Dynamic reconfiguration of multiobjective distribution networks considering the variation of load and DG using a novel LDEDBO algorithm

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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Bibliographic Details
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
Subjects:
Distribution network reconfiguration
LDEDBO algorithm
Optimization algorithm
Dynamic reconfiguration
Time-varying load
Online Access:https://doi.org/10.1038/s41598-024-83307-5
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Summary: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.
ISSN:2045-2322

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