Dynamic reconfiguration of multiobjective distribution networks considering the variation of load and DG using a novel LDEDBO algorithm
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.
Authors
- Lu Wang (ORCID: https://orcid.org/0009-0009-6607-3791)
- Yanmin Wu (ORCID: https://orcid.org/0000-0001-6880-3991)
- Xiaofeng Zhang (ORCID: https://orcid.org/0000-0002-7997-0813)
- Zhenjie Wan
- Deng-Feng Fu
- Jiaqi Liu (ORCID: https://orcid.org/0009-0001-7489-4241)
- Yanjun An
Institutions
- Zhengzhou University of Light Industry (CN)
- Naval University of Engineering (CN)
- Henan University of Engineering (CN)
Publication Details
- Journal
- Scientific Reports
- Published
- 2024-12-28
- DOI
- https://doi.org/10.1038/s41598-024-83307-5
- Citations
- 7
- Primary Topic
- Microgrid Control and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 2.30
Funders
- Science and Technology Department of Henan Province