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A novel multi-objective self-adaptive modified θ-firefly algorithm for optimal operation management of stochastic DFR strategy

机译:随机DFR策略最优运行管理的新型多目标自适应改进θ-萤火虫算法

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摘要

This paper suggests a new self-adaptive modification method using firefly algorithm (FA) to investigate the multi-objective probabilistic distribution feeder reconfiguration problem. In this regard, the idea of phase angle vector is employed to replace the traditional Cartesian framework in the FA and thus called θ-FA. Also, a new modification method based on an adaptive mechanism is suggested that will allow each firefly to choose the appropriate modification technique during the optimization suitably. As regards the objective functions, the main focus of this paper is to assess the effect of the reconfiguration on the reliability indices including active power losses, voltage deviation, and system average interruption frequency index. In order to handle the uncertainty effects, a sufficient framework based on 2m+ 1 point estimate method is proposed too. The satisfying performance of the proposed method is checked using IEEE 32-bus radial distribution system. Copyright © 2014 John Wiley & Sons, Ltd.
机译:本文提出了一种使用萤火虫算法(FA)的自适应修改方法,以研究多目标概率分布馈线重构问题。在这方面,采用相角矢量的思想来代替FA中的传统笛卡尔框架,因此称为θ-FA。此外,提出了一种基于自适应机制的新的修改方法,该方法将允许每个萤火虫在优化过程中适当地选择适当的修改技术。关于目标函数,本文的主要重点是评估重新配置对可靠性指标的影响,这些指标包括有功功率损耗,电压偏差和系统平均中断频率指标。为了处理不确定性影响,还提出了一个基于2m + 1点估计方法的充分框架。使用IEEE 32总线径向分配系统检查了所提出方法的令人满意的性能。版权所有©2014 John Wiley&Sons,Ltd.

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