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Optimization of distribution system operation by network reconfiguration and DG integration using MPSO algorithm

机译:利用MPSO算法通过网络重新配置和DG集成优化分配系统运行

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摘要

This paper introduces a Mixed Particle Swarm Optimization (MPSO) approach for active power loss minimization and voltage profile improvement in the distribution network. The developed technique joins the Binary Particle Swarm Optimization (BPSO) and the conventional PSO algorithms. The first one is devoted to identify the optimal distribution network configuration, while the second one is used to solve Distributed Generation (DG) placement and sizing problems. To evaluate the performance of the developed approach, three different load scenarios were assessed during network reconfiguration (NR) and DG integration. Simulations are conducted on two distribution test systems, namely, the IEEE-33-bus and the IEEE-69-bus. The obtained results clearly demonstrate the performance and the effectiveness of the proposed method to find optimal status of switches, as well as DG locations and sizes. A benchmark comparison is presented to prove the efficiency of the proposed MPSO with regard to other optimization techniques. The results show that MPSO outperforms these techniques in terms of quality of solution, power loss reduction and voltage profile enhancement. This study is an extension of the earlier published conference paper.
机译:本文介绍了一种混合粒子群优化(MPSO)方法,用于分配网络的有源功率损耗最小化和电压型材改进。开发技术加入二元粒子群优化(BPSO)和传统的PSO算法。第一个致力于识别最佳分发网络配置,而第二个用于解决分布式生成(DG)放置和大小写问题。为了评估开发方法的性能,在网络重新配置(NR)和DG集成期间评估了三种不同的负载方案。模拟在两个分配测试系统上进行,即IEEE-33总线和IEEE-69总线。获得的结果清楚地证明了所提出的方法的性能和有效性,以找到开关的最佳状态,以及DG位置和大小。提出了基准比较以证明所提出的MPSO的效率关于其他优化技术。结果表明,在解决方案质量,功率损耗和电压型材增强方面,MPSO优于这些技术。本研究是早期发布的会议论文的延伸。

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  • 来源
    《Refocus》 |2020年第9期|37-46|共10页
  • 作者

    Sirine Essallah; Adel Khedher;

  • 作者单位

    University de Sousse Ecole Nationale d'lngenieurs de Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems 4023 Sousse Tunisie;

    University de Sousse Ecole Nationale d'lngenieurs de Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems 4023 Sousse Tunisie;

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