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首页> 外文期刊>Journal of intelligent & fuzzy systems: Applications in Engineering and Technology >A hybrid fuzzy-PEM stochastic framework to solve the optimal operation management of distribution feeder reconfiguration considering wind turbines
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A hybrid fuzzy-PEM stochastic framework to solve the optimal operation management of distribution feeder reconfiguration considering wind turbines

机译:混合模糊-PEM随机框架,用于解决考虑风力涡轮机的配电馈线重构的最优运行管理

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This paper proposes a new stochastic framework based on point estimate method to solve the optimal operation management of Distribution Feeder Reconfiguration (DFR) considering several Wind Turbines (WTs) in the system. The proposed method can properly solve the complex and discrete DFR optimization problem by the use of an adaptive modification approach based on firefly algorithm (FA). In addition, a new stochastic solution based on 2m Point Estimate Method (2m PEM) is proposed to handle the uncertainty associated with the problem random variables including the active and reactive loads as well as the wind speed variations effectively. The problem is then formulated in a multi-objective optimization structure including four significant targets: 1) active power losses, 2) bus voltage deviation, 3) total system costs and 4) total pollution produced. As a result of the conflicting behavior of the four objective functions, a fuzzy based clustering technique is employed to reach the set of optimal solutions called Pareto solutions. The feasibility and satisfying performance of the proposed method is examined on the IEEE 32-bus standard test system.
机译:本文提出了一种基于点估计的随机框架,解决了考虑系统中多个风力发电机组的配电馈线重构的最优运行管理问题。所提出的方法可以通过使用基于萤火虫算法(FA)的自适应修改方法来正确解决复杂和离散的DFR优化问题。此外,提出了一种基于2m点估计方法(2m PEM)的新随机解决方案,以有效处理与问题随机变量(包括有功和无功负载)以及风速变化有关的不确定性。然后,该问题以多目标优化结构提出,包括四个重要目标:1)有功功率损失; 2)母线电压偏差; 3)系统总成本; 4)产生的总污染。由于这四个目标函数的行为冲突,因此采用了基于模糊的聚类技术来获得称为Pareto解的最优解集。在IEEE 32总线标准测试系统上研究了该方法的可行性和令人满意的性能。

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