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: Yanmin Wu, Lu Wang, Zhenjie Wan, Jiaqi Liu, Dongpeng Fu, Yanjun An, Xiaofeng Zhang
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-024-83307-5
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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.
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institution Kabale University
issn 2045-2322
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publishDate 2024-12-01
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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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