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首页> 外文期刊>Power Systems, IEEE Transactions on >Comprehensive Cost Minimization in Distribution Networks Using Segmented-Time Feeder Reconfiguration and Reactive Power Control of Distributed Generators
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Comprehensive Cost Minimization in Distribution Networks Using Segmented-Time Feeder Reconfiguration and Reactive Power Control of Distributed Generators

机译:使用分段时间馈线重新配置和分布式发电机的无功功率控制,在配电网中全面降低成本

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摘要

In this paper, an efficient methodology is proposed to deal with segmented-time reconfiguration problem of distribution networks coupled with segmented-time reactive power control of distributed generators. The target is to find the optimal dispatching schedule of all controllable switches and distributed generators' reactive powers in order to minimize comprehensive cost. Corresponding constraints, including voltage profile, maximum allowable daily switching operation numbers (MADSON), reactive power limits, and so on, are considered. The strategy of grouping branches is used to simplify the formulated mathematical problem and a hybrid particle swarm optimization (HPSO) method is presented to search the optimal solution. Fuzzy adaptive inference is integrated into basic HPSO method in order to avoid being trapped in local optima. The proposed fuzzy adaptive inference-based hybrid PSO algorithm (FAHPSO) is implemented in VC++ 6.0 program language. A modified version of the typical 70-node distribution network and several real distribution networks are used to test the performance of the proposed method. Numerical results show that the proposed methodology is an efficient method for comprehensive cost minimization in distribution systems with distributed generators.
机译:本文提出了一种有效的方法来解决配网的分段时间重新配置问题以及分布式发电机的分段时间无功控制。目标是找到所有可控开关和分布式发电机无功功率的最佳调度时间表,以最大程度地降低综合成本。考虑了相应的约束条件,包括电压曲线,最大允许的每日开关操作次数(MADSON),无功功率限制等。采用分支策略简化了数学公式,提出了一种混合粒子群算法(HPSO)来寻找最优解。模糊自适应推理被集成到基本的HPSO方法中,以避免陷入局部最优中。提出的基于模糊自适应推理的混合PSO算法(FAHPSO)是用VC ++ 6.0程序语言实现的。典型的70个节点的配电网络和几个实际的配电网络的修改的版本用于测试该方法的性能。数值结果表明,所提出的方法是一种在具有分布式发电机的配电系统中实现综合成本最小化的有效方法。

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