Dung Beetle Optimization Algorithm Based on a Hybrid Strategy of L...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-12-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-83307-5 |
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| _version_ | 1846101351419871232 |
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| author | Yanmin Wu Lu Wang Zhenjie Wan Jiaqi Liu Dongpeng Fu Yanjun An Xiaofeng Zhang |
| author_facet | Yanmin Wu Lu Wang Zhenjie Wan Jiaqi Liu Dongpeng Fu Yanjun An Xiaofeng Zhang |
| author_sort | Yanmin Wu |
| collection | DOAJ |
| description | Abstract To address the challenges related to active power dissipation and node voltage fluctuation in the practical transformation of power grids in the field of new energy such as wind and photovoltaic power generation, an improved Dung Beetle Optimization Algorithm Based on a Hybrid Strategy of Levy Flight and Differential Evolution (LDEDBO) is proposed. This paper systematically addresses this issue from three aspects: firstly, optimizing the DBO algorithm using Chebyshev chaotic mapping, Levy flight strategy, and differential evolution algorithm; secondly, validating the algorithm’s feasibility through real-time network reconfiguration at random time points within a 24-h period; and finally, applying the LDEDBO to address the dynamic reconfiguration problems of the IEEE-33 and IEEE-69 node bus. The simulation indicates that the power dissipation of the IEEE-33 node bus is decreased by 28.94% and the minimum node voltage is elevated from 0.9273 p.u to 0.9447 p.u after the reconstruction with LDEDBO. The power dissipation of the IEEE-69 node bus is reduced by 36.45%, and the minimum node voltage is increased from 0.9224 p.u to 0.9481 p.u. The LDEDBO enhances both the pace of convergence and the precision of the optimization model, leading to a superior solution for the switching combination. |
| format | Article |
| id | doaj-art-8b76693b587a4677a63164a7deea38a4 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-8b76693b587a4677a63164a7deea38a42024-12-29T12:16:44ZengNature PortfolioScientific Reports2045-23222024-12-0114112110.1038/s41598-024-83307-5Dynamic reconfiguration of multiobjective distribution networks considering the variation of load and DG using a novel LDEDBO algorithmYanmin Wu0Lu Wang1Zhenjie Wan2Jiaqi Liu3Dongpeng Fu4Yanjun An5Xiaofeng Zhang6College of Building Environment Engineering, Zhengzhou University of Light IndustryCollege of Building Environment Engineering, Zhengzhou University of Light IndustryCollege of Building Environment Engineering, Zhengzhou University of Light IndustryCollege of Building Environment Engineering, Zhengzhou University of Light IndustrySchool of Accounting, Henan University of EngineeringCollege of Building Environment Engineering, Zhengzhou University of Light IndustryCollege of Electric Engineering, Naval University of EngineeringAbstract To address the challenges related to active power dissipation and node voltage fluctuation in the practical transformation of power grids in the field of new energy such as wind and photovoltaic power generation, an improved Dung Beetle Optimization Algorithm Based on a Hybrid Strategy of Levy Flight and Differential Evolution (LDEDBO) is proposed. This paper systematically addresses this issue from three aspects: firstly, optimizing the DBO algorithm using Chebyshev chaotic mapping, Levy flight strategy, and differential evolution algorithm; secondly, validating the algorithm’s feasibility through real-time network reconfiguration at random time points within a 24-h period; and finally, applying the LDEDBO to address the dynamic reconfiguration problems of the IEEE-33 and IEEE-69 node bus. The simulation indicates that the power dissipation of the IEEE-33 node bus is decreased by 28.94% and the minimum node voltage is elevated from 0.9273 p.u to 0.9447 p.u after the reconstruction with LDEDBO. The power dissipation of the IEEE-69 node bus is reduced by 36.45%, and the minimum node voltage is increased from 0.9224 p.u to 0.9481 p.u. The LDEDBO enhances both the pace of convergence and the precision of the optimization model, leading to a superior solution for the switching combination.https://doi.org/10.1038/s41598-024-83307-5Distribution network reconfigurationLDEDBO algorithmOptimization algorithmDynamic reconfigurationTime-varying load |
| spellingShingle | Yanmin Wu Lu Wang Zhenjie Wan Jiaqi Liu Dongpeng Fu Yanjun An Xiaofeng Zhang Dynamic reconfiguration of multiobjective distribution networks considering the variation of load and DG using a novel LDEDBO algorithm Scientific Reports Distribution network reconfiguration LDEDBO algorithm Optimization algorithm Dynamic reconfiguration Time-varying load |
| title | Dynamic reconfiguration of multiobjective distribution networks considering the variation of load and DG using a novel LDEDBO algorithm |
| title_full | Dynamic reconfiguration of multiobjective distribution networks considering the variation of load and DG using a novel LDEDBO algorithm |
| title_fullStr | Dynamic reconfiguration of multiobjective distribution networks considering the variation of load and DG using a novel LDEDBO algorithm |
| title_full_unstemmed | Dynamic reconfiguration of multiobjective distribution networks considering the variation of load and DG using a novel LDEDBO algorithm |
| title_short | Dynamic reconfiguration of multiobjective distribution networks considering the variation of load and DG using a novel LDEDBO algorithm |
| title_sort | dynamic reconfiguration of multiobjective distribution networks considering the variation of load and dg using a novel ldedbo algorithm |
| topic | Distribution network reconfiguration LDEDBO algorithm Optimization algorithm Dynamic reconfiguration Time-varying load |
| url | https://doi.org/10.1038/s41598-024-83307-5 |
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